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

Latest Episodes:

No Innovation Without a Market: Ahmad Bahai on TI’s R&D Model Nov 05, 2026

Show notes

Semiconductor development cycles run a decade or longer, but markets shift faster than any company can predict. Ahmad Bahai, Senior Vice President and Chief Technology Officer at Texas Instruments, explains how TI navigates that gap by betting on directional technology vectors rather than specific end markets. TI’s high-voltage program, started over a decade ago with smart grid in mind, eventually served electric vehicles and then became core infrastructure for AI data centers. In this episode of Technovation, Peter High speaks with Ahmad Bahai, SVP and CTO at Texas Instruments, about long-horizon R&D, the power delivery bottleneck in AI infrastructure, and why transistor scaling is now one of several co-equal innovation vectors. Bahai also reflects on the Bell Labs model, TI’s $60B-plus US fab expansion, and the case for a “virtual Bell Labs” that bridges academic curiosity and commercial urgency.

Key Highlights:

Why TI embeds Kilby Labs researchers inside business units from the start, so innovations never expire on a shelf
How TI’s high-voltage program moved from smart grid to EV to AI data centers without changing the underlying technology platform
Why stepping voltage from 400V at the rack down to sub-1V at the processor is the overlooked bottleneck in AI infrastructure
Why transistor scaling is now one innovation vector among several, with materials and packaging becoming co-equal drivers
Why building fabs during a market trough is the only way to have capacity ready when the next peak arrives

Data from Thousands of Tests: How Simpson Strong-Tie Is Building an AI Moat Nov 02, 2026

Show notes

A 70-year-old manufacturer’s proprietary test data may be a more defensible AI moat than software capability alone. In this episode of Technovation, Peter High speaks with Udit Mehta, Chief Technology Officer at Simpson Strong-Tie, about building an AI strategy on a foundation of structural engineering expertise. Mehta joined in 2024 from Carrier and Siemens, and has spent two years modernizing the company’s infrastructure, upskilling 1,200-plus employees on AI, and launching an integrated cloud-native software portfolio for component manufacturers. He describes how Simpson’s combination of hardware, software, services, and proprietary test data creates a position pure-play software entrants cannot match, and why AI must augment engineering judgment rather than replace it.

Key Highlights:

Why Simpson’s hardware-plus-software bundling creates an AI moat pure-play entrants structurally cannot replicate
How AI tools assist structural engineers without removing human judgment from high-stakes decisions
Why workflow embeddedness, not technical feasibility, is the real adoption gate in construction
How a three-pillar AI strategy spans individual productivity, enterprise value, and customer growth in parallel
Why business owners, not AI teams, must remain accountable for every AI-enabled workflow outcome

This podcast episode is sponsored by Blitzy. Autonomous software development at enterprise scale.

Not Just More Pilots: Shweta Gummidipudi on Scaling AI at Twilio Oct 29, 2026

Show notes

Most companies can prove an AI use case works. Scaling it is where they stall. Shweta Gummidipudi, CIO at Twilio, has spent her first year building the infrastructure layer that makes scale possible: a single model gateway for routing and cost control, a shared library of agents and connectors, and inference budgets that keep business-unit builds inside enterprise guardrails. She also addresses two problems most governance conversations skip: agentic identity, which the industry has not solved, and agent sprawl, which she maps directly to the shadow IT problem CIOs spent the last decade managing. Alongside those structural challenges, she describes Twilio's Customer Zero program, where IT runs Twilio's own products in live workflows and converts that experience into reference architectures that enterprise customers adopt faster than vendor documentation alone.

