The $700 Billion AI Productivity Problem No One's Talking About

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Dec 1, 2025

In this conversation, Russ Fradin, founder of Larridin and an early ad-tech pioneer, discusses the critical need for measurement infrastructure in AI adoption. He reveals how employees often hide their AI tool usage, while companies remain clueless about their value. Fradin highlights the challenges of measuring productivity, emphasizing that AI budgets may not lead to real results. He also explores employee anxiety and the role of training in successful adoption, advocating for data-driven metrics to enhance AI effectiveness in the workplace.

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Measurement Is The Missing AI Infrastructure

Enterprises are spending massive amounts on AI without a reliable way to measure whether it works.
Measurement infrastructure made digital ads scale and the same is now the missing piece for AI.

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From Early Ad Tech To AI Measurement

Russ Fradin recounts being first at the first online ad network and later at Comscore, building measurement for internet ads.
That experience inspired Larradin to build measurement and governance for AI spend and adoption.

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Begin With A Usage Baseline

Start by asking a simple baseline: did anyone actually use the AI tools you bought?
Detect undisclosed or unmanaged AI use across the company before judging value.

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