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

How do you scale AI in a regulated enterprise without risking trust, compliance, or credibility?

In this episode of Technovation, Nick Colisto, CIO of Avery Dennison, and Sathish Muthukrishnan, Chief Information, Data & Digital Officer at Ally Financial, share how they are moving from AI pilots to measurable enterprise impact.

From governance-first implementation inside a federally regulated bank to CFO-grade ROI tracking across a global manufacturing enterprise, this conversation focuses on the discipline required to operationalize AI at scale.

Key highlights include:

Why one AI misstep can set a regulated enterprise back years

How to win over risk, audit, and compliance before scaling

Embedding “human-in-the-loop” safeguards from day one

Measuring AI-enabled initiatives using EBIT and IRR

Taking credit for AI embedded in SaaS platforms

If you’re leading AI in a regulated or board-visible environment, this episode offers a pragmatic blueprint for scaling responsibly.

🎧 Listen to learn how CIOs are turning AI experimentation into enterprise value.

Can trust be engineered into digital systems or is it purely cultural?

In this episode of Technovation, Peter High speaks with Jimmy Wales, co-founder of Wikipedia and author of The Seven Rules of Trust, about designing platforms that scale without sacrificing integrity. From neutrality policies to radical transparency and human-in-the-loop AI governance, Wales shares how trust must be built, not assumed.

Key highlights from the episode:

Why trust operates at a human scale, even inside global platforms

How incentives shape behavior, and why ad-driven models distort integrity

Lessons from Airbnb’s early trust crisis

Managing generative AI with human oversight

Neutrality as a strategic discipline in polarized times

Is AI really eliminating jobs, or is it redefining skills?

In this episode of Technovation, Peter High speaks with Ehren Powell, Chief Digital Officer of Marathon Petroleum Corporation, about leading digital transformation at one of America’s largest and most complex industrial enterprises. Powell shares how he is building a skills-first organization—decomposing roles, augmenting capabilities with AI, and reassembling work around differentiated processes.

Key topics include:

Why AI should be treated as a value multiplier—not a strategy

How data contextualization unlocks massive sensor environments

The creation of data domain ownership across the enterprise

Applying edge technology and AI to improve safety and reliability

Why curiosity and reinvention define the future workforce

You can’t scale AI on fragmented data.

In this episode of Technovation, Peter High speaks with Ogi Redzic, Chief Digital Officer of Caterpillar, about the foundational platform transformation that made rapid AI innovation possible across a $65B industrial enterprise.

Ogi shares how retiring legacy systems, consolidating data into the Helios cloud platform, and establishing trusted data pipelines enabled CAT Digital to launch an enterprise AI assistant in just 10 months.

Key topics include:

Building Helios to process millions of data pipelines daily

Turning unplanned downtime into predictive maintenance at scale

Scaling $5B in industrial e-commerce

Partnering with NVIDIA on edge AI and digital twins

Aligning digital teams to measurable business outcomes

In this episode of Technovation, Peter High speaks with Saam Motamedi, General Partner at Greylock Partners, about the evolving role of artificial intelligence within the enterprise technology stack. They discuss how venture capital approaches enterprise AI companies at an early stage, how large enterprises are evaluating changes to their technology stacks, and what implications AI may have for workforce dynamics.

Saam shares perspectives on how AI may influence infrastructure decisions, application development, and software business models over time.

Key insights include:

Shifts in enterprise infrastructure strategy

Usage- and outcome-based software economics

The future of AI agents

What large enterprises should understand about emerging AI startups