Key Highlights:

Why a single model gateway is the prerequisite for moving from pilots to scale
How Twilio structured a three-tier access model to prevent agent sprawl without blocking experimentation
Why agent identity is categorically different from human identity and what that means for security
How the Customer Zero program turns internal practitioner experience into customer reference architectures
Why career-leveling guides need to be rebuilt from scratch rather than retitled for the AI era

Fix the Process Before the AI: Prakash Kota of UKG Oct 22, 2026

Show notes

AI layered onto a broken process doesn’t fix the process; it just runs it faster. Prakash Kota spent his first 18 months at UKG consolidating two legacy companies into unified CRM, ERP, and data systems before any AI conversation began. Now, as Chief Transformation Officer, he is shifting the question from “what tools can we deploy?” to “what outcome are we trying to reach?” That discipline extends to the customer funnel, where AI-assembled signals travel with a prospect through every handoff, and to sales reps, where an autonomous assistant pushes pre-meeting briefs before a rep has to ask, reclaiming the 40–50% of call-prep time currently spent on research.

Key Highlights:

Why redesigning the process must come before choosing the technology
How UKG unified two legacy companies’ systems as the foundation for AI-era work
The shift from AI as a tool you pull from to an autonomous teammate that pushes the right information to you
How AI-enriched signals travel with a prospect through every funnel handoff, making customers feel individually known
Why UKG’s CEO holds a weekly cockpit review of the top 10 transformation programs, measured at the business-outcome level

This episode is sponsored by Tines. This episode is presented by Tines: Freedom to build. Complete security. No compromises. Learn more at tines.io

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AI Fluency Over AI Tools: Kristie Grinnell on Transforming TD SYNNEX Oct 19, 2026

Show notes

The binding constraint on AI adoption is not access to tools. It is the organizational fear and mindset shift required to reimagine work entirely.

In this episode of Technovation, Peter High speaks with Kristie Grinnell, EVP and Chief Information Officer at TD SYNNEX, about building company-wide AI fluency across a global workforce of nearly 30,000 employees.

Grinnell joined TD SYNNEX roughly two years ago and holds executive sponsorship of its AI fluency strategy alongside full IT operational scope. She describes how TD SYNNEX structured fluency at three tiers, required every ELT member to produce an AI plan, and built Fluidworks.ai as an internal factory to scale governed AI across the organization.

Key Highlights:

Why AI adoption fails as a change management problem before it fails as a technology problem
How a tiered fluency certification gives every employee a concrete path to AI readiness
Why every AI agent at TD SYNNEX must carry a registered identity and a named human owner
How agentic SOC triage turned tier-1 analysts into threat hunters
Why TD SYNNEX policy holds employees accountable for the AI outputs they use

This episode is sponsored by Tines. This episode is presented by Tines: Freedom to build. Complete security. No compromises. Learn more at tines.io

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No Pilot Graveyards: How Novant Health’s CAIO Turns AI Into Patient Outcomes Oct 15, 2026

Show notes

Healthcare has accumulated friction that patients have come to accept as normal. Novant Health’s Chief AI Officer is systematically dismantling it.

In this episode of Technovation, Peter High speaks with Vijay Sankararaman, Chief AI Officer at Novant Health, about deploying AI across patient experience, clinical operations, and proactive population outreach at a system with 22-plus hospitals and 8 million annual patient encounters.

Sankararaman came to healthcare from retail product and engineering leadership at Walmart and Lowe’s, and he brought a problem-first discipline with him: every AI initiative must justify the problem it solves before the technology is considered. His team has deployed a 24/7 surgical companion, a lung-cancer screening outreach program that contacted more than half of 20,000 at-risk patients in a fraction of the time human call programs managed, and a mammography scheduling agent that drove call abandonment to near zero.

Key Highlights:

Why the hardest part of a CAIO’s job is saying no to AI proposals
How a conversational AI agent reached thousands of at-risk lung-cancer patients human callers could not
What 40% after-hours engagement reveals about suppressed patient demand
Why the CEO’s frame on AI (technology feature vs. business reimagination) determines whether a CAIO role makes sense
How Novant’s build/buy/co-develop architecture avoids vendor lock-in without slowing deployment

This episode is sponsored by Tines. This episode is presented by Tines: Freedom to build. Complete security. No compromises. Learn more at tines.io

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95% AI Adoption: How Zoetis Built a Model-Agnostic Platform That Stuck Oct 12, 2026

Show notes

Most generative AI programs stall at the pilot stage. Zoetis reached 95% computer-based colleague adoption.

