Episode Overview
In this episode of AI Leadership Lab, host Ryan Heath sits down with Ryan Steelberg, CEO of Veritone, to explore the practical realities of deploying AI in enterprises. With a deep history in ad tech and in structuring previously unstructured audio and video data, Steelberg offers a grounded perspective on AI adoption that cuts through the hype. From discussing the critical importance of data infrastructure to sharing insights on ROI measurement and the mistakes companies make when integrating AI, this conversation provides essential guidance for leaders who want AI solutions that actually work—not just shiny marketing promises.
Key Takeaways
Focus Data Infrastructure, Forget AI Magic
Most organizations struggle with basic data management and cloud migration before they can meaningfully apply AI. Companies must understand and embrace their data journey first—there's no skipping this step, regardless of how advanced the AI tools promise to be.
AI is a Tool, Not a Solution
When evaluating AI products, redact every mention of "AI" from the marketing literature and ask: why are you buying this software? The AI is just a component, like an engine in a car. Focus on whether the solution satisfies your well-defined needs, not whether it's labeled as "next generation" or "future proof."
Track Everything to Improve Everything
Smart AI deployment requires comprehensive tracking of how users interact with applications. This data reveals whether bottlenecks stem from the AI model itself or the application layer, enabling companies to improve both the technology and the workflow continuously.
Customized ROI Metrics Matter
ROI metrics must be tailored to specific use cases and business models. What drives value for a sports organization (speed to market for content) differs radically from what matters to a media company (ad revenue optimization), even when using the same technology stack.
Combine Experience with Fresh Perspective
Organizations need both veterans who understand traditional processes and newcomers who organically embrace AI tools, and communicate naturally with data.
Regulated Environments Require Specific AI Approaches
In secure or air-gapped environments like Department of Defense networks, you cannot invoke third-party AI models. Everything must be containerized and deployable within the secure environment.
Key Quotes
"Imagine taking a piece of marketing literature and redacting any word that mentions AI. Why are you buying this software solution?"
"Don't ever throw away your ore. You don't know where the gold or diamonds are gonna be materialized or processed through."
Chapter Timestamps
[00:00] Veritone's AI journey from ad tech origins
[02:04] Bringing structure to unstructured data
[04:02] Deploying AI in regulated industries
[05:17] Product roadmap evolution and customer feedback
[08:00] Common mistakes in AI integration
[10:06] Skills and upskilling challenges
[12:25] Measuring ROI in AI deployments
[16:00] Surprising customer use cases
[21:00] Smart questions for evaluating AI products
About the Guest
Ryan Steelberg is the CEO of Veritone. Steelberg's journey into AI began with a fundamental problem: how to target ads against audio and video content in an increasingly organic media ecosystem. This challenge led Veritone to develop sophisticated capabilities in transcription, object detection, and machine vision to bring structure to unstructured media content.
Under Steelberg's leadership, Veritone's major clients include NBCUniversal, iHeartMedia, the US Tennis Association, CNBC, and the Department of Defense.
Connect with Ryan & Veritone
https://www.veritone.com
https://linkedin.com/in/ryansteelberg/
About AI Leadership Lab
AI Leadership Lab interviews C-suite leaders about their AI journeys, covering what's working, where they're getting stuck, how they pivot, and the lessons they take from the losses.
Host: RyanHeathConsulting.com