In this episode of Business AI Explained, I sit down with Elise Masurel de Laval, co-founder of Catalyst.ai Academy, to break down what makes AI training actually work inside companies. Elise and her team focus on practical AI training for non-technical roles, with a strong emphasis on role-based use cases and learning by doing rather than abstract demos. 

They discuss why AI adoption needs to be tied to real business workflows, why peer-led learning often beats formal training, and how companies should think about shadow AI, governance, and long-term capability building. They also explore why AI agents create excitement early on but often become difficult to maintain unless internal teams can truly own them.

They cover:

•  Why most AI training programs fail 
•  The case for role-specific AI enablement 
•  Why peer practitioners are often the best teachers 
•  How to build relevance through real company use cases 
•  Why AI communities can outperform static courses 
•  How to think about shadow AI without overreacting 
•  Balancing experimentation with governance 
•  The hidden maintenance cost of AI agents 
•  Why practical adoption matters more than tool knowledge 
•  How non-technical teams can build AI confidence quickly 

This episode is for founders, operators, enablement leaders, consultants, and anyone trying to move from AI awareness to real adoption across teams.

About the guest
Elise Masurel de Laval is co-founder of Catalyst.ai Academy. Catalyst describes its approach as practical AI training for non-tech roles, and the company’s about page highlights Elise’s background in marketing, digital, sales, innovation, and executive leadership in education. 

Where to find Elise:
→ LinkedIn: https://www.linkedin.com/in/elise-masurel-de-laval-2579b999/?skipRedirect=true
→ Company: https://catalystacademy.ai/

Work with Vlad:
If you’re implementing AI in your operations and want hands-on help building real workflows:
→ https://www.elementsagents.com/

Subscribe / follow Vlad:
→ LinkedIn: https://www.linkedin.com/in/vladeziegler/
→ AI with Vlad: https://www.youtube.com/@aiwithvlad

He later co-founded Booxkeeping, a bookkeeping business built around fixed pricing, operational efficiency, and standardized financial reporting. That business went on to scale through franchising, becoming a standout model in the bookkeeping industry.

In this episode of Business AI Explained, Vlad sits down with Max to unpack that journey and explore how AI is being used inside real business operations today. They discuss where AI genuinely saves time, why custom AI builds often disappoint, and how off-the-shelf tools like ChatGPT and QuickBooks can create real leverage when applied to the right workflows.

They cover:

•  Lessons from the construction industry and the 2008 recession 
•  The path from bankruptcy to building a new business 
•  Why bookkeeping was the opportunity Max chose to pursue 
•  How Booxkeeping scaled through franchising 
•  Where AI works well in finance and ops 
•  Why custom AI tools can be costly and impractical 
•  How AI helps evaluate franchise territories faster 
•  Using AI to automate notes, emails, and internal workflows 
•  Why efficiency gains matter more than hype 
•  How lower operating costs can become a competitive advantage 

This episode is for founders, operators, franchise builders, finance leaders, and anyone trying to understand what practical AI adoption looks like inside a real business.

Where to find Max Emma:

 → LinkedIn: https://www.linkedin.com/in/maxemma/

→ Company: https://www.linkedin.com/company/booxkeeping/

Work with Vlad:

 If you’re implementing AI in your operations and want hands-on help building real workflows:
 → https://www.elementsagents.com/

Subscribe / follow Vlad:
→ LinkedIn: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Charlotte Lucas is Head of Strategy at ScorePlay, where she’s driving AI adoption across the business to help teams in sales, customer success, marketing, and operations move faster and work smarter. As ScorePlay competes in sports broadcasting with a lean team, Charlotte is building practical AI workflows that save time, improve execution, and help teams scale without losing the human touch. 

In this episode of Business AI Explained, we break down what AI adoption actually looks like when it works: how to get buy-in, where to start, which workflows to prioritize, and how to combine executive sponsorship with team-level ownership. We also cover how AI can support relationship-driven work, why shared learning matters, and how to build trust in AI outputs across the company. 

We cover:

•  Why AI adoption works best when leadership sponsors it, but teams own the use cases 
•  How to start with small, practical workflows that build trust quickly 
•  How ScorePlay is using AI across lead generation, deal desk ops, customer success, and marketing 
•  Why peer learning, internal sessions, and shared channels accelerate adoption 
•  How to match the right AI tools to the right teams 
•  What strong governance looks like: access, review loops, and exception handling 
•  How AI can strengthen relationship-driven work instead of replacing it 
•  Why automating high-impact, low-complexity workflows creates leverage across the business 
•  How unstructured data can become a strategic advantage with the right AI workflows 
•  What it takes to build an AI culture that works both top-down and bottom-up 

This conversation is for founders, operators, GTM leaders, strategy teams, and department heads trying to move from AI experimentation to real adoption across the company.

