While some discussions reference a “Florida AI Bill of Rights,” there is currently no enacted Florida statute formally titled that. Instead, Florida has passed the Florida Digital Bill of Rights (2023), a consumer data privacy law that includes provisions relevant to profiling and automated data processing. Additionally, the state has addressed AI in specific contexts such as election-related disclosures and government use. 

Gary and Scott separate terminology from law and explain what Florida’s existing legislation means for enterprises deploying AI systems today. 

In this episode, they discuss: 

• What the Florida Digital Bill of Rights covers — and how it intersects with AI 
• How profiling and automated decision-making may trigger compliance obligations 
• The difference between proposed AI frameworks and enacted statutes 
• How state-level developments interact with federal guidance such as the NIST AI Risk Management Framework 
• What multi-state enterprises should be doing now to strengthen AI governance 

For CIOs, CISOs, HR leaders, general counsel, and board members, this conversation provides a clear, fact-based overview of Florida’s current legal landscape and the broader direction of AI regulation in the United States. 

As AI adoption accelerates, governance maturity — including transparency, documentation, and oversight — is becoming an operational expectation, not just a regulatory response. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Gary and Scott walk through the core shift: security teams used to ask who is the user, where are they going, and is the data allowed to move? In the AI era, the question becomes far more complex: should this semantic content—originating from this identity, device posture, and region—be allowed to influence a reasoning system that can take downstream action? That’s not a firewall rule, URL filter, or traditional CASB problem—it’s a new enforcement model. 

The conversation builds an actionable architecture for securing AI across the global enterprise WAN, including why AI controls must be inline, preventative, and WAN-native. They outline the AI security capability stack—AI traffic classification, semantic inspection, and AI-specific policy enforcement—and explain why enforcement must be bidirectional, since model outputs can be just as risky as prompts. 

From there, the episode tackles the two dominant enterprise realities: securing AI that users consume (often hidden inside SaaS and productivity platforms) and securing AI the enterprise builds, including training pipelines, RAG systems, and agent-driven execution. The hosts also dive into the hardest global constraints—latency, sovereignty, and elastic load—and why distributed enforcement with centralized policy is now mandatory for performance and compliance. 

Finally, they cover what it takes to operationalize AI security over time: derived telemetry (not raw prompt hoarding), explainable policies, automated response integration, continuous governance, and agent privilege reviews—because architecture without operations is theory. 

Key takeaway: AI is now a first-class WAN workload—semantic, stateful, autonomous, latency-sensitive, and globally distributed. Treat it like SaaS and you lose control. Anchor AI security in the WAN and you gain visibility, preventative enforcement, and durable governance at enterprise scale. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

In this episode of the Macro AI Podcast, Gary Sloper and Scott Bryan deliver a deep, authoritative discussion on AI protocols for retail, focusing on two of the most important early standards shaping agent-driven commerce today: Universal Commerce Protocol (UCP) and Agentic Commerce Protocol (ACP). 

The episode begins with the origin of UCP and ACP, explaining why these AI commerce protocols were created, who is driving them, and how they reflect two different approaches to enabling AI-powered retail transactions. Gary and Scott then break down how UCP and ACP work technically, translating complex protocol concepts into clear explanations for business and technology leaders. 

Listeners will learn how UCP standardizes commerce capabilities across retailers, enabling AI agents to discover products, manage carts, initiate checkout, and handle post-purchase workflows, while ACP focuses on structured, conversational, agent-led buying experiences designed for AI assistants operating in real time. 

Beyond the technology, the discussion explores what AI protocols mean for retail leaders, including: 

• How AI agents may reshape digital commerce architecture 
• Why data quality, pricing logic, and fulfillment accuracy are becoming critical competitive advantages 
• What agent-first commerce means for brand control, customer experience, and retail strategy 
• Why UCP and ACP represent early-stage infrastructure, not finished standards 

The hosts emphasize that AI commerce protocols are still in their early stages, and no one yet knows which standards will dominate or how they will evolve. However, understanding UCP, ACP, and the broader shift toward agentic commerce is becoming essential for CIOs, CTOs, CFOs, and retail executives planning for the future of AI-driven retail. 

This episode is designed for leaders who want to move beyond hype and gain practical insight into how AI protocols could redefine retail commerce over the next several years. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

In this episode of the Macro AI Podcast, Gary Sloper and Scott Bryan break down the energy reality behind artificial intelligence, from individual AI usage to hyperscalers and national infrastructure strategy. They explain where AI actually consumes power, why your laptop is just the remote control, and how every prompt to a large language model triggers real energy use inside GPU-powered data centers. 

The conversation scales from home offices to enterprises, introducing the concept of the “shadow data center” — the hidden energy footprint organizations incur when using AI through SaaS platforms and APIs. Even without owning infrastructure, businesses are consuming significant AI-driven electricity at scale. 

Gary and Scott then examine how many gigawatts of new data center capacity are being planned in the U.S. and globally, why grid timelines are becoming the true bottleneck for AI growth, and how energy availability is reshaping competition between the United States and China. 

Bottom line: AI strategy without energy awareness is incomplete. The future of AI will be written in code — but powered by electrons. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

As organizations move beyond AI pilots and demos, many are discovering that AI isn’t failing because of the models—it’s failing because of integration, governance, and cost. This episode explores why enterprise AI so often hits scaling walls and how MCP is emerging as a critical piece of infrastructure to remove them. 

The conversation breaks down MCP at a practical, executive level—explaining how it standardizes the way AI systems discover, understand, and safely interact with enterprise tools and data. Gary and Scott walk through why traditional API-based integrations struggle in AI-driven environments, how MCP changes the N-by-M integration problem, and why this matters for CIOs, CFOs, and CEOs planning long-term AI strategies. 

A major focus of the episode is AI economics, including a deep dive into token costs—one of the most misunderstood and underestimated drivers of enterprise AI spend. Using clear, real-world examples, the discussion shows how MCP can dramatically reduce token usage, improve performance, and turn unpredictable inference costs into a controllable operating expense. 

The episode also covers: 

• Why MCP fundamentally changes the economics of scaling enterprise AI 
• How token efficiency directly impacts ROI, latency, and adoption 
• The infrastructure and total cost of ownership tradeoffs leaders need to understand 
• Governance risks, including the rise of “shadow MCP,” and why centralized oversight matters 
• How MCP complements—not replaces—RAG in modern enterprise AI architectures 

Bottom line: MCP is not a feature or a framework—it’s becoming core infrastructure for serious enterprise AI. If you’re responsible for AI strategy, governance, or budgets, this episode explains why MCP belongs on your radar now. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

They explore how Amazon Web Services is using custom silicon like Trainium to shift enterprises from renting AI to building and owning it—and why that strategy only works when customers go deeper into the AWS ecosystem. This isn’t about winning benchmark battles; it’s about creating economic gravity around where AI gets built. 

The conversation also tackles the question every executive is asking: How does this compare to Nvidia? While NVIDIA continues to dominate AI innovation and experimentation, AWS is focused on industrial-scale economics—making large, repeatable training workloads cheaper, more predictable, and easier to operationalize inside its cloud. 

Gary and Scott then connect the dots to real enterprise strategy, including: 

• Why AI infrastructure decisions are becoming long-term financial commitments 
• How custom chips influence cloud pricing power and cost curves 
• The rise of multi-cloud strategies that separate AI innovation from AI economics, including the role of Oracle Cloud Infrastructure as a cost-efficient execution layer 
• Why FinOps is becoming essential as AI training, retraining, and inference costs compound over time 

The key takeaway for business leaders: AI advantage won’t come from simply adopting the latest models. It will come from who controls the economics of building, scaling, and evolving AI over the next decade. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Rather than focusing on hype, the conversation starts with fundamentals. What does ChatGPT Health actually do? What systems can it connect to? How does it stay current with your health information? And how is it architected to operate safely inside one of the most regulated domains in the world? 

From there, Gary and Scott explore how OpenAI has deliberately framed ChatGPT Health as a grounded, trust-first intelligence layer, designed to interpret and explain verified health data—rather than replace clinicians or generate unbounded medical advice. They discuss the technical architecture behind the platform, including interoperability, real-time contextual data assembly, and the “health sandbox” model that keeps personal data isolated and protected. 

The conversation then zooms out to examine the macro implications: the end of “Dr. Google,” the shifting role of patients and clinicians, the redistribution of cognitive labor in healthcare, and the emerging governance questions around data sovereignty and AI-mediated decision-making. 

Finally, the episode connects these lessons to a broader business audience—explaining why ChatGPT Health isn’t just a healthcare story, but a blueprint for how AI will move into the interpretation layer of complex, high-stakes industries everywhere. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

In this episode of the Macro AI Podcast, Gary and Scott unpack the most important recent research on AI and labor markets, including Vanguard’s 2025–2026 “Job Growth Paradox,” the IMF’s AI preparedness and global stability warnings, and the Roosevelt Institute’s analysis of who really captures AI-driven productivity gains. 

