Technovation with Peter High (CIO, CTO, CDO, CXO Interviews)

1036: What does it mean to manage a digital workforce? In this episode of Technovation, we feature a panel from our most recent Metis Strategy Summit where three top executives explore how AI is reshaping work, both automating tasks, and changing the nature of management itself. Peter High speaks with: Jennifer Charters, Chief Information Officer at Lincoln Financial Prasanna Gopalakrishnan, Chief Product & AI Officer at ADP Daniel Marcu, Global Head of AI Engineering at Goldman Sachs Together, they discuss: Why AI agents require new thinking about team structure and oversight How CIOs and CHROs must partner to build enterprise AI fluency The risks of shadow AI and the need for secure platforms How habit loops and performance incentives impact AI adoption What it takes to balance innovation speed with organizational readiness

Our broadcast today features a panel from our most recent Metis Strategy Summit on the topic of Delivering the Product Operating Model (and Mindset) at Scale. In this panel episode, we explore the limits and lessons of scaling the product operating model. Sal Companieh (Cushman & Wakefield), Jim Fowler (Nationwide), and Diane Schwarz (Smurfit WestRock) reflect on where product thinking thrives and where it breaks down. Here are 5 takeaways from their candid discussion: Why “readiness” must come before model The risks of forcing product teams into fragmented structures When to co-create with business leaders—and when to slow down How agile funding models can clash with CapEx culture What to do when the organization “doesn’t want the service”

What if the most defensible companies of the AI era aren’t the ones building the infrastructure—but the ones using it to rethink workflows? In this Technoventure episode, Peter High speaks with Jamie Montgomery, Founder and Managing Partner of March Capital, about why the firm is investing heavily in the AI application layer—not chips, not clouds, but the companies delivering real task-based outcomes. Key topics explored: Why workflow-based moats beat data moats in the new venture cycle How application-layer companies are scaling faster with leaner GTM The ripple effects of AI CapEx on the U.S. economy and tax base March Capital’s bets on open-source LLMs and scientific discovery Why Montgomery believes AI “bailed out” the U.S. and VC industry alike

What’s stopping AI from scaling across the enterprise? For Madhu Ramamurthy, CIO of Zurich North America, it’s not the technology. It’s the culture. In this episode, Madhu shares how he’s navigating the paradox of AI: a tool with unprecedented potential, surrounded by institutional resistance, unclear regulations, and cultural misalignment. He outlines Zurich’s approach to responsible AI deployment, organizational change, and ethical tech use. Key highlights include: How “organizational antibodies” can kill innovation before it scales The case for explainability and governance in AI development Why domain expertise is more valuable than tech fluency Building AI-native teams outside of legacy systems Madhu’s warning on digital flattery and sycophantic AI

What does it really take to scale AI across a global enterprise? In this episode, Jaime Montemayor, Chief Digital and Technology Officer at General Mills, shares the AI playbook behind the company’s digital transformation from foundational investments in cloud and data governance to business-led innovation across supply chain, e-commerce, and marketing. With 96% of General Mills’ supply chain data now clean and governed, Jaime’s team is shifting from predictive analytics to agentic architectures that enable scalable, AI-powered automation. Key insights include: Why cloud migration came before ERP modernization How trust and business integration drive AI adoption Building a connected data foundation to serve every segment Agentic AI use cases in supply chain and marketing Org design strategies to “lift and shift” innovation at scale

In this engaging discussion, Waco Bankston, CIO at NiSource, shares insights from his extensive experience leading a major technology transformation. He highlights the shift from viewing IT as a bottleneck to embracing it as a business accelerator. Waco outlines a comprehensive six-year roadmap to modernize legacy systems and instill a new culture of urgency and integrity. He delves into governance strategies for AI and cybersecurity and the importance of adapting lessons from other industries to enhance decision-making and integration post-acquisition.

Gautam Roy, the Chief Technology Officer of Unum, leads the charge in transforming the company’s digital landscape. He discusses shifting from traditional applications to value-based journeys, emphasizing a digital-first approach. Gautam highlights the role of AI and automation in enhancing efficiency and customer experiences. He shares insights on fostering a culture of innovation through hackathons and cross-functional teams, along with the importance of continuous learning and adapting talent strategies for the future.

Mike Hayes, a former Navy SEAL and Managing Director at Insight Partners, discusses the strategic advantage of having a clear mission in business. He emphasizes the importance of identity over roles, advising organizations to align their missions with leadership for elite performance. Mike shares lessons from SEAL training on constructive feedback and making effective decisions. He also reflects on the balance between ambition and purpose, underscoring humility as a key leadership quality. His insights are drawn from high-stakes experiences, making for a compelling conversation.

What does it take to evolve IT into a forward-looking innovation engine? Mike Blandina, CIO of Snowflake, shares how he’s reimagined IT as “Enterprise Technology” as a way to describe what ‘IT’ really does: lead a solutions-first mindset at Snowflake designed for the AI era. In this conversation, Mike reflects on his first eight months leading tech at one of the world’s most AI-forward data cloud companies. Key highlights include: The philosophy behind the Enterprise Technology rebrand Building Raven and RevOps—AI agents replacing 250+ dashboards The Customer Zero model for product influence Governance and localization strategies for responsible AI Redefining staff models to include digital agents

What if your hiring strategy were fueled by the largest contingent workforce dataset in the world? Magnit CEO Chandra Dhandapani joins Technovation to explore how data is reshaping how companies think about talent—from role design to sourcing strategy to real-time labor cost insights. Chandra also shares lessons from her journey from CIO to CEO and offers perspective on why automation—not AI—is the skill trend to watch. Key topics covered include: 12% YoY surge in automation roles vs. 2% in AI Data-driven frameworks for balancing contingent and permanent talent How Magnit uses GenAI internally via its “Maggi” platform Strategic applications of workforce analytics Leadership shifts from digital to enterprise-wide responsibility