AI Brings Cheap Prediction & Expensive Change ft Avi Goldfarb Invisible Machines Podcast

Most organizations are still implementing AI as point solutions, dropping new technology into existing workflows to do the same work, just slightly better. The real value lies in system solutions that completely transform how organizations operate. Avi Goldfarb, economist and co-author of Prediction Machines, joins Robb and Josh to explain why AI adoption follows predictable economic principles and why internal resistance, not technology limitations, is the primary barrier to transformation. This conversation, recorded back in 2023, reminds us that most organizations continue to struggle with the same issues surrounding systemic change in 2026. Goldfarb's core argument: AI is fundamentally cheap prediction. Just as the internet made search and copying cheap, AI makes prediction cheap. When something becomes a commodity, the complements, the things that work alongside it, become more valuable. This includes compute power (benefiting Microsoft, Amazon, Google), unique data, and crucially, human judgment. The problem? System solutions require organizational transformation. They create winners and losers inside companies. When AI enables insurance companies to shift from pricing risk (the domain of powerful underwriters) to reducing risk (requiring marketing and behavior change expertise), the power structure fractures. Vested interests resist. Departments see their importance diminished. For leaders evaluating AI investments, the question isn't whether to adopt AI, it's whether you're willing to pursue system transformation and confront the organizational disruption that creates real value. Chapters 00:00 - Intro: Avi Goldfarb on AI as “cheap prediction” 01:37 - Have LLMs changed the prediction framework? 03:36 - Do we need “new economics” for generative AI? 04:15 - What got cheaper on the internet: search, copying, communication 05:07 - What becomes more valuable as prediction gets cheap? (complements) 05:49 - OneReach.ai sponsor: runtime for AI agents (GSX) 06:46 - AI adoption inside companies: invest in people + workflows 08:13 - Unintended consequences: jobs, bias, discrimination 09:47 - The bigger question: new value creation (not just replacement) 10:33 - Upskilling: writing and opportunity expansion for millions 12:30 - "No more excuses”: using ChatGPT for clearer communication 14:50 - Social media déjà vu: noise, polarization, participation 17:04 - Intermediaries changed: self-publishing, music, podcasting 19:06 - AI commoditization: $600 models + implications for OpenAI 22:36 - Where the money is: compute, data, and complements (not predictions)---------- Support our show by supporting our sponsors! This episode is supported by OneReach.ai Forged over a decade of R&D and proven in 10,000+ deployments, OneReach.ai’s GSX is the first complete AI agent runtime environment (circa 2019) — a hardened AI agent architecture for enterprise control and scale. Backed by UC Berkeley, recognized by Gartner, and trusted across highly regulated industries, including healthcare, finance, government and telecommunications. A complete system for accelerating AI adoption - design, train, test, deploy, monitor, and orchestrate neurosymbolic applications (agents). - Use any AI models - Build and deploy intelligent agents fast - Create guardrails for organizational alignment - Enterprise-grade security and governance Book a free demo: ---------- The revised and significantly updated second edition of our bestselling book about succeeding with AI agents, Age of Invisible Machines, is available everywhere: Amazon —

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AI Brings Cheap Prediction & Expensive Change ft Avi Goldfarb Invisible Machines Podcast is an episode from In Conversation with UX Magazine by Invisible Machines.

This episode is 50:41 long.

This episode was published on Feb 27, 2026.

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