Rather than asking whether AI will eliminate jobs, this discussion explores a more nuanced—and more urgent—set of questions: 

• Why are some of the most AI-exposed roles seeing higher wages and increased hiring? 
• How does AI change demand, productivity, and firm-level growth? 
• Why could AI widen global and organizational inequality if leaders aren’t intentional? 
• What does the shift from task execution to direction and orchestration mean for leadership, talent, and career paths? 

Gary and Scott examine how AI is reshaping work at the task level, why demographics and labor scarcity matter more than most headlines suggest, and how agentic AI systems are accelerating the move toward an “economy of direction.” 

The episode closes with clear, practical guidance for executives on how to think about AI not as a cost-cutting tool—but as a capacity-expansion strategy that demands new leadership choices. 

If you’re a business leader trying to understand what AI really means for jobs, growth, and competitiveness in 2026, this is a conversation you won’t want to miss. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Announced in mid-December 2025 by the U.S. Office of Personnel Management with White House backing, the U.S. Tech Force is designed to recruit highly skilled technologists for time-bound service inside federal agencies. The goal isn’t just IT modernization — it’s building real, internal capability to deploy, govern, and scale AI responsibly across government. 

Gary and Scott walk through how the initiative came together, why it’s structured around skills rather than degrees, and why the initial target of roughly 1,000 technologists is intentional. They explore how even small numbers of deeply technical talent can unlock stalled AI projects, modernize legacy systems, and reduce long-term reliance on external vendors. 

The conversation also connects the dots for business leaders. As government modernizes and embeds AI expertise internally, expectations around procurement, compliance, interoperability, and data standards will rise. The episode examines how this initiative could influence the future AI talent pipeline, shape public-sector AI standards, and eventually evolve into a permanent federal technology or AI corps. 

If you’re a business leader, technologist, or policymaker trying to understand what the U.S. Tech Force is, why it matters, and what it signals about the future of AI talent and national competitiveness, this episode provides the context you need. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Generative AI is transforming how enterprises operate, but it also introduces an entirely new attack surface. Traditional cybersecurity models were never built for systems that reason, take action, integrate with sensitive data, and can be manipulated through language alone. This episode breaks down what that means for your business, your customers, and your risk posture. 

Gary and Scott guide you through the full lifecycle of securing GenAI: how these systems fail, where attackers are striking today, how enterprise architectures introduce new vulnerabilities, what frameworks (like NIST’s AI RMF) actually matter, and how leaders should build a modern defense-in-depth strategy tailored specifically for LLMs, RAG pipelines, and AI agents. 

You’ll hear detailed insight into prompt injection, jailbreaks, data poisoning, insecure output handling, RAG access control, observability, vendor risk, and the organizational operating models required to govern AI safely. The episode closes with a clear 30/90/365-day executive roadmap to help any organization move from experimentation to secure, governed AI at scale. 

If you’re a CIO, CISO, CTO, head of data/AI, product leader, or board member tasked with understanding the true cyber risks of GenAI, this episode is your playbook. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

For decades, carriers have delivered connectivity as a static, reactive utility. But AI workloads are fundamentally breaking traditional network designs. Large enterprises running global inference pipelines, real-time analytics, digital twins, and distributed training now require deterministic latency, workload-aware routing, and transport layers that can predict and self-optimize in real time. 

Gary and Scott explain why the next era of global connectivity will be defined by AI-native networks — intelligent, autonomous systems that continuously sense, anticipate, and orchestrate data flows based on model behavior, compute availability, energy conditions, and regulatory constraints. 

They break down how this shift will transform: 
• Enterprise architecture and global WAN design 
• Latency-sensitive AI applications and GPU cluster connectivity 
• Data governance and cross-border regulatory compliance 
• The business models and competitive landscape of Tier-1 ISPs 

Finally, the episode introduces a real-world blueprint of this future: the emerging partnership between Lumen, one of the world’s largest Tier-1 global networks, and Palantir, an AI-driven decision platform built for national-scale complexity. Gary and Scott explain how this collaboration hints at the telecom industry’s next decade — one where networks become intelligent participants in the AI ecosystem rather than passive transport. 

If you’re a CIO, CTO, global network architect, cloud strategist, or enterprise AI leader, this is a must-listen episode that will reshape how you think about connectivity in the AI era. 

This is the beginning of the intelligent network revolution — and the Macro AI Podcast will keep you up to date on the roadmap

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

The hosts explore how Google evolved from lightweight collaboration apps to a full AI automation platform, what lessons they learned from Duet AI, and how Workspace Studio changes the game for businesses that rely on Google Workspace. Gary and Scott dive into real use cases for HR, finance, sales, marketing, and knowledge management, and they compare Workspace Studio to Microsoft Copilot Studio to help leaders understand which platform delivers the most value. 

They also cover the risks, governance challenges, ethical considerations, and where AI agents are headed next—including the rise of digital coworkers with persistent memory. 

If your teams live inside Google Workspace, or if you’re evaluating the future of AI-driven productivity, this episode is essential listening. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

We break down where the technology stands today, the breakthrough use cases unfolding in consumer and enterprise environments, and how AI is turning ordinary glasses into contextual, multimodal assistants that can interpret the world in real time. 

Then we go deeper. CIOs, CTOs, and digital leaders will get a full technical walkthrough of how smart eyewear integrates into an enterprise tech stack — including identity, zero-trust security, backend APIs, data governance, edge vs. cloud AI, workflow orchestration, networking requirements, and build-vs-buy considerations. If your organization is planning pilots or evaluating AR/AI wearables, this segment provides the architecture-level clarity most companies are missing. 

We also unpack the privacy, legal, and ethical challenges of putting a camera and an AI agent two inches from the human eye — from workplace monitoring to bystander consent to accessibility and equitable deployment. 

Whether you’re a business leader exploring AI transformation, a technologist thinking about new platforms, or just curious where everyday computing is headed, this is a must-listen conversation. 

Topics covered include: 
• The evolution of smart eyewear and why adoption is accelerating 
• Real consumer and enterprise use cases already delivering ROI 
• How AI is shifting glasses from passive cameras to active “perceptual agents” 
• Technical architecture for enterprise integration 
• Data protection, identity, and zero-trust considerations 
• Privacy, surveillance, and ethical implications 
• What the next 3–7 years of wearable AI will look like 

Smart eyewear isn’t a gadget — it’s the beginning of a new interface era. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Gary and Scott unpack the three big buckets of state AI rules, from comprehensive frameworks in Utah, Colorado, and Texas to targeted laws on deepfakes, hiring algorithms, mental-health chatbots, and digital replicas. They also explore how regulators are using existing consumer-protection laws to police AI even in states without formal AI acts. 

Listeners will hear why 2025 has become a turning point in AI governance, how the federal government’s attempted preemption triggered a tug-of-war with state attorneys general, and what common themes are emerging across the country. 

Most importantly, Scott and Gary translate the entire mess into a clear, practical playbook for executives. They explain how to build an AI inventory, assess high-risk systems, align to the strictest state standards, tighten vendor governance, and prepare for inquiries from regulators — all without slowing down innovation. 

Whether you’re a CEO, CIO, or someone building AI into your products, this episode will help you understand the new regulatory reality and how to thrive in it. 

Perfect for: 
Business leaders, AI COEs, CTOs, product teams, compliance professionals, and anyone deploying AI across multiple U.S. states. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

They compare K2 to OpenAI, Anthropic, DeepSeek, and Qwen, explain the significance of its open-weights release, and analyze what this means for Western enterprises, policymakers, and the broader U.S.–China AI competition. 

A must-listen for anyone tracking the global AI race, national competitiveness, or enterprise-grade LLM deployment strategies. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

In this episode, Gary and Scott break down: 
• What Project Prometheus is — and what we actually know so far 
• Why it’s attracting elite talent from OpenAI, DeepMind, and Meta 
• The meaning of “AI for the physical economy,” explained in simple terms 
• How Bezos and co-leader Vik Bajaj are positioning this as a multi-decade moonshot 
• The emerging shift from digital AI to AI that designs, builds, and optimizes physical systems 
• Potential applications: factories that self-optimize, AI-designed materials, robotic labs, new aerospace components, and more 
• The profound implications for business leaders across manufacturing, engineering, logistics, and operations 
• The risks, unknowns, and why Prometheus could reshape competitive advantage for entire industries 

This is one of the clearest signals yet that AI is moving beyond screens and into the world of atoms. If you’re a CIO, COO, CTO, or executive responsible for operations or innovation, this episode will give you a front-row view into the next wave of AI transformation — and what you should be watching now. 

