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

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

AI efficiency is not the destination. At Sunlife, it is the means to something harder to automate: meaningful human connection.

In this episode of Technovation, Peter High speaks with Laura Money, Executive Vice President and Chief Information and Technology Innovation Officer at Sunlife, about building AI around people rather than processes.

Money joined Sunlife in 2020 with a mandate to connect technology strategy directly to business strategy. She describes a four-year AI adoption journey, from an internal GenAI chatbot in early 2023 to agentic systems governed by a shared control plane built with banking and telecom peers. Her core argument: adoption, not technology, is the real bottleneck, and AI’s value in financial services depends on what it frees people to do, not what it replaces.

Key insights include:

Designing AI agents around people and human decision-making

Creating an “empathy dividend” by reducing administrative work

Using AI to accelerate enterprise architecture and advisor workflows

Evolving agile teams and technology operating models

Collaborating on agent governance through an industry consortium

This episode is sponsored by Tines: Freedom to build. Complete security. No compromises.

This episode is also sponsored by Blitzy: autonomous software development at enterprise scale.

 

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