Episode length: ~45 minutes

👤 ABOUT THE GUEST

Charlotte Lucas
Head of Strategy, ScorePlay

Charlotte Lucas leads strategy at ScorePlay and is driving AI adoption across the company to help teams save time, improve execution, and support sales, customer success, and marketing at scale.

→ LinkedIn: https://www.linkedin.com/in/charlotte-lucas-ba479125/

→ Company: https://www.scoreplay.io/

🔗 WORK WITH VLAD

If you’re implementing AI in your operations and want hands-on help building real workflows:

👉 https://www.elementsagents.com/

🔔 SUBSCRIBE

→ Linkedin: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad

New episodes every Tuesday.

In this episode, I’m joined by Adis Ceman, Regional Enterprise Sales Director at Cequens, a company building AI-powered communication systems across channels like WhatsApp, SMS, and voice.

We go deep into how enterprises are actually using AI today, beyond the hype.

We cover:

•  How AI chatbots are replacing missed opportunities in customer support 
•  Why most companies fail at AI
•  How to structure your data and prompts to get real results 
•  How AI is used in enterprise sales (lead generation, qualification, demos) 
•  The role of human touch in high-value deals (and why it still matters) 
•  How to use AI internally to train teams, build proposals, and move faster 
•  What signals actually matter when selling to enterprise clients 
•  Why speed + personalization are the real competitive advantages in 2026 

One of the most valuable insights:
AI doesn’t replace sales teams, it makes them faster, sharper, and more responsive.

If you're building a product, running sales, or thinking about implementing AI in your company, this episode will give you a clear, practical view of what works.

Episode length: ~24 minutes

👤 ABOUT THE GUEST

Adis Ceman

Regional Sales Director at Cequens - UAE

→ LinkedIn: https://www.linkedin.com/in/adisceman/

→ Company: https://www.cequens.com/

🔗 WORK WITH VLAD

If you’re implementing AI in your operations and want hands-on help building real workflows:

👉 https://www.elementsagents.com/

🔔 SUBSCRIBE

→ Linkedin: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad

New episodes every Tuesday.

But very few are restructuring their operations around it.

In this episode of Business AI Explained, Vladimir de Ziegler sits down with Sean Griffith, founder of Truffle, to discuss how AI is reshaping hiring, software workflows, and internal operations.

Sean explains how his team is able to produce the same level of output with fewer than 10 people compared to what he previously experienced inside a publicly listed company doing over $300M in ARR.

The conversation explores how startups and modern teams are beginning to replace traditional software tools with AI-driven workflows and how leaders can rethink operations to become fully AI-native.

Sean also explains how Truffle is redesigning the hiring process using AI-assisted candidate screening, transcription, and evaluation to help HR teams move from hundreds of applicants to a shortlist much faster.

The conversation covers:

• How startups can control costs when rolling out AI features
• Quick SEO opportunities to appear in LLM search results
• How developers are replacing traditional software with Claude Code
• How to structure operations for AI-native teams
• Which tools and workflows companies should automate first
• How AI is transforming hiring and recruitment processes

If you're building products, leading a startup, or exploring how AI can reshape your internal operations, this episode provides practical insights into the next generation of AI-native companies.

Episode length: ~30 minutes

👤 ABOUT THE GUEST

Sean Griffith

Founder of Truffle

→ LinkedIn: https://www.linkedin.com/in/griffithsean/

→ Company: https://www.hiretruffle.com/

🔗 WORK WITH VLAD

If you’re implementing AI in your operations and want hands-on help building real workflows:

👉 https://www.elementsagents.com/

🔔 SUBSCRIBE

→ Linkedin: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad

New episodes every Tuesday.

Very few actually implement it in production.

In this episode of Business AI Explained, Vladimir de Ziegler sits down with Alexis d'Eudeville, AI Product Manager at Lemlist, to discuss how AI is being used inside real companies.

Alexis shares practical lessons from building AI products, launching startups, and working at Google.

They explore how AI is transforming product management, sales automation, and go-to-market strategy and why the most important factor is still keeping humans in the loop.