Listen in and learn why the future of AI won’t just be about thinking… it’ll be about building. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

We break down: 

• Why AI literacy is now a foundational skill 
• How schools can shift from fear to structure 
• The four-tier AI policy every school should adopt 
• Real-world classroom examples across English, math, science, history, and languages 
• How parents can support responsible AI use at home 
• A practical 90-day action plan for school leaders 

If you’re a parent, teacher, principal, or district leader wondering how to navigate AI in education, this episode gives you a clear, practical roadmap. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Apple AI partnership, Google Gemini, Siri upgrade, DeepMind, Transformer architecture, Google Research 2017, TPU Trillium, word2vec, Google Brain, Jeff Dean, Demis Hassabis, Macro AI Podcast 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

They explain what Palantir actually is (and isn’t), how its four platforms — Gotham, Foundry, Apollo, and AIP — work together to fuse data, decisions, and actions, and why its ontology-driven architecture has become the blueprint for operational AI at scale. 

The conversation explores Palantir’s: 

• Government and commercial growth engine, including NHS and DoD programs 
• Financial transformation into a profitable, recurring-revenue software company 
• Competitive landscape, from cloud hyperscalers (Microsoft, AWS, Google, IBM, Oracle) to modern AI platforms (Databricks, Snowflake, C3.ai), BI specialists (Tableau, Splunk, Alteryx, SAS), and defense-sector rival Govini 
• Platform differentiation — how Palantir uniquely unifies structured and unstructured data into a single, governable operating system 

Gary and Scott close with practical lessons for executives: how to evaluate enterprise AI platforms, what to ask vendors, and why Palantir’s model represents the next phase of AI transformation — moving beyond analytics toward true decision infrastructure. 

Whether you’re a CEO, CIO, or board member exploring how to operationalize AI responsibly, this episode gives you the clearest explanation yet of what makes Palantir different — and why its approach may define the next decade of enterprise intelligence. 

Links & References: 

• Palantir Investor Relations – Quarterly Results and AIP Overview 
• Govini Ark Platform Overview 
• Macro AI Podcast Executive AI Readiness Checklist 

SEO Tags / Keywords 

palantir technologies, palantir ai, palantir explained, palantir foundry, palantir gotham, palantir aip, palantir apollo, enterprise ai, ai for business, data ontology, ai operating system, macro ai podcast, gary and scott, ai transformation, databricks vs palantir, snowflake ai, govini defense analytics, artificial intelligence platforms, ai governance, ai decision making, ai strategy for executives 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Listeners will learn how Walmart is leveraging this partnership to expand its digital reach, strengthen its retail-media flywheel, and transform from a traditional retailer into a data-driven AI platform. The hosts also unpack what this means for OpenAI’s evolving business model, as commerce becomes a core workload for ChatGPT and a foundation for agent-based ecosystems. 

The conversation covers: 

• 🧭 Strategic Implications: How Walmart gains share-of-basket and new demand surfaces beyond walmart.com 
• 🧠 Technical Breakdown: How AI agents plan, retrieve, rank, and execute orders using retrieval-augmented generation, constraint solving, and real-time checkout orchestration 
• ⚙️ Optimization Insight: Why planning a shopping cart is a “knapsack scheduling problem under uncertainty” — and how that’s reshaping AI logistics 
• ⚖️ Governance & Risk: Hallucinations, ranking fairness, privacy, and accountability in agent-driven transactions 
• 🚀 Future of Retail (2025–2035): From persistent household twins to multimodal perception, agent media, and composable fulfillment 

Gary and Scott explore what this means for CIOs, CFOs, and strategy leaders who need to prepare for AI-driven commerce infrastructure — where assistants become execution engines and supply chains become conversational. 

If you want to understand how Walmart × OpenAI is quietly redefining the economics of retail and why this partnership will shape the next decade of consumer behavior, this is the episode you can’t miss. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

They explain what a Data Commons is, how it differs from traditional data lakes, and why it’s essential to the next phase of AI transformation. From Google’s global Data Commons and the NIH’s biomedical repositories to emerging “Private Data Commons” inside enterprises, the hosts show how these ecosystems are reshaping trust, governance, and efficiency. 

Listeners will learn how Data Commons reduce AI hallucination, enable grounding, improve reproducibility, and support ethical AI. Gary and Scott also explore governance models, global equity, and the rise of AI agents that automatically fetch verified data from commons networks. 

If you’re a CIO, CTO, or business leader preparing your organization for AI, this episode offers the strategic framework you’ll need to understand the infrastructure of the future. 

🔗 Links mentioned: 

• Google Data Commons 
• Open Data Policy Lab — AI Data Commons Blueprint 
• Therapeutics Data Commons 
• NIH Data Commons 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

They dive deep into Yale University’s Budget Lab study, “Evaluating the Impact of AI on the Labor Market: Current State of Affairs” (October 2025), which concludes that there has been no discernible economy-wide labor disruption since the launch of ChatGPT in late 2022. Using decades of labor data, the Yale team found that the pace of occupational change today looks remarkably similar to earlier waves of innovation like the PC and Internet eras. 

But Gary and Scott don’t stop there. They explore contradictory findings from other top institutions: 

• Stanford’s Digital Economy Lab (Aug 2025): Early-career workers in AI-exposed jobs have seen employment drop by roughly 13%, signaling localized disruption. 
• IMF (2024): Up to 40% of jobs globally are exposed to AI, especially in advanced economies. 
• OECD & WEF (2024–25): AI is already reshaping skills demand, with executives expecting major restructuring by 2030. 

Throughout the episode, Gary and Scott translate these insights into an executive playbook for 2025: 
✅ Build an internal AI exposure map by task. 
✅ Track real adoption and productivity telemetry. 
✅ Reinvent early-career roles through apprenticeships. 
✅ Reinvest AI gains into upskilling and responsible adoption. 

The takeaway?
No broad labor shock yet—but localized tremors are real. 
The smartest leaders are already using data to navigate the gray zone between augmentation and automation. 

Referenced Research: 

• Yale Budget Lab (2025): Evaluating the Impact of AI on the Labor Market: Current State of Affairs 
• Stanford Digital Economy Lab (2025): AI Exposure and Early-Career Employment Effects (working paper) 
• IMF (2024): Generative AI and the Future of Work 
• OECD Employment Outlook (2024): AI, Skills, and the Changing Labor Market 
• World Economic Forum (2025): Future of Jobs Report 

Takeaway:
AI is transforming how we work, not yet how many of us work. Stay adaptive, build visibility into your workforce data, and lead with metrics—not headlines. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

So what exactly is a privacy engineer? They’re the bridge between regulators and technologists. Their mission is to embed privacy by design into AI systems, turning complex laws like GDPR, HIPAA, California’s CPRA, and the EU AI Act into concrete technical safeguards. From minimizing sensitive data in training pipelines to stress-testing models for leaks, these engineers are the ones who make sure your AI is trustworthy, compliant, and resilient. 

The timing could not be more urgent. The EU AI Act comes into full force in 2026, while in the U.S., the FTC is already forcing companies to delete models trained on tainted data. Without privacy engineers, businesses risk not just fines but also losing the very models they’ve invested millions in. 

Gary and Scott dive into: 

• How privacy engineers protect the AI lifecycle—from data collection to model deployment. 
• Why businesses of every size need this role, with different priorities for startups, mid-market firms, and global enterprises. 
• The ROI story: Cisco research shows a nearly 2x return on privacy investments, driven by faster sales cycles and stronger customer trust. 
• A practical roadmap for building privacy capacity—starting small with guardrails and scaling up to ISO 42001 certification readiness. 
• And new in this episode: the talent pipeline challenge. Where do you find these people? The best privacy engineers often start as ML engineers, security professionals, or graduates of specialized programs like Carnegie Mellon’s Privacy Engineering track. But supply is thin, so forward-looking enterprises are upskilling internal talent, partnering with consultancies, and competing aggressively to hire the rare hybrid who can talk about both differential privacy and the NIST AI Risk Management Framework. 

The bottom line: Privacy Engineers for AI aren’t just compliance hires. They future-proof your AI investments, accelerate growth, and turn privacy into a strategic differentiator in an era where trust is the new currency. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

AI Workslop describes polished, AI-generated work that looks good on the surface but lacks the substance, accuracy, or context to drive real decisions. It’s the long memo with no action, the glossy slide deck without insight, the email that shifts the burden onto the reader. And it’s not just annoying — it’s expensive. 

Recent research from Harvard Business Review, BetterUp Labs, and Stanford found that: 

• 40% of desk workers encountered AI Workslop in the last month. 
• Each incident wasted nearly 2 hours. 
• The hidden cost adds up to $186 per employee per month — over $9M annually for a 10,000-person company. 
• Colleagues perceive Workslop senders as less creative, less capable, and less reliable. 

In this episode, Gary and Scott explore: 

• What AI Workslop is — and how it differs from AI hallucinations. 
• Why it happens (old habits, new tools, and cultural pressure). 
• How leaders can spot Workslop before it derails productivity. 
• Why prompting skill matters — and why it’s not the full cure. 
• The Anti-Workslop Playbook: leadership guardrails, workflow templates, training strategies, and metrics. 
• Real-world examples of slop vs. substance in sales, operations, and contact centers. 
• The single KPI executives should watch: time-to-decision. 

