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.
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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/
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