AI Insiders

Skoda Auto runs AI transformation with two leaders, one from the business and one from IT. Dr. Ina Offergeld, Head of AI and Transformation, brings the platform and architecture lens. Dominika Matarazzo, Head of Consumer and Digital AI Transformation, brings the customer and strategy lens.

Host Vincent Pirenne talks with them about how Skoda picks AI investments worth making. They explain why saying no to ideas matters. They also cover how a large, traditional company builds AI into the way it already works, without adding new committees.

New job titles are showing up faster than most org charts can keep up with.

In this episode, Hanna Andréason breaks down the new roles she's seen emerge as large companies move from AI pilots to AI at scale, and why the org chart itself is becoming one of the most contested parts of AI transformation.

The conversation explores how roles like AI product managers and AI trainers differ from their traditional counterparts, why data ownership is shifting from a purely technical responsibility to a shared business one, and what it actually takes to build the muscle for AI-native ways of working inside an established organization.

This is a grounded, practical look at how new AI roles take shape inside big companies, and why getting the people and structure right matters as much as the technology itself.

If you are leading AI transformation in your own organization, this one is for you.

Amir Ouki, partner at BOI, breaks down what's actually happening inside large organizations. Why the jobs most at risk aren't the ones companies expect. Why pilots stall before they scale. And how the conversation has shifted from cost reduction to building entirely new revenue streams.

Labor is splitting into more valuable and less valuable segments. Understanding which side your role sits on is no longer optional.

If you're a manager, executive, or knowledge worker wondering whether your role is safe or how to stay relevant, this episode will give you a compelling blueprint for navigating AI-driven change.

Amir leads BOI's Americas practice and has worked with MasterCard, Johnson & Johnson, and Coca-Cola.

Becoming AI-first isn’t about deploying more tools, but about changing how work gets done.

In this episode, Laura Stevens breaks down why AI transformation is fundamentally a leadership and operating model challenge, not a technology one. The conversation explores how organizations must redesign workflows, confront technical debt, rethink roles and responsibilities, and build trust in AI systems to unlock real value. Drawing on patterns across industries, Laura explains why smaller organizations often move faster, how AI exposes hidden inefficiencies, and what leaders must do to shift from managing tasks to overseeing outcomes. 

This is a grounded, practical look at what AI-first actually means in practice - and why most organizations underestimate the change required.

Dive deeper: Download your AI-first playbook here

Takeaways

• AI transformation requires a redesign of organizational workflows.
• Technical debt can become a strategic bottleneck for AI adoption.
• AI should be integrated into business processes, not treated as a separate technology.
• Trust in AI is hindered by psychological barriers and fear of loss of control.
• Roles in organizations must shift from task execution to oversight and strategy.
• Smaller organizations often adapt to AI faster due to less legacy complexity.
• AI adoption should focus on outcomes rather than isolated use cases.
• Leadership must understand that AI changes how value is created in organizations.
• AI can expose existing complexities and inefficiencies in processes.
• The success of AI transformation depends on the willingness to rethink how work is done.

In this conversation, Vincent Pirenne interviews Alberto Prado, who shares insights from his extensive experience in leading AI and digital transformations at major companies like Unilever, Philips, and Nokia. They discuss the evolving landscape of technology disruption, the unique challenges of implementing AI in R&D, and the importance of building a robust data foundation. Alberto emphasizes the need for organizations to embrace change, foster partnerships, and focus on long-term growth strategies rather than short-term efficiencies. He also highlights the significance of leadership in navigating the complexities of AI transformation and the future of organizations in an AI-driven world.

Takeaways

• Technology breakthroughs drive the need for transformation.
• The pace of disruption is increasing in today's landscape.
• R&D requires high reliability and sophistication in AI models.
• Data quality and richness are crucial for AI insights.
• AI transformation in R&D needs a different approach than other functions.
• Building a data lab can accelerate R&D innovation.
• Organizational culture must embrace data as a key asset.
• Partnerships are essential for successful AI transformation.
• Measuring ROI should focus on growth, not just efficiency.
• The future of organizations will require a balance of human expertise and automation.

In this episode of AI Insiders, we dive into how GenAI is reshaping commercial strategy across enterprise with Alyssa Fenoglio.

Alyssa shares how she’s putting GenAI to work to unlock business value at enterprise scale:

• How to build GenAI momentum across global commercial teams
• Lessons from embedding AI in sales, marketing, and agency workflows
• What it really takes to scale GenAI in a compliance-heavy industry
• Why AI literacy, soft skills, and governance matter just as much as technology

What does it take to go from pilot use case to impact at scale?

Tune in to find out.

In this episode of AI Insiders, we explore what enterprise AI actually looks like in practice inside Bayer Crop Science.

Dan Kurdys and Sachi Desai join us to share how one of the world’s largest companies is putting GenAI to work:

From internal pilots to a full-fledged internal startup, they walk us through how Bayer is building AI-powered tools that scale expert knowledge, support frontline teams, and move fast:

• How Bayer built momentum for GenAI from the inside
• Lessons learned from launching an internal GenAI startup, E.L.Y.
• What it takes to drive real adoption in complex organizations

How does enterprise AI go from an idea to impact? Listen to this episode!

In this episode of AI Insiders, we sit down with Béatrice Dautzenberg, Global Director of Beauty Tech Services at L’Oréal, to explore how AI, computer vision, and GenAI are revolutionizing personalized beauty. From skin diagnostics to virtual try-ons, Beatrice shares how tech is elevating the consumer experience—and what it takes to integrate AI at scale in a global powerhouse.

Ready to decode the future of beauty tech? Let’s dive in.

In this episode, we're joined by Norberto Chaclin, SVP of R&D at Mondelēz International (the company behind Oreo, Cadbury, and other fan favorites), to explore how AI is revolutionizing the food and bev industry. 

From predicting consumer trends to reformulating recipes, AI enables faster innovation, better decisions, and personalized products. We discuss insights on balancing risk, fostering organizational agility, and breaking with traditional "cookie cutter" approaches. With AI transforming everything from regulatory compliance to global product strategy, this discussion underpins how leaders need to embrace digital tools and rethink decision-making to drive efficiency, creativity, and better outcomes in an always rapidly changing industry.

Solving at scale: prioritizing the problem, not the solution. Tune into this episode to get insights into how JP Morgan Chase scale successful corporate-startup relationships.
 
In this episode, we’re joined by Lisa Besserman, a top 100 tech influencer and the force driving innovation at JP Morgan Chase. 

Lisa shares her approach to solving at scale, dives into harnessing AI and emerging tech to boost both employee and customer experiences, and how to find impactful solutions and forging dynamic partnerships between startups and corporate giants.

We’ll also explore how AI fits into her work and personal life—and how mountaineering (yes, she’s climbed Kilimanjaro!) has shaped her thinking around risk and resilience. Her advice? Find your believers, stay flexible in execution, and don’t fear failure.

Tune in for insights on building a career and mindset that fuel real-world impact.