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 Jaime 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

What does it take to transform IT from a bottleneck into a business accelerator?

In this episode, Waco Bankston, Chief Information Officer at NiSource, shares how he’s repositioning the IT organization to support growth, enable speed, and shift decades of technical and cultural inertia. Leading a 6.5-year enterprise transformation effort, Waco discusses the discipline required to modernize legacy systems while instilling a new execution culture.

Key insights from the episode include:

• Building a modern tech foundation to support future acquisitions

• Restructuring outsourced/insourced IT mix through platform consolidation

• Shaping team behavior through leadership-by-experience

• Establishing unified governance across AI, cybersecurity, and innovation

• Leading with operational safety and customer-back design

What does it take to reimagine a 10,000-employee enterprise for a digital-first future?

In this episode, Unum CTO Gautam Roy breaks down how he transformed the company’s operating model, culture, and technology foundation by reshaping experiences from the customer backward.

Gautam shares how Unum evolved from applications to journeys to value streams; how AI, data, and automation have become levers for acceleration; and how innovation culture and continuous learning drive enterprise adaptability.

Highlights:

• Unum’s shift to digital-first architecture and “moments that matter”
• How AI, data, and automation remove friction across operations
• Building predictive, proactive technology employee experience
• Creating safe spaces and recognition models for innovation
• Developing a future-focused, cross-functional learning culture

What if your company’s greatest advantage isn’t the product—but the purpose behind it?

Mike Hayes, Managing Director at Insight Partners and former COO of VMware, believes mission clarity is more than culture—it’s a strategic asset. Drawing on 20 years as a Navy SEAL and senior tech executive, Mike shares why knowing “who you want to be” is a superpower for founders and boards.

In this episode, Mike and Peter High discuss:

• How purpose-led companies outperform in high-growth markets
• Mike’s “Three Circles” framework for aligning talent to mission
• What Insight Partners looks for in founder-VC alignment
• How to say no (with clarity) when everything seems urgent
• Why values-based leadership scales in unpredictable markets

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