AI isn’t the problem. Workslop is. And leaders who build the right norms, culture, and skills will see ROI instead of sludge. 

🔗 Resources mentioned in this episode: 

• Harvard Business Review article introducing “AI Workslop” (Sept 2025): https://hbr.org/2025/09/ai-workslop 
• BetterUp Labs research and resources: https://www.betterup.com/resources/research/ai-workslop  
• Stanford Social Media Lab collaboration: https://sml.stanford.edu  

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Michael shares his perspective on why agility and flexibility in connectivity are now strategic imperatives for CIOs, CTOs, and CFOs—and how Megaport is positioning itself at the heart of this transformation. We discuss the company’s recent global expansion, the impact of Project Centurion’s 400G backbone upgrade, and what enterprises need to think about as AI workloads demand more bandwidth, lower latency, and tighter integration across multiple clouds. 

Listeners will hear insights on: 

• How enterprises can simplify multicloud strategies while maintaining performance and security. 
• The role of software-defined networking in accelerating digital transformation. 
• Why infrastructure investments like Project Centurion are foundational to AI adoption. 
• Practical advice for decision-makers navigating the convergence of networking, cloud, and AI. 

Michael also highlights where Megaport is heading next, from enabling new AI-centric services to supporting the rapid evolution of edge computing. For executives thinking about how to future-proof their connectivity strategies, this episode delivers both strategic guidance and actionable insights. 

Want more from Megaport? Don’t miss their own podcast, Uplink, where Michael and his team dive deeper into connectivity, cloud adoption, and the future of digital infrastructure. It’s the perfect complement to today’s conversation. You can listen here: https://www.megaport.com/uplink 

If you enjoyed this episode, please subscribe to The Macro AI Podcast, share it with colleagues, and stay tuned for more conversations at the intersection of AI, infrastructure, and business transformation. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

We start with the basics: what CCaaS actually is, why it matters, and who the leading players are — from established platforms like Five9, NICE, Genesys, and Avaya to innovators such as Verint, Talkdesk, 8x8, Microsoft, Zoom, eGain, and Observe.AI. This sets the stage for sourcing decisions and gives listeners a realistic view of the vendor ecosystem. 

From there, we dive into where CX stands today. Companies have chatbots, transcription tools, and AI-driven coaching — but most of it is fragmented. The real future is orchestration: AI systems that not only interact with customers but orchestrate workflows across humans, machines, and enterprise systems. 

Looking ahead, Gary and Scott explore four insights executives may not have considered: 

• Contact centers as insight engines — mining every customer interaction for churn risk, product feedback, and revenue opportunities. 
• A shift in the economic model — from cost-per-seat to outcome-based pricing tied to resolution, containment, or customer satisfaction. 
• Regulatory blind spots — how compliance, transparency, and trust will define CX success as much as speed and efficiency. 
• The organizational shift — why CX won’t remain a siloed department but will evolve into an enterprise-wide orchestration function. 

The episode also highlights the role of independent AI consultants in bridging the gap between technology and business outcomes. From assessing data readiness and designing orchestration fabrics to implementing governance frameworks, consultants help companies avoid vendor lock-in and align AI to their unique business models. 

For CIOs, COOs, and CEOs, the message is clear: the companies that start building AI fluency and governance now will be the ones delivering tomorrow’s customer experience. The future of CX is not just faster service — it’s intelligent, predictive, and woven into the fabric of the entire enterprise. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

What does it mean for an AI system to be robust? In simple terms, it’s the ability to keep performing under stress — when the data is messy, unexpected, or even deliberately manipulated. Without robustness, AI that looks flawless in a demo can fail spectacularly in production, creating business risks instead of business value. 

Gary and Scott break it all down for business leaders, connecting technical concepts to practical outcomes. You’ll learn: 

• Why accuracy is not enough — accuracy is practice, robustness is game day. 
• Real-world examples of AI failures across healthcare, finance, retail, and even autonomous vehicles. 
• How organizations can build robustness into their AI systems through diverse data, stress testing, fallback mechanisms, and advanced methods like adversarial training and ensembles. 
• Ways to measure robustness, from stress-test error rates to cross-domain testing and robustness curves. 
• The growing role of third-party robustness testing, which is quickly becoming the AI equivalent of cybersecurity penetration testing. 
• The high cost of ignoring robustness — from financial losses to reputational damage. 
• Why future enterprise AI will require independent certifications, insurance validation, and proof of resilience to win trust. 

For executives, the message is clear: robustness equals trust. If you can’t trust your AI under pressure, you can’t scale it. Robustness is no longer a technical “nice-to-have” — it’s a business differentiator, a regulatory expectation, and the foundation for long-term AI success. 

Whether you’re a CEO, CIO, CFO, or a technical leader building AI systems, this episode will give you the insights, analogies, and practical takeaways to put robustness at the center of your AI strategy. 

Key soundbites: 

• “AI without robustness is like a self-driving car that only works in the sunshine.” 
• “Accuracy is practice. Robustness is game day.” 
• “Third-party robustness testing will soon be as common as penetration testing.” 

Good Reference Article:  Machine Learning Robustness A Primer 

Tune in and learn how to future-proof your AI investments. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

What does it mean for an AI system to be robust? In simple terms, it’s the ability to keep performing under stress — when the data is messy, unexpected, or even deliberately manipulated. Without robustness, AI that looks flawless in a demo can fail spectacularly in production, creating business risks instead of business value. 

Gary and Scott break it all down for business leaders, connecting technical concepts to practical outcomes. You’ll learn: 

• Why accuracy is not enough — accuracy is practice, robustness is game day. 
• Real-world examples of AI failures across healthcare, finance, retail, and even autonomous vehicles. 
• How organizations can build robustness into their AI systems through diverse data, stress testing, fallback mechanisms, and advanced methods like adversarial training and ensembles. 
• Ways to measure robustness, from stress-test error rates to cross-domain testing and robustness curves. 
• The growing role of third-party robustness testing, which is quickly becoming the AI equivalent of cybersecurity penetration testing. 
• The high cost of ignoring robustness — from financial losses to reputational damage. 
• Why future enterprise AI will require independent certifications, insurance validation, and proof of resilience to win trust. 

For executives, the message is clear: robustness equals trust. If you can’t trust your AI under pressure, you can’t scale it. Robustness is no longer a technical “nice-to-have” — it’s a business differentiator, a regulatory expectation, and the foundation for long-term AI success. 

Whether you’re a CEO, CIO, CFO, or a technical leader building AI systems, this episode will give you the insights, analogies, and practical takeaways to put robustness at the center of your AI strategy. 

Key soundbites: 

• “AI without robustness is like a self-driving car that only works in the sunshine.” 
• “Accuracy is practice. Robustness is game day.” 
• “Third-party robustness testing will soon be as common as penetration testing.” 

Good Reference Article:  Machine Learning Robustness A Primer 

Tune in and learn how to future-proof your AI investments. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Sarah provides excellent insight into how organizations can begin their AI journey breaking down areas to focus including in some instances using CPUs over GPUs.  

Have a listen and hear about Sarah’s journey in AI.  Oh, and she’s an amazing Tri-athlete.

Sarah’s profile:  https://www.linkedin.com/in/sczumbrum/

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

In this episode of The Macro AI Podcast, hosts Gary and Scott dive into America’s AI Action Plan, a July 2025 White House roadmap to secure U.S. leadership in the global AI race. This 28-page document outlines three pillars—Accelerating AI Innovation, Building AI Infrastructure, and Leading International AI Diplomacy—to drive economic growth, national security, and technological dominance. 

Segment 1: Why It Matters 
The plan positions AI as a catalyst for an industrial, information, and cultural renaissance, emphasizing that the nation with the largest AI ecosystem will set global standards. 

Segment 2: Pillar I – Accelerating AI Innovation 
The first pillar focuses on unleashing private-sector innovation by removing bureaucratic barriers, like rescinding Biden’s Executive Order 14110. Regulatory sandboxes and AI Centers of Excellence enable rapid testing of AI tools, especially in healthcare and energy. The plan promotes open-source AI models, ensuring startups can innovate without relying on big tech. Federal funding will enhance access to compute resources, and workforce initiatives, including tax-free AI training reimbursements, aim to upskill workers, complementing rather than replacing jobs. 

Segment 3: Pillar II – Building AI Infrastructure 
AI demands robust infrastructure—data centers, semiconductors, and energy. The plan streamlines permitting for data centers via NEPA exclusions and FAST-41 reforms, ensuring faster deployment. It addresses energy needs by stabilizing the U.S. grid and preventing power source decommissioning. The CHIPS Act bolsters domestic semiconductor production, reducing reliance on foreign supply chains. Cybersecurity is prioritized with secure-by-design AI and a skilled workforce trained for infrastructure roles. 