The conversation covers:

• How AI is implemented inside modern sales teams
• The role of generative AI in product management
• Why data quality matters for AI adoption
• How companies can move from experimentation to AI in production
• Practical examples of AI improving marketing and customer success

If you're a founder, operator, or builder trying to understand how AI is actually used inside businesses, this episode breaks down the real strategies behind AI implementation.

Key Topics:

AI implementation in business
AI in product management
Sales automation and RevOps
Go-to-market strategy
AI in production systems

Chapters:

00:00 Introduction – Alexis d'Eudeville & AI at Lemlist
01:45 AI in Business: Why Implementation Matters
05:12 How Companies Are Using AI in Production
08:30 Generative AI for Content and Data Analysis
12:45 Human-in-the-Loop AI and Ethical Considerations
18:20 The Future of AI Tools in Business Workflows
22:15 Real AI Examples in Marketing and Customer Success
27:40 AI Adoption Challenges for Startups and SMEs
31:05 How Companies Can Successfully Implement AI
35:50 Key Takeaways: AI Impact on Business Growth
38:15 Final Thoughts on the Future of AI

Episode length: ~40 minutes

👤 ABOUT THE GUEST

Alexis d’Eudeville

AI Product Manager at Lemlist

→ LinkedIn: https://www.linkedin.com/in/alexis-d-eudeville-348bb858/

→ Company: https://www.lemlist.com/

🔗 WORK WITH VLAD

If you’re implementing AI in your operations and want hands-on help building real workflows:

👉 https://www.elementsagents.com/

🔔 SUBSCRIBE

→ Linkedin: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad

New episodes every Tuesday.

In Episode 4, I sit down with Tim Masek, CMO of Storetasker, to break down how AI is actually being used inside real e-commerce businesses.

Not demos. Not theory. Real execution.

We cover:

• Using AI for copywriting and site structure
• Rethinking positioning with AI
• Automating workflows without losing originality
• Why trust still matters more than tools
• How expert networks outperform random freelancers
• Where AI creates leverage and where it doesn’t

Tim shares how AI has become indispensable in strategic work saving thousands in external consulting and accelerating execution.

If you run an e-commerce brand or care about practical AI adoption, this episode gives you a grounded view of what’s actually working.

Episode length: ~49 minutes

👤 ABOUT THE GUEST

Tim Masek

CMO of Storetasker

→ LinkedIn: https://www.linkedin.com/in/timmasek/

→ Company: https://www.storetasker.com/

🔗 WORK WITH VLAD

If you’re implementing AI in your operations and want hands-on help building real workflows:

👉 https://www.elementsagents.com/

🔔 SUBSCRIBE

→ Linkedin: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad

New episodes every Tuesday.

I’m Vlad Ziegler, founder of Elements Agents. 

For the past two years, I’ve helped companies move from “we want to use AI” to actual production systems that drive measurable ROI.

Every conversation starts the same:

“We want to use AI. We just don’t know where to begin.”

The gap isn’t technical knowledge.

It’s operational knowledge:

→ What actually works in production?
→ What breaks after launch?
→ What’s the realistic ROI timeline?
→ How do teams structure AI internally?
→ What mistakes cost companies months?

This podcast is about real implementation stories.

No hype.
No theory.
No futurism.

Just operators sharing what they built, what failed, and what worked.

Launching February 24th with three episodes:

→ Abraham Gomez (Google) on AI in GTM
→ Eliott Wertheimer (VanMoof CEO) on rebuilding after bankruptcy
→ David Arnoux on structuring AI GTM teams

New episodes every Tuesday.

Subscribe now so you don’t miss the launch.

🎥 Watch full episodes on YouTube:
 https://www.youtube.com/@aiwithvlad

🌐 Learn more about Elements Agents:
https://www.elementsagents.com/

🔗 Connect with Vlad on LinkedIn:
https://www.linkedin.com/in/vladeziegler/

David Arnoux is a fractional GTM AI strategist who sits inside companies building AI implementation, not just advising. 

He runs Gen AI Circle (400+ heavy AI adopters) and has worked with scale-ups and enterprise companies transforming their go-to-market teams with AI.

In this episode of Business AI Explained, we break down how AI-native GTM teams actually work, what the team structure looks like, and why the best ones now run a 3:1 ratio of developers to marketers.

