The Other AI Revolution: Why Predictive AI will Overtake Generative AI in 2027

Predictive AI often gets ignored, yet it may hold the real key to business value in the current tech landscape. Machine learning expert Eric Siegel, author of The AI Playbook and Predictive Analytics, joins the Digital Disruption podcast to explain why organizations should invest at least as much in predictive AI as they do in generative AI. He breaks down how predictive AI can improve real-world operations, why so many AI pilots fail to reach deployment, and where the promise of autonomous AI agents encounters reliability challenges. While generative AI captures the headlines, Eric argues that more dependable returns often come from systems that predict outcomes and improve decision-making. The conversation explores the differences between predictive and generative AI, why meaningful business value comes from deployment rather than impressive demos, and the limitations of fully autonomous AI agents and artificial general intelligence. Tune in to learn how predictive AI could make generative AI more reliable, why business leaders and data scientists need to work together, and whether AI will really cause a job apocalypse. Like and follow for more conversations on AI, technology, innovation, the future of work, and digital transformation. 00:00 Why businesses may be investing in the wrong AI 00:47 Predictive AI vs. generative AI 03:01 How large language models fit into predictive AI 06:59 What kind of AI is solving real-world problems? 08:06 The two “wows” of AI: Impressive demos vs. deployment 09:28 Build your AI strategy with Info-Tech 10:37 Why predictive AI is still delivering business value 12:32 Why most AI pilots fail to reach production 16:25 AI hype and mismanaged expectations 19:31 AI agents, AGI, and the promise of autonomy 20:44 Can predictive AI make generative AI more reliable? 23:57 Why full AI autonomy remains unrealistic 26:59 Large language models vs. human intelligence 29:21 The limits and diminishing returns of AI models 31:35 What businesses are getting wrong about AI 35:35 Bridging the gap between technology and business leaders 37:18 Why leaders need a semi-technical understanding of AI 38:59 Three questions every predictive AI project must answer 42:22 Will AI replace developers and other technical roles? 49:29 Who should own AI strategy and accountability? 53:41 Is AI creating the productivity gains we were promised? 55:49 Could future technology overcome today’s AI limitations? 59:21 How organizations can unlock more value from AI 1:01:43 Eric Siegel’s six-step AI deployment framework 1:04:42 Why AI is a business improvement project, not a tech install 1:06:02 What’s new in The AI Playbook 1:09:30 Eric’s advice for business and technology leaders 1:10:46 About Info-Tech Connect with Eric: LinkedIn: https://www.linkedin.com/in/predictiveanalytics/ X: https://x.com/predictanalytic?lang=en IG: https://www.instagram.com/eric_siegel/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG