Advertise on podcast: Technovation with Peter High (CIO, CTO, CDO, CXO Interviews)

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

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

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

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

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.

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

Proving AI works was never the hard part. The hard part is industrializing it. In this episode of Technovation, Peter High speaks with Dilip Venkatachari, Chief Information and Technology Officer at U.S. Bank, about what it actually takes to move from scattered AI experiments to a common platform with reusable components and measurable outcomes. Drawing from eight years leading technology at one of the country’s largest banks, Venkatachari explains how U.S. Bank treats model risk management and regulatory requirements as design parameters rather than obstacles, why the real technical challenge is plumbing rather than models, and how an internal AI marketplace uses social incentives to drive reuse without mandating it. Key Highlights: Why industrialization, not proof-of-concept, is the defining AI challenge for large enterprises How U.S. Bank treats regulatory requirements as design inputs rather than blockers to AI deployment Why the best AI system creates no value if people don’t change their workflows How an internal AI marketplace and citation-style reuse incentives prevent redundant technology stacks Why AI is emerging as an unexpected solution to the COBOL skills retirement crisis How frontier model companies are shifting from LLM providers to enterprise deployment partners This episode is sponsored by Tines. This episode is presented by Tines: Freedom to build. Complete security. No compromises. Learn more at tines.io

AI is reshaping every stage of pharmaceutical distribution, but only if the organization is built to absorb it. In this episode of Technovation, Peter High speaks with Pawan Verma, Executive Vice President and Chief Data and Information Officer at Cencora, about leading technology and data strategy at one of the world’s largest healthcare companies ($320B+ in revenue, 5 million pharmaceuticals moving through its network daily). Verma joined Cencora in 2024 after serving as Global CIO at MetLife, with earlier leadership at Foot Locker, Target, and Verizon, a cross-industry arc that shapes how he thinks about patient access, workforce transformation, and what AI can and cannot replace in leadership. Key Highlights: Why “centered-out” change management outperforms both top-down mandates and bottoms-up experimentation How Cencora evaluates AI investments against a four-bucket prioritization model, including long-term sustaining value Where AI is shortening the pharmaceutical chain: virtual clinical cohorts, faster drug discovery, and real-time inventory optimization Why pharmaceutical supply chains demand a different standard of precision than conventional logistics What AI cannot replace: the ability to unlearn, reframe on new emotional data, and hold authentic human connection This episode is sponsored by Tines. This episode is presented by Tines: Freedom to build. Complete security. No compromises. Learn more at tines.io

A digital-only bank can’t afford to retrofit security. Ally Financial builds it in from the start. In this episode of Technovation, Peter High speaks with Spencer Cremers, Chief Information Security Officer at Ally Financial, about designing security and resiliency into cloud infrastructure by default — and what that requires organizationally. Cremers spent 20+ years at Ally progressing through divisional CIO and engineering roles before becoming CISO, including a stretch as interim Chief Information and Data Officer. That delivery background shapes how he positions security: not as a gatekeeper handing down requirements late in the cycle, but as a design partner embedded from the start. Key Highlights: Why Ally’s cloud environment uses templatized resiliency patterns so application teams inherit security standards automatically How a three-bucket framework separates AI-in-defenses, AI-enabled external threats, and governing Ally’s own AI use What Cremers learned running a three-day, CEO-involved crisis simulation with concurrent threat vectors Why a CISO with a delivery background can dismantle the adversarial dynamic between security and engineering How Cremers managed the interim CIDO role without putting the organization into a holding pattern This episode is sponsored by Tines. Freedom to build. Complete security. No compromises. Learn more at tines.io

What separates a great founder from a great company? For XYZ Venture Capital Founder and Managing Partner Ross Fubini, execution is only part of the equation. The company also needs to find its “wave.” In this episode of Technoventure, Fubini joins Peter High to unpack the investment philosophy behind XYZ’s bets on founder networks, defense technology, and AI. Drawing on his experience as an engineer, entrepreneur, executive coach, and investor, he explores: Why XYZ built an early thesis around the Palantir talent network What Fubini saw in Anduril before other investors embraced defense technology Why exceptional execution still needs a market “wave” How AI changes software development, defensibility, and venture investing Why forward-deployed engineers are becoming increasingly important Fubini also shares how he personally uses AI to research, challenge investment theses, and sharpen his thinking.