We cover:

• How to audit a company's AI readiness (and the red flags that mean they're not ready)
• The maturity levels of AI implementation: from basic prompting to autonomous loops
• Performance marketing as a self-learning loop (campaigns that optimize themselves)
• Why "repo ownership" is now strategic power, the person who controls context controls outcomes
• The 3:1 developer-to-marketer ratio in cutting-edge GTM teams (and why AI is literally the third team member)
• Buy vs. build framework: when to use off-the-shelf tools vs. building custom
• The two internets theory: one for humans (doom scrolling), one for agents (decision-making)
• Why SEO is becoming "programmatic listicles" to game LLMs
• The revenge of the 1950s: why authenticity, friction, and in-person events matter more than ever
• How to work remotely while transforming companies (90% remote, 10% in-person)

This conversation is for CMOs, CROs, GTM leaders, and operators who need to figure out how AI actually fits into their team structure, not just tools, but people.

Episode length: ~45 minutes

👤 ABOUT THE GUEST

David Arnoux 

Fractional GTM AI Strategist | Founder, Gen AI Circle

Works with scale-ups and enterprise companies on AI GTM transformation. 

Builds ventures through Humanoids studio (including ViralBrain.ai)

→ LinkedIn: https://www.linkedin.com/in/davidarnoux 

→ Company: https://www.heyarnoux.com/

→ Community: https://www.thegenaicircle.com/

🔗 WORK WITH VLAD

If you’re implementing AI in your operations and want hands-on help building real workflows:

👉 https://www.elementsagents.com/

🔔 SUBSCRIBE

→ Linkedin: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad

New episodes every Tuesday.

Eliott Wertheimer is the CEO of VanMoof, the iconic European e-bike brand rebuilding after bankruptcy.

In this episode of Business AI Explained, we explore AI in operations for hardware companies and what it takes to rebuild trust, reliability, and economics in a physical product business.

We cover:

• Why VanMoof’s brand survived bankruptcy
• The economics that killed VanMoof 1.0 (low margins, returns, D2C)
• Rebuilding trust through over-delivery, not marketing promises
• Where AI actually fits in hardware companies (support, supply chain, maintenance)
• Why AI should be an operational tool, not a product feature
• Why brand and design matter more as hardware gets easier to build

This episode is for founders, operators, and product leaders working on hardware, consumer brands, or complex operations and trying to apply AI without breaking trust.

Episode length: ~40 minutes

👤 ABOUT THE GUEST

Eliott Wertheimer

CEO of VanMoof

Former McLaren (Lavoie), founder of Fuero Systems

Aerospace engineer turned hardware operator

→ LinkedIn: https://www.linkedin.com/in/eliott-wertheimer-6910a1b6/

→ Company: https://www.vanmoof.com/

🔗 WORK WITH VLAD

If you’re implementing AI in your operations and want hands-on help building real workflows:

👉 https://www.elementsagents.com/

🔔 SUBSCRIBE

→ Linkedin: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad

New episodes every Tuesday.

Abraham Gomez is a Strategic Startups Customer Engineer at Google, where he has advised 400+ founders on AI implementation in go-to-market (GTM) teams. 

In this episode of Business AI Explained, we break down how AI actually gets implemented inside sales, marketing, and GTM operations and why most teams struggle once AI moves beyond experimentation.

We cover:

• How to choose your first AI implementation in GTM
• The 80/20 rule: which AI workflows actually deliver ROI
• Buy vs. build decisions for AI tools (including when not to use Google’s)
• Accuracy vs. precision in AI systems, and why domain expertise matters more than models
• Why AI adoption fails even when the tech works
• How to plan AI projects knowing models change every 6–12 months

This conversation is for founders, COOs, RevOps leaders, and operators who need AI to work inside real GTM teams, not just look good in demos.

Episode length: ~50 minutes

👤 ABOUT THE GUEST

Abraham Gomez

Strategic Startups Customer Engineer at Google

Works with startups implementing AI in GTM, operations, and core workflows.

→ LinkedIn: https://www.linkedin.com/in/goabego/

→ WhoInvitedAbe Podcast: https://www.youtube.com/@WhoInvitedAbe

→ Website: https://goabego.com/

🔗 WORK WITH VLAD

If you’re implementing AI in your operations and want hands-on help building real workflows:

👉 https://www.elementsagents.com/

🔔 SUBSCRIBE

→ Linkedin: https://www.linkedin.com/in/vladeziegler/

→ AI with Vlad: https://www.youtube.com/@aiwithvlad

Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad

New episodes every Tuesday.