Segment 4: Pillar III – International AI Diplomacy 
This pillar aims to make American AI the global standard by exporting to allies and countering external influence in governance bodies. Strengthened export controls protect AI compute and chips, while biosecurity investments address risks in synthetic biology. The TAKE IT DOWN Act combats synthetic media, ensuring trust in AI.

Segment 5: Technical Deep Dive 
For tech enthusiasts, the plan invests in AI interpretability via DARPA, enhancing trust in high-stakes applications like defense. NIST’s AI Evaluations Ecosystem standardizes reliability metrics, and secure compute environments at NSF and DOE protect sensitive data. Open-source support and hackathons foster innovation. 

Segment 6: Practical Advice 
Business leaders should join sandboxes, upskill teams with federal programs, secure AI stacks with U.S. tech, and align with American AI standards for global markets. Visit whitehouse.gov for the full plan. Tune in for actionable insights to le

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

• Business Leaders: Start with a high-impact AIoT pilot (e.g., smart logistics) to drive ROI. 
• Tech Teams: Prioritize secure, interoperable systems using MQTT/CoAP and robust data pipelines. 
• Future-Proofing: Prepare for 6G and decentralized AI to stay competitive. 

With a 2025 McKinsey report estimating AIoT’s $5 trillion GDP impact by 2030, Gary and Scott urge listeners to act now. Tune in for actionable advice and inspiring use cases to transform your business with AIoT! 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

The episode traces the history of CoEs from their 1990s origins in IT and quality control to their modern role as strategic engines for AI innovation. Gary and Scott discuss how early adopters like JPMorgan Chase and Siemens used CoEs for fraud detection and manufacturing optimization, while contemporary examples like Cleveland Clinic’s 2024 CoE showcase multimodal AI for personalized medicine. 

Listeners will learn key steps for building an AI CoE, including securing C-suite sponsorship (backed by a 2025 McKinsey study), assembling multidisciplinary teams with roles like AI strategists and ethicists, and prioritizing quick-win projects to demonstrate value. The hosts also break down three organizational models—Centralized, Federated, and Hybrid—offering insights on their pros, cons, and best use cases, supported by examples like Walmart’s hub-and-spoke approach. 

The episode addresses challenges like talent shortages and governance risks, while highlighting strategies to foster enterprise-wide innovation through hackathons, shared resources, and agile methodologies. Looking ahead, Gary and Scott explore emerging trends like multimodal AI, federated learning, and quantum computing, emphasizing the role of CoEs in navigating regulations like the EU AI Act and driving sustainability. 

Perfect for executives and AI enthusiasts, this episode offers actionable insights for transforming AI from a concept into a competitive differentiator. Tune in to learn how to structure and scale an AI CoE for enterprise success! 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

From his personal career journey to the strategic deployment of AI within Verizon, Michael offers a fascinating look at how large enterprises are identifying and implementing AI use cases to achieve operational efficiencies. Michael shares insights into Verizon’s innovative applications of AI, including the use of propensity modeling and geospatial analysis to proactively mitigate fiber network disruptions, ensuring seamless connectivity for customers. 

 Michael addresses the importance of clean, high-quality data in building robust AI models, a topic that resonates with executives grappling with leveraging historical datasets. For students and job seekers, Michael provides actionable advice on pursuing careers in AI and analytics, emphasizing the skills and mindset needed to thrive in this rapidly evolving field. Beyond technical expertise, he highlights the leadership qualities critical for successfully driving AI initiatives within a complex organization and reflects on the most impactful lessons from his career. 

This episode is packed with practical insights for professionals, aspiring technologists, and anyone curious about the intersection of AI and business. Don’t miss Michael’s inspiring perspective on the future of work in an AI-driven world and his recommendations for the next generation of innovators. 

Subscribe to The Macro AI Podcast on Buzzsprout, share this episode with others, and connect with us at www.macroaipodcast.com or on LinkedIn to submit your questions. Stay curious, keep learning, and join us for the next episode! 

Listen now to explore how Verizon is shaping the future with AI and gain career advice for the AI era!

Guest:  Michael Raj - Vice President - Artificial Intelligence & Data (CDO Organization) at Verizon

https://www.linkedin.com/in/michael83/

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

The hosts dissect the application of AI within the DMAIC framework (Define, Measure, Analyze, Improve, Control) and discuss its implications for practitioners, ethical considerations, and the future of operational excellence. This summary provides a comprehensive overview of the episode’s key insights, offering business leaders actionable guidance for leveraging AI to elevate Six Sigma initiatives.

Introduction to Six Sigma and Its Evolution
 The episode opens with an introduction to Six Sigma, described as a disciplined, data-driven methodology aimed at eliminating defects in processes across industries, from manufacturing to services. AI Agent X explains that Six Sigma targets near-perfection, aiming for a maximum of 3.4 defects per million opportunities (DPMO). AI Agent Y provides historical context, tracing Six Sigma’s roots to the 1920s with Walter Shewhart’s statistical process control, through the Total Quality Management (TQM) movement led by W. Edwards Deming and Joseph Juran, to its formalization by Bill Smith at Motorola in the 1980s. 

The methodology gained prominence in the 1990s under Jack Welch’s leadership at General Electric, becoming a cornerstone for operational efficiency in companies like 3M and Honeywell. Today, Six Sigma, often combined with Lean principles as Lean Six Sigma, is practiced by millions of professionals and adopted by numerous Fortune 500 companies in sectors like healthcare, IT, finance, and supply chain management.AI’s Immediate Impact on the DMAIC Cycle
 The hosts delve into how AI is revolutionizing each phase of the DMAIC cycle, emphasizing that these advancements are already driving significant improvements in real-world applications.

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

 The episode opens with Gary and Scott emphasizing the pivotal role of data labeling in AI development. Data labeling involves tagging raw data—such as images, text, or videos—to enable AI models to recognize patterns and make accurate predictions. Gary likens it to teaching a child to identify animals using labeled pictures, underscoring its foundational importance. Poorly labeled data can lead to flawed AI models, resulting in significant financial and reputational costs. For example, in healthcare, mislabeled medical images could cause incorrect diagnoses, such as missing a tumor, leading to both business and ethical failures. 

Scott highlights the market’s growth, projecting the data labeling industry to expand from $4.8 billion in 2025 to $30 billion by 2032, with a compound annual growth rate (CAGR) of 29%. This growth reflects the increasing demand for high-quality labeled data across industries like healthcare, automotive, and retail. A compelling real-world example is Waymo, the autonomous vehicle company, which relies on meticulously labeled video and sensor data to train self-driving cars to detect pedestrians, traffic signs, and lane markings. High-quality labeling ensures safer vehicles and strengthens Waymo’s market position, while errors could lead to accidents and eroded trust. 

The segment underscores that investing in robust data labeling is not just a technical necessity but a strategic imperative. It reduces risks, enhances customer trust, and drives measurable business outcomes, setting the stage for the episode’s exploration of 2025 trends. 

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Spotlight on AI Startups – Key Players in Each Sector 

AI Infrastructure:  

• Celestial AI: Known for its Photonic Fabric, an optical interconnect technology that reduces AI computing energy costs by up to 90%, Celestial AI raised $250 million in 2025, reaching a $2.5 billion valuation.  
• Lambda: This startup builds AI-optimized cloud platforms for model training, securing $480 million in Series D funding to democratize AI access for businesses.  
• io (formerly epic.io): Acquired by OpenAI for $6.5 billion, io is developing AI-powered hardware devices, led by former Apple designer Jony Ive, hinting at a disruptive family of AI-aware devices with environmental detection capabilities. 

Horizontal AI:  

• KORE.AI: With $234 million in funding, KORE.AI offers a conversational AI platform with over 250 agent templates, automating customer service and workflows for over 400 global enterprise clients, integrating with platforms like Salesforce and AWS.  
• Sprinklr: A publicly traded company, Sprinklr delivers an AI-powered platform for unified customer experiences across social media, marketing, and service, leveraging generative AI for personalization.  
• Sinch: Another publicly traded player, Sinch provides conversational AI for customer communications, integrated with platforms like Google Cloud.  
• Runway: With $308 million in funding, Runway transforms creative industries with AI-driven video generation, showcasing the versatility of Horizontal AI. 

Vertical AI:  

• Observe.AI: A Redwood City-based startup founded in 2017, Observe.AI has raised $300 million for its GenAI Conversation Intelligence platform, serving brands like SoFi, DoorDash, and Cox Automotive. 
• Abridge: Valued at $2.75 billion, Abridge automates clinical documentation in healthcare, saving doctors significant time.  
• CallRevu: Specializing in automotive, CallRevu offers AI for call tracking and analytics to enhance dealership customer interactions.  
• LEvel AI: With $39.4 million in funding, LEvel AI provides AI-native analytics for call centers in sectors like retail and automotive.  
• Logically: Backed by $24 million from Alexa Fund, Logically uses AI to combat disinformation for governments and enterprises.