In this episode of Technovation, Nationwide CTO Michael Carrel joins Peter High to discuss how the company is building an AI-ready workforce while modernizing technology across its insurance and financial services businesses. Carrel explains why Nationwide made everyday AI available to associates across the company and paired access with future-ready learning sprints, manager certifications, and role-specific skill development. He also shares how Nationwide is applying generative and agentic AI across underwriting, claims, software engineering, and other domains while maintaining disciplined governance, trusted data, and human judgment. This episode is presented by Tines — Freedom to build. Complete security. No compromises. Learn more at tines.io

What happens when AI moves beyond generating content and starts autonomously optimizing the physical world? In this episode of Technovation, Peter High speaks with Riaz Raihan, Senior Vice President and Chief Digital Officer of Trane Technologies, about how the company is applying AI, connected equipment, and massive volumes of IoT data to make buildings more autonomous and energy efficient. Riaz explains how BrainBox AI acts as an “autopilot” for complex HVAC systems, continuously making small adjustments to optimize energy use without sacrificing comfort. He also discusses Trane Technologies’ three-pillar AI strategy, responsible data use and cybersecurity, and a future in which smart, resilient buildings coordinate energy consumption, storage, and generation autonomously.   This episode is presented by Tines — Freedom to build. Complete security. No compromises. Learn more at tines.io

For Goodyear CIO Raman Mehta, enterprise AI cannot remain stuck in pilot mode. His mandate is to bring a startup mindset to a 128-year-old manufacturer by making speed a strategy and turning AI experimentation into measurable business impact. In this episode of Technovation, Raman joins Peter High to discuss Goodyear’s push toward industrial-scale AI, Lighthouse Projects, enterprise-grade intelligence, and connected manufacturing. He explains why trusted master data is essential for AI systems that reason, how his team is using AI itself to improve data quality, and why reskilling must happen through live work rather than courses alone. Key topics include: Moving AI from pilots to measurable business outcomes Building Lighthouse Projects around cross-functional problems Creating enterprise-grade intelligence with governed data Reskilling technology teams for agentic AI Preparing connected factories for agents, robotics, and physical AI This episode is presented by Tines — Freedom to build. Complete security. No compromises. Learn more at tines.io

Bobcat is transforming machines that were once physical “tool carriers” into software-enabled, connected products. Behind that evolution is a broader effort to modernize the digital foundation of the business. In this episode of Technovation, Peter High speaks with Bobcat Chief Digital Officer Roy Greco about harmonizing global processes, building a trusted data intelligence platform, and scaling practical AI applications. They explore how Bobcat is: Building a digital foundation for faster growth Preparing trusted data for AI and analytics Applying AI to equipment service and logistics Bringing voice-enabled AI into machines Using connected equipment to improve customer uptime This episode is presented by Tines — Freedom to build. Complete security. No compromises. Learn more at tines.io This episode is also presented by Retool — Build internal software better, with AI. Learn more at retool.com

Before the market is obvious, what gives an investor the conviction to act? In this episode of Technoventure, Peter High speaks with Shardul Shah, Partner at Index Ventures, about why exceptional founders can matter more than early market signals. Shardul shares lessons from investing in companies including Datadog and Wiz and explains how he evaluates conviction, high agency, and founders who can “hold contradiction with ease.” They also explore: How AI is reshaping enterprise software and infrastructure Why companies born before 2025 need to reinvent themselves The rise of machine-to-machine cybersecurity Why enterprise AI adoption begins with culture and risk How Shardul uses relationships and AI agents to accelerate learning