In this episode, Frank Schüler, Managing Director of Global Business Services at DHL Global Forwarding, shares how he leads one of the world's largest GBS organizations, supporting global operations with 6,000 people, 160 automation bots, and AI-driven innovation. He explores the rise of agentic AI, managing a hybrid workforce of people and digital workers, and the leadership principles behind building a high-performing, people-first organization.

Many GBS leaders still lead with "we save money," but is that still the right pitch? In this episode, Steve Rudderham, SVP GBS at Ecolab, joins us to talk about the shift from cost center to value engine. Drawing on his experience leading GBS organizations at Carrier, AkzoNobel, Kellogg's, and now Ecolab, Steve explains why "we save money" is the flip-phone version of the conversation, where agentic AI is already moving the needle on revenue and customer outcomes, and his honest take on the "our data isn't ready" excuse.

In this episode, we cover:

• What separates a world-class GBS from a transactional service center — and how that shift shows up internally at Ecolab
• Why automation doesn't have to mean headcount reduction, and what the role of people looks like in an Agentic GBS
• Accountability in an agentic world: who owns the outcome when AI agents act autonomously, and when "good enough" data is good enough to start

Data quality isn't the most glamorous topic in enterprise AI — but it might be the most important one. In this episode, Sally Fletcher, Head of Thought Leadership & Community, Hypatos, sits down with Vandana Khanna, a global finance and technology leader at MetLife who is leading the company's Finance Modernization and Digital Transformation initiative. With experience spanning insurance, consumer goods, telecom, and retail, Vandana brings a rare blend of strategic vision and operational reality to one of AI's most underestimated challenges.

We dig into what "AI-ready" actually means in practice, why bad data is so costly and so hard to catch, and how leaders can navigate the politics of data ownership inside large organizations. From the minimum data-quality bar for a successful AI implementation to the structural changes that would have the greatest downstream impact, this is a candid conversation about the unglamorous groundwork that determines whether AI succeeds or fails.

If you're under pressure to move fast with AI, this episode is essential listening.

If you want to learn more about how to implement Agentic AI, download our whitepaper here.