In this episode of Technovation, Peter High speaks with Keith Sarbaugh, Chief Digital and Technology Officer at Zoetis, about how the world’s leading animal health company built an AI platform that colleagues actually use, and how Sarbaugh measures whether any of it is working.

Sarbaugh spent over two decades in human pharmaceuticals at companies including Eli Lilly and Biogen before joining Zoetis in 2023. He now oversees IT, AI, data, cybersecurity, and global customer experience, and describes the role as more hybrid business-technology leader than traditional CIO.

Key Highlights:

Why Zoetis built a model-agnostic platform (Zen AI) with 10–11 LLMs rather than standardizing on one
How a 350-person global Change Champion Network drove adoption faster than any top-down mandate
What Sarbaugh’s Business Value Realization Framework requires teams to define before a project begins
Where agentic AI earns its place: rules-based, high-value decisions like supply chain demand forecasting
Why aggregating all customer touchpoints at 10x prior volume revealed service failures that NPS never could

This episode is sponsored by Tines. This episode is presented by Tines: Freedom to build. Complete security. No compromises. Learn more at tines.io

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Lior Susan on Why Now Is the Time to Build Industrial Giants Oct 09, 2026

Show notes

The next generation of technology giants may not be built in software. They may be built in factories.

In this episode of Technoventure, Peter High speaks with Lior Susan, Founder and Managing Partner of Eclipse, about why AI, robotics, and industrial innovation are transforming the economics of American manufacturing.

Lior explains Eclipse’s five-forces framework for building industrial companies and why physical industries represent a significant opportunity for venture capital.

They explore:

How AI and robotics enable competitive domestic manufacturing
Why industrial startups need operating expertise beyond capital
The infrastructure opportunities emerging from AI’s energy and compute demands
Why humanoid robotics may be getting ahead of practical applications
How policy and national security are shaping industrial investment

Listen to discover why Lior believes this is an extraordinary moment to build companies in the physical world.

How Mastercard Stopped $13B in Fraud With Real-Time AI Oct 08, 2026

Show notes

Mastercard processes billions of transactions, and fraud doesn’t wait for rules-based systems to catch up. In this episode of Technovation, Peter High speaks with Nirav Mehta, Chief Technology Officer at Mastercard Services, about how the company uses AI to score transactions in the milliseconds between a card tap and approval, and what it takes to build that kind of infrastructure at scale.

Nirav leads engineering, analytics, and decisioning for Mastercard’s $14B Services business, which spans fraud prevention, threat intelligence, data commercialization, and emerging agentic commerce. He explains how Decision Intelligence Pro prevented roughly $13B in fraud in 2026 alone before the holiday season, why the company treats data unification as a use-case-first problem rather than an architecture mandate, and how agentic commerce today resembles the early web, competing standards, good intent, unresolved identity questions. He also makes the case that senior technology leaders need to stay hands-on, not just well-read.

Key Highlights:

Decision Intelligence Pro stopped approximately $13 billion in fraud in 2026 year-to-date by applying AI models in the milliseconds between card tap and transaction approval
Mastercard’s Data Commercialization Platform reduced location-data staleness from 8-10 weeks to hours and cut processing time from multiple weeks to under 10 minutes
Agentic commerce is still in early-standards chaos, Mehta compares it to the web in its first years, and Mastercard’s bet is that its payments trust transfers directly to machine-to-machine contexts
GenAI is compressing engineering team size: a two-person pod plus ten AI agents is already viable for smaller programs, and the scarce skill is now systems thinking, not coding ability
Mehta makes the case for hands-on experimentation over passive learning, logging 1-1.5 hours of personal vibe coding daily since December 2025

This episode is sponsored by Tines. Freedom to build. Complete security. No compromises. Learn more at tines.io

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