Booking Overview

Eye on A.I. is a biweekly interview show focused on how real AI practitioners are applying (and sometimes restraining) today’s technology. It’s especially useful for PR teams because guests tend to be credible builders/deployers who can speak to adoption realities, enterprise implementation, and broader societal implications.

Metrics

Episodes: 345

Frequency: Biweekly

Rating: 4.7/5.0

Estimated listeners: 1k-10k

Gender skew: Neutral

Location: USA

YouTube: 33.4k subscribers

Instagram: 1.2k followers

30s Ad: 43 - 53, 60s Ad: 51 - 61

Contact Form

Contact form available - Official Form

Host

Craig S. Smith - Longtime New York Times correspondent who hosts Eye on A.I., using a journalism lens to contextualize incremental AI advances and discuss global implications of the technology. His interview style ...

Booking Intelligence

Booking Requirements

medium
Typical Credentials:  
Senior leaders or recognized experts in AI implementation/deployment (enterprise strategy, infrastructure, security, transformation) and/or advanced technology research/roadmaps (e.g., quantum systems). Guests typically have hands-on experience translating technical progress into organizational outcomes.
Required Achievements:  
Executive or senior leadership role at major tech/consulting/enterprise organizations, Direct responsibility for large-scale technology transitions or deployment programs, Notable technical contributions or roadmap ownership for advanced computing systems

Recent Guest Discussions

Errol Gardner - Enterprise Agentic AI Adoption Barriers; Organizational Readiness Vs Technology Maturity; Human Resistance; Government Role In Workforce Displacement; Value Exchange Sustainability

Oliver Dial - Quantum Utility Vs Advantage Timelines; IBM Roadmap For Fault-tolerant Quantum; Error Correction And Qubit Overhead; Skepticism Around Competing Claims

Kris Lovejoy - Why Agentic-first Startups Don’t Disrupt Enterprises As Fast; Path From Pilot To Production; IT Service Management As Entry Point; Agent Security Risks; Ai’s Impact On IT Administration And Roles

Recent Topics

Artificial Intelligence, Ai Adoption, Enterprise It, Agentic Ai, Machine Learning, Data Platforms, Cybersecurity, Quantum Computing, Workforce, Policy

Episodes

Here's the recent few episodes on
Eye On A.I.
:

The Single Biggest Barrier to AI Adoption Isn't the Technology — It's This | Errol Gardner of EY

May 22, 2026

Errol Gardner has spent 35 years advising the world's largest organizations through major technology transitions, and his assessment of where enterprise agentic AI actually stands is one of the most grounded you'll hear anywhere. His number: less than 1 out of 10 on a maturity scale. Not because the technology isn't ready, but because deploying agentic AI across an organization doesn't tweak how it works, it requires rebuilding how it works. And that is a fundamentally different kind of chall...

Oliver Dial of IBM: Quantum Advantage Is Happening This Year

May 19, 2026

IBM's VP of Quantum Systems, Oliver Dial, has spent his career building quantum computers from the ground up, and he's unusually direct about what they can and can't do. In this conversation with Craig Smith, Oliver Dial walks through where the field actually stands in 2026: quantum utility was achieved in 2023, quantum advantage is the target for this year, and a fully error-corrected machine capable of tackling the hard problems is on IBM's roadmap for 2029. That last milestone, Dial says, ...

Why Agentic-First Startups Won't Disrupt Enterprises as Fast as Everyone Thinks | Kris Lovejoy

May 15, 2026

Kris Lovejoy, Global Strategy Leader at Kyndryl, has spent her career at the intersection of IT infrastructure and security. Right now, she's one of the people enterprises call when they want to move from AI experimentation to real deployment. Her diagnosis is clear: agentic AI is a bullet train sitting on tracks built for 30 miles per hour. The technology is ready. Most organizations aren't, and the gap between a successful pilot and a production system running at scale is far wider than the...

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