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Gary Sloper

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Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Below are the links to Google’s Agent2Agent (A2A) protocol GitHub repository and official documentation, based on the most relevant and up-to-date information available as of June 23, 2025: 

• A2A GitHub Repository:
  https://github.com/google-a2a/A2A 
  This is the official GitHub repository for the A2A protocol, hosting the source code, specification, and contribution guidelines. It includes details on how to engage with the community through discussions, issues, and a partner program for Google Cloud customers. 
• Google A2A Documentation:
  https://google.github.io/A2A/ 
  This is the official Agent2Agent Protocol documentation site, providing a comprehensive overview, the full protocol specification, tutorials, and guides. It covers core concepts, technical definitions, and a Python quickstart for building A2A-compliant agents. 

Additional relevant resources: 

• A2A Samples GitHub Repository:
  https://github.com/google-a2a/a2a-samples 
  This repository contains code samples and demos using the A2A protocol, including Python and JavaScript examples to help developers implement A2A. 
• A2A Python SDK GitHub Repository:
  https://github.com/google-a2a/a2a-python 
  The official Python SDK for the A2A protocol, offering tools to build A2A-compliant agents with support for frameworks like LangChain. 
• A2A Protocol Specification:
  https://google.github.io/A2A/specification/ 
  This page provides the detailed technical specification for A2A, including JSON-RPC 2.0 error codes, Agent Card definitions, and interaction models. 

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

In this dynamic and insightful episode of The Macro AI Podcast, hosts Gary and Scott take listeners on a journey through the world of Reinforcement Learning (RL)—one of the most powerful yet misunderstood branches of artificial intelligence. They explore RL’s psychological roots, its rise in AI history, how it’s shaping business innovation today, and what the future holds for this adaptive learning technology. 

Whether you’re an executive curious about AI’s business potential, a tech strategist exploring emerging models, or simply fascinated by how machines learn like humans do—this episode is a must-listen. 

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Gary Sloper

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Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

In this pivotal episode of The Macro AI Podcast, hosts Gary and Scott deliver a definitive guide for CFOs tasked with measuring the Return on Investment (ROI) of AI projects. With global AI spending projected to reach $300 billion by 2025, according to IDC, CFOs are under intense pressure to justify multimillion-dollar investments in technology, talent, and infrastructure while delivering measurable financial outcomes. Titled "Unlocking AI’s Financial Potential: The CFO’s Blueprint for ROI Mastery in 2025," this episode provides a rigorous, data-driven framework to quantify AI’s value, mitigate risks, and align investments with strategic goals. 

Gary, with his strategic C-suite perspective, and Scott, with his technical expertise, offer a balanced dialogue that resonates with experienced financial leaders. The episode features a five-step ROI playbook, real-world success stories, cutting-edge predictive tools, and forward-looking trends, all grounded in the latest 2025 data from McKinsey, Gartner, and Bain. With CFO-friendly terminology (e.g., NPV, EBITDA, WACC) and a professional tone, it positions The Macro AI Podcast as the go-to resource for CFOs seeking to transform AI into a financial lever. 

Why AI ROI Matters More Than Ever 

The episode opens with a compelling case for why measuring AI ROI is a top priority for CFOs. Gary frames AI as a financial bet with C-suite stakes, citing a 2025 McKinsey report that companies mastering AI ROI achieve profit margins 5-10% higher than peers. This sets the stage for a discussion on the competitive advantage AI offers when properly quantified. Scott emphasizes the accountability CFOs face, greenlighting multimillion-dollar initiatives—cloud platforms, data pipelines, specialized talent—while boards demand hard numbers. Gartner’s 2025 data reveals a stark challenge: 70% of AI projects under-deliver due to vague goals or untracked costs, underscoring the gap between potential and proof. 

Gary reframes AI as a portfolio of returns, blending tangible savings (e.g., cost reductions) with strategic wins (e.g., improved cash flow, competitive differentiation). This dual lens appeals to CFOs balancing short-term financial gains with long-term value creation. The hosts’ interplay—Gary’s executive framing and Scott’s technical grounding—establishes credibility and sets a professional tone for the episode. 

 Navigating AI Risks Like a CFO 

Risk management is a CFO’s domain, and this segment tackles AI’s pitfalls. Scott leads with data risks, noting that a 2025 Forrester study attributes 80% of AI failures to poor data quality. He advocates for a data quality framework—cleansing, standardizing, validating—before investing. Gary references a prior episode, “Dirty Data, Big Losses,” to deepen the podcast’s value. 

Gary then addresses scalability

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Gary Sloper

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Scott Bryan

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Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

In this episode of The Macro AI Podcast, hosts Gary and Scott dive into the transformative world of AI-driven humanoid robotics, exploring how these innovations are reshaping business and daily life. With the global robotics market hitting $16.5 billion in 2024, AI is enabling humanoids to move beyond factories into homes, tackling tasks from chores to eldercare. We unpack advancements like NVIDIA’s Isaac GR00T, which trains robots via virtual simulations, and real-world use cases, such as AgiBot’s humanoids folding T-shirts in Shanghai and Amazon’s warehouse automation. 

Globally, the US, China, and Europe lead the charge. Elon Musk claims Tesla’s Optimus will hit 10,000 units in 2025, scaling to millions by 2030 at $20,000 each, though experts question full autonomy. China’s $137 billion investment, including Shenzhen’s 10 billion yuan fund, drives companies like UBTECH, while Europe’s KUKA and Robotnik focus on sustainable designs. Japan, South Korea, and India also innovate, with the humanoid market projected to reach $13.25 billion by 2029. 

For consumers, humanoids like Tesla’s Optimus or UBTECH’s Walker will handle chores, eldercare, and tutoring by 2030, with costs dropping to $17,000. Challenges include safety, privacy, and cloud connectivity in air-gapped environments like mines, requiring edge AI solutions. Practical advice for leaders includes adopting cobots, leveraging RaaS, and training workforces to mitigate job displacement risks, with 20 million manufacturing jobs potentially automated by 2030. 

Our technical deep-dive explores AI integration—Analytical AI for navigation, Physical AI for training, and hardware like bionics-inspired grippers. We address cloud dependency issues for robots in remote settings and highlight tools like ROS 2 for developers. Looking ahead, humanoids could dominate homes by 2040, with Musk predicting 10 billion robots, though privacy and ethical concerns will drive regulations. 

Join us for actionable insights on leading in the AI era and preparing for a future where humanoids are as common as smartphones. Subscribe and share to stay ahead in the AI revolution! 

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Gary Sloper

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Scott Bryan

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Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Gary and Scott kick off by defining the terms: deterministic AI delivers consistent, rule-based outputs, like a recipe yielding the same result every time, while probabilistic AI embraces uncertainty, using statistical models to adapt to complex, data-rich scenarios. Through real-world examples, they illustrate the impact: UPS leverages deterministic AI for reliable route optimization, while Amazon’s probabilistic recommendation engine drives $1 billion in annual sales. The hosts discuss trade-offs—deterministic systems ensure compliance and trust in industries like finance, while probabilistic models power innovation in marketing and fraud detection, as seen with JPMorgan Chase catching 70% more suspicious transactions. 

In a dedicated technical segment, Gary and Scott unpack the mechanics: deterministic AI uses fixed algorithms like minimax for chess, while probabilistic AI relies on neural networks and softmax functions, as in large language models. They highlight hybrid approaches, like Zeotap’s Customer Data Platform, blending both for precision and scalability. 

For business leaders, the episode offers actionable advice: align AI with use cases, invest in governance to mitigate risks, embrace hybrid models, and upskill teams to build a data-driven culture. Backed by 2025 insights from McKinsey, PwC, and MIT Sloan, this episode equips listeners to make smarter AI decisions. Tune in to learn how to balance predictability and innovation to transform your business in the AI era. 

Keywords: Deterministic AI, Probabilistic AI, business transformation, AI strategy, machine learning, hybrid AI, business leadership, innovation, 2025 AI trends. 

 Sources: 

• Gaine Technology, “Probabilistic and Deterministic Results in AI Systems” (2023) 
• Moveworks, “What is a Probabilistic Model?” 
• Stanford HAI, “AI Index Report 2025” 
• Zeotap, “Probabilistic vs. Deterministic Data” (2021) 
• PwC, “2025 AI Business Predictions” 
• Exploding Topics, “50 NEW Artificial Intelligence Statistics (May 2025)” 
• McKinsey, “The State of AI: How Organizations Are Rewiring to Capture Value” (2025) 
• MIT Sloan, “Leadership and AI Insights for 2025” 
• Medium, “Bridging the Probabilistic and Deterministic” (2025) 
• Capgemini, “The Evolution of Hybrid AI” (2024) 

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Key Takeaways for Listeners 

• Workforce Dynamics: AI drives job polarization, with 40% growth in high-skill roles and 25% contraction in low-skill roles by 2030, necessitating reskilling and hybrid roles like AI-human collaboration specialists. 
• Sector Impacts: Healthcare, education, creative, and green sectors see job creation (e.g., 34 million in agriculture/aquaculture), but automation reduces routine roles, requiring adaptation. 
• Technical Drivers: Agentic and multi-modal AI, supported by 6G and edge computing, fuel innovation, creating roles like AI integration engineers (35% growth by 2030). 
• Societal Shifts: A potential 3.5-day workweek by 2040 and UBI/UHI debates highlight AI’s cultural impact, with mental health and digital divide concerns needing attention. 
• Education and Skills: Interdisciplinary education, AI literacy, and global skills (e.g., multilingual economists) are critical, with universities like MIT leading the way. 
• Leadership: Human-centric AI, reskilling, and sustainability drive success, while navigating regulatory and ethical challenges is essential. 
• Opportunities: AI startups, governance roles, and power infrastructure jobs (e.g., grid engineers) offer growth, supported by collaborative ecosystems. 

Relevance and Impact 

Episode 22 stands out for its comprehensive analysis, blending data-driven projections with real-world examples, like aquaculture’s AI-driven roles and Musk’s UHI controversy. Its focus on actionable advice—reskilling for leaders, interdisciplinary skills for students—makes it relevant for a broad audience. The episode’s engagement hooks, addressing questions like AI’s net job creation and education’s adaptation, spark curiosity and invite listener participation, ensuring it resonates in the ongoing AI discourse. 

#AIFutureOfWork, #UBI, #AIJobs, #Reskilling, #2030Workforce  

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Introduction: Setting the Stage for Conversational AI 

The episode kicks off with the signature sophisticated and forward-looking intro music, setting the tone for an engaging discussion. Hosts Gary and Scott warmly welcome their audience, expressing excitement about the topic of Conversational AI and its transformative potential. They introduce Kolin Koehl, a key figure at Observe.AI, and set the stage for a conversation that ties into previous episodes on Agentic AI and the broader impact of AI on customer experience (CX). With Observe.AI’s mission to enhance customer service through advanced AI, this episode promises to deliver actionable insights and forward-thinking perspectives. 

Guest Introduction: Kolin Koehl and Observe.AI 

Kolin Koehl takes the mic to share his professional journey and how it led him to Observe.AI. As Vice President of Product, Kolin brings a wealth of experience in product development and innovation in the AI space. He provides an overview of Observe.AI, a San Francisco-based company dedicated to transforming customer service through its Conversation Intelligence platform. The platform leverages advanced AI to analyze, optimize, and enhance customer interactions, enabling businesses to deliver exceptional experiences while streamlining operations. Kolin’s introduction sets the foundation for a deeper exploration of how Observe.AI is making waves in the AI-driven customer service landscape. 

The Future of Conversational AI 

Scott shifts the conversation to the future, asking Kolin where he sees Conversational AI heading. This segment explores emerging trends and innovations that are poised to redefine how businesses interact with customers. From advancements in natural language processing (NLP) to more intuitive and context-aware AI systems, Kolin shares his vision for a future where AI not only responds to customer queries but anticipates needs and personalizes interactions at scale. This forward-looking discussion is sure to captivate listeners interested in the next frontier of AI-driven customer experiences. 

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Gary Sloper

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Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Join hosts Gary and Scott on The Macro AI Podcast as they dive into the cutting-edge world of large language models (LLMs) for business leaders aiming to transform their organizations and compete globally. In this episode, we unpack the latest advancements in AI, focusing on parameter counts—a key benchmark for model capacity—and explore how top LLMs like ChatGPT 4.0, Claude 3.7, Grok 3, Llama 3.1 405B, Gemini 2.5 Pro, and Mistral Large 2 are driving innovation.  

Discover what each model excels at: ChatGPT 4.0 (200B parameters) offers versatile multimodal capabilities for customer service and analytics; Claude 3.7 (400B) ensures safety for regulated sectors like healthcare; Grok 3 (2.7T) powers R&D in pharmaceuticals; Llama 3.1 405B (405B) enables customizable, open-source solutions for logistics; Gemini 2.5 Pro (~200–400B) integrates vision and audio for retail; and Mistral Large 2 (123B) delivers cost-effective, GDPR-compliant processing.  

In a technical deep dive, Gary and Scott explain transformer architectures, Mixture-of-Experts designs, and training techniques like RLHF, balancing insights for tech leads and executives. Looking ahead, we explore speculative giants like China’s BaGuaLu (174T parameters, unverified) and ByteDance’s 5T-parameter model with novel “di-reasoning,” hinting at future breakthroughs in strategic planning and scientific discovery. 

With practical advice for leading in the AI era—aligning AI with business goals, budgeting for infrastructure, and fostering AI literacy—this episode equips leaders to harness LLMs for competitive advantage. Tune in for actionable insights and a glimpse into AI’s transformative future! 

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

 
Join hosts Gary and Scott as they explore digital twins—virtual replicas transforming industries worldwide. Learn how these dynamic models, powered by real-time data, AI, and IoT, drive efficiency, innovation, and sustainability in manufacturing, healthcare, urban planning, automotive, and more. From predictive maintenance to smart cities, discover practical applications and leadership strategies to leverage digital twins for competitive advantage. Dive into a technical deep dive on the tech stack—cloud platforms, AI models, and data pipelines—and hear answers to listener questions on ROI, skills, and security. With the market projected to hit $73.5B by 2027, this episode offers business leaders and tech enthusiasts actionable insights to lead in the AI era. Tune in for 35 minutes of cutting-edge AI solutions!  

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Join hosts Gary Sloper and Scott Bryan in this engaging episode of The Macro AI Podcast as they explore how Artificial Intelligence is transforming the cybersecurity landscape for enterprises. Featuring special guest Ed Dunnahoe, VP of Innovation at Guidepoint Security—a trusted cybersecurity provider for over 40% of Fortune 500 companies—this episode dives into the evolving challenges and solutions in enterprise security driven by advancements in AI and machine learning. 

Kicking off the discussion, Ed shares his background and journey to his current role at Guidepoint Security, offering a glimpse into his expertise at the forefront of cybersecurity innovation. The conversation then shifts to key areas impacted by AI in the enterprise threat landscape. 

The hosts and Ed first tackle Governance, Risk, and Compliance (GRC), exploring how AI introduces new complexities and opportunities for ensuring regulatory adherence and managing risks in large organizations. Next, they discuss Application Security (AppSec), examining how AI tools have reshaped the practices of identifying and mitigating vulnerabilities in software applications, fundamentally altering the AppSec landscape. 

The episode also covers Incident Response, where Ed highlights the challenges IT teams face in responding to security incidents in an AI-driven world, drawing from real-world conversations with industry leaders. The discussion then turns to Identity Management, addressing the emerging challenges of securing identities as AI technologies introduce new vulnerabilities and authentication complexities. 

Finally, the episode delves into AI TRiSM tools (Trust, Risk, and Security Management), which are designed to ensure AI systems remain trustworthy, secure, and compliant with ethical and regulatory standards. Ed shares insights into the latest TRiSM tools and their role in helping enterprises navigate the risks associated with AI adoption. 

Wrapping up, Gary and Scott thank Ed for his invaluable insights and invite listeners to share the episode and connect on LinkedIn for more AI-driven discussions. Tune in to this episode for a high-level overview of how AI is reshaping enterprise cybersecurity and what businesses are doing to stay ahead of the evolving threat landscape. 

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Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

The episode begins by defining AI bias—when systems produce skewed outcomes due to flawed data, assumptions, or design. Bias isn’t just a technical glitch; it’s a business risk that can lead to inefficiencies, missed opportunities, and eroded trust. Real-world examples illustrate the stakes: a retailer’s AI overstocked urban stores while neglecting rural ones due to unrepresentative data, and a beverage company’s ad-targeting AI missed older customers by focusing on tech-savvy urbanites. These cases highlight how bias can sabotage operations and alienate markets, while proactive mitigation can unlock competitive advantages. 

Next, the hosts explore how bias infiltrates AI systems. Data bias arises from unrepresentative datasets, like a manufacturing AI overpredicting demand based on peak-season data. Design bias stems from narrow team perspectives, and model bias amplifies small data flaws, as seen in an e-commerce AI pushing high-margin products and alienating budget shoppers. These examples show how bias compounds, emphasizing the need for leaders to scrutinize data sources, team diversity, and testing rigor. 

In the Tech Deep Dive segment, Gary and Scott unpack the mechanics of bias for technical listeners. They explain how unbalanced datasets cause models to overfit to majority cases, using a coffee shop sales AI that overpredicted demand for urban locations as an example. Feature selection can also introduce bias, like a logistics AI misjudging rural delivery times by prioritizing distance over road conditions. Fairness audits and tools like SHAP help uncover these issues, ensuring robust model performance across scenarios. 

The episode wraps with practical mitigation strategies. Leaders should audit data for representativeness, diversify AI teams, test for fairness across use cases, ensure transparency in AI decisions, and engage stakeholders to understand real-world impacts. Examples include a hotel chain validating demand forecasts across property types and a manufacturer consulting plant managers to refine production AI. These steps transform bias from a liability into an opportunity for better, more inclusive systems. 

Gary and Scott close with a call to action: ask your AI team how they’re ensuring fairness. Resources like the World Economic Forum’s AI Governance Framework and G

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

• What’s Vibe Coding? 
  Imagine saying, “Create an app to track sales,” and watching AI write the code in seconds. With tools like Cursor and GitHub Copilot, Vibe Coding turns plain-language ideas into functional software—empowering everyone, from pro developers to total novices. It’s more than a tool; it’s a new creative frontier.  
• Why It’s a Big Deal 
  The impact is already here: 25% of Y Combinator’s Winter 2025 startups built 95% AI-generated codebases. Investors are all in—startups like Codeium and Cursor are hitting unicorn status. But there’s a catch: security risks and bugs, like those in recent SaaS breaches, mean it’s not foolproof yet.  
• How to Make It Work for You 
  Business leaders, take note—Vibe Coding means faster prototypes, cheaper builds, and teams free to focus on big ideas. Here’s how to nail it:  
• Secure It: Craft clear prompts for safer AI code, and use tools like Snyk for human oversight.  
• Debug Smart: Build one feature at a time, and use VS Code breakpoints to squash bugs early.  
• Upskill Fast: Train your team to vet AI code, merging human ingenuity with AI speed. 
• What’s Next? 
  Vibe Coding might soon become “vibe designing,” where intuitive interfaces birth software—unleashing a wave of creators. But as AI does more, security and reliability will be make-or-break. Start small, test boldly, and keep your edge. 

Dive into this episode for a practical, no-fluff look at how Vibe Coding can revolutionize your business—and what it takes to stay ahead.  

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Drawing on a groundbreaking Microsoft study, we reveal how AI delegates work: gathering your meeting objectives, engaging in real-time discussions, and using text-to-speech to mimic your voice. Real-world demos show delegates joining project scrums, sharing updates, and asking questions, with models like GPT-4o hitting 60% accuracy in responses. But challenges like transcription errors—think mistaking “Saanvi” for “Savvy”—and latency highlight areas for growth. 

For business leaders, AI delegates offer massive ROI: cutting meeting time, scaling your presence across time zones, and freeing teams for high-value work. Hear how Amtrak’s AI handles 20 million calls yearly and how a healthcare provider used LLMs to catch critical patient data. We also dive into technical details—transformers, self-attention, and retrieval-augmented generation—for tech enthusiasts, plus practical tips for implementation. 

Leading in the AI era means piloting delegates in low-stakes settings, setting clear data boundaries, and reskilling teams. Ethical considerations, like privacy and bias, are front and center, with a phased approach to ensure trust. Whether you’re a CEO in Singapore or a tech lead in São Paulo, this episode equips you to harness AI delegates for smarter collaboration. 

Tune in for actionable insights, real-world examples, and a glimpse into the future of work. Subscribe and share your thoughts 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Evan Siegel is eGain’s VP of business development and financial services, where he is developing the next generation of AI powered conversational guidance. Prior to eGain, Evan held various customer experience strategy and contact center leadership roles over 16 years at Wells Fargo, where he also established a financial health coaching team that was featured in the bank’s annual report, brand advertising campaign, and ABC’s Good Morning America. Evan is an active writer and speaker, with recent pieces published The Financial Brand, BAI Banking strategies and an appearance on Bain & Company’s Net Promoter Score Podcast. 

eGain is a company that provides AI-powered knowledge management software for customer engagement. eGain Corporation builds and sells AI knowledge SaaS (Software as a Service) products specifically designed for service and support functions. The company is headquartered in Sunnyvale, California. Wikipedia 

Their main product is a platform that unifies knowledge silos within enterprises and transforms content by orchestrating GenAI and experts. This helps businesses provide correct, consistent, and compliant answers to customers, agents, and employees. eGain 

eGain's platform is designed to automate customer engagement with innovative SaaS capabilities powered by AI and knowledge management. Their solutions include virtual assistance, self-service options, and modern agent desktop tools that aim to improve customer experience while reducing agent effort. 

Evan Siegel’s Contact information:  https://www.linkedin.com/in/evan-siegel-ab436845/ 

Link to eGain’s new self-provisioned AI Agent:   https://www.egain.com/ai-agent/ 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Segment 1: The Big Picture 
AI is reshaping telecom with tools like machine learning, chatbots, and infrastructure upgrades. By 2030, AI-driven apps will drive two-thirds of network traffic, requiring a six-fold bandwidth increase. Telecoms use AI to cut downtime by 20% and enhance customer service. Globally, firms like Ooredoo in Qatar optimize wireless networks, while India’s digital boom highlights AI’s role in managing bandwidth. AI’s energy use and workforce shifts—toward strategic roles—require careful planning. 

Segment 2: Telecom Strategies 
Telecoms are investing in 5G, fiber optics, and edge computing to support AI. By 2027, 87% of data centers will need 800 Gbps per wavelength, with ultra-high fiber cables meeting demand. Edge computing powers real-time AI, like Verizon’s traffic analysis or AT&T’s factory automation. Network as a Service (NaaS) offers on-demand connectivity and security. Telecoms are becoming AI enablers, with Verizon using AI to prevent fiber cuts via geospatial analysis. 

Segment 3: Technical Dive 
Trans-oceanic fiber cables, carrying 99% of global data, face pressure from AI’s data needs, driving upgrades to terabit speeds. AI optimizes cable traffic, predicts issues, and boosts resilience against threats like cable cuts. Security is critical, with AI monitoring cyber and physical risks. Sustainability efforts use AI to reduce carbon footprints, aligning with ESG goals. 

Segment 4: Enterprise Impact 
AI-driven bandwidth demands will surge, with core bandwidth up over 50% in five years. By 2030, two-thirds of traffic will be AI-driven, fueled by innovations like AI inferencing. 6G, offering 1 Tbps speeds, will enable futuristic applications. CIOs must integrate network strategies into AI Centers of Excellence to prepare. 

Closing Takeaways 
AI is telecom’s biggest game-changer, accelerating rapidly. IT leaders must baseline network capacity, plan for growth, and address security. Gary and Scott stress network representation in AI strategy to stay ahead. 

Comcast AI Updates  https://www.fierce-network.com/broadband/comca

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

For students entering college in 2025, the hosts advise embracing interdisciplinary skills—pairing technical expertise with human insights—targeting fields like healthcare innovation, where salaries could rise 50% by 2030. Adaptability, global awareness, and practical portfolios are key to thriving in this AI-driven era. Technologically, multi-modal AI and advanced hardware will drive these shifts, enabling real-time optimization and generative design by 2035. 

Leaders are urged to assess AI’s current impact, pilot high-return initiatives, and invest in reskilling, aligning technology with long-term value creation—such as sustainability efforts yielding 15% premiums. This episode blends strategic foresight, technical depth, and practical guidance, equipping listeners to navigate the AI revolution with confidence. 

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Gary and Scott break it down: Prompt studios like PromptLayer provide visual registries, A/B testing, and usage analytics, letting teams—from marketing to IT—craft precise AI interactions without coding. Real-world wins shine through—think Telstra slashing customer follow-ups by 20% or Coles speeding app rollouts 6x faster. Prompt studios amplify these gains, refining prompts to boost ROI in customer support, content creation, and beyond.  

Technically, they’re built with Python and JavaScript, integrating seamlessly via APIs into your AI stack—pulling data from CRMs or ERPs and pushing optimized outputs. Security? Covered. With SOC 2 compliance, on-premise hosting, and real-time risk flagging, tools like PromptLayer keep sensitive data safe, meeting GDPR and HIPAA standards for regulated industries.  

The hosts spotlight market leaders—PromptLayer ($50/month Pro), Helicone (free to 100,000 requests), and Langsmith—plus free starters like Prompthub. Their advice? Start small—automate a report, measure results, then scale with confidence.  

Balancing business strategy and technical depth, Gary and Scott show how prompt studios deliver secure, measurable value—your ticket to leading in the AI era. Tune in for actionable insights to transform your business in 2025!  

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Additionally, for those static AI requirements, intellectual propriety developments, security and tighter governance, enterprises have opted to add or expand their hybrid cloud model with colocation.  

 However, this hybrid approach doesn't represent a complete cancel of cloud GPUaaS, as many organizations maintain a strategic mix, using colocation for baseline workloads while leveraging cloud elasticity for peak demands and specialized tasks.

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog