AI or Traditional Methods: the 2026 Review

This column series looks at the biggest data and analytics obstacles facing contemporary business and dives deep into successful use cases that can help other organizations accelerate their AI development. Carolyn Geason-Beissel/MIT SMR Getty Images MIT SMR columnists Thomas H. Davenport and Randy Bean see 5 AI trends to take note of in 2026: deflation of the AI bubble and subsequent hits to the economy; growth of the "factory" facilities for all-in AI adapters; greater focus on generative AI as an organizational resource rather than a private one; continued development toward value from agentic AI, in spite of the hype; and ongoing concerns around who must manage information and AI.

This indicates that forecasting enterprise adoption of AI is a bit easier than forecasting innovation change in this, our 3rd year of making AI predictions. Neither of us is a computer system or cognitive researcher, so we normally stay away from prognostication about AI innovation or the particular methods it will rot our brains (though we do anticipate that to be an ongoing phenomenon!).

We're also neither economists nor investment experts, but that won't stop us from making our very first prediction. Here are the emerging 2026 AI patterns that leaders should comprehend and be prepared to act upon. In 2015, the elephant in the AI room was the increase of agentic AI (and it's still clomping around; see listed below).

It's difficult not to see the resemblances to today's scenario, including the sky-high valuations of start-ups, the emphasis on user growth (keep in mind "eyeballs"?) over earnings, the media buzz, the pricey facilities buildout, etcetera, etcetera. The AI market and the world at large would most likely take advantage of a small, sluggish leak in the bubble.

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Building AI Roadmaps for Modern Enterprises

It will not take much for it to take place: a bad quarter for an essential vendor, a Chinese AI model that's much less expensive and simply as efficient as U.S. models (as we saw with the first DeepSeek "crash" in January 2025), or a few AI spending pullbacks by large corporate clients.

This column series looks at the greatest data and analytics obstacles facing contemporary companies and dives deep into effective usage cases that can help other companies accelerate their AI progress. Thomas H. Davenport (@tdav) is the President's Distinguished Professor of Information Innovation and Management and faculty director of the Metropoulos Institute for Technology and Entrepreneurship at Babson College, and a fellow of the MIT Effort on the Digital Economy.

Randy Bean (@randybeannvp) has been an advisor to Fortune 1000 companies on information and AI management for over 4 decades. He is the author of Fail Fast, Find Out Faster: Lessons in Data-Driven Leadership in an Age of Disturbance, Big Data, and AI (Wiley, 2021).

Quantum computing has actually long felt like science fiction. But scientists are going into a "years, not decades" period where quantum makers will begin taking on problems classical computers can't, says Jason Zander, executive vice president of Microsoft Discovery and Quantum. That looming advancement, called quantum advantage, might help fix society's most difficult difficulties, Zander says.

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AI discovers patterns in information. And quantum includes a new layer that will drive far higher accuracy for modeling molecules and products, he says.

Ways AI Will Redefine Enterprise Roadmaps for 2026

It's the very first quantum chip constructed utilizing topological qubits, a style that naturally makes fragile qubits more steady and trusted. It's likewise the only quantum service engineered to capture and correct errors. That architecture paves the method for makers with countless qubits on a single chip, supplying the processing power required for complicated scientific and commercial problems.

"The future of AI and science will not just be quicker, it will be fundamentally redefined." Lead image created by Kathy Oneha/ We. Communications. Illustrations produced with Create in Microsoft 365 Copilot. Story released on Dec. 8, 2025.

A year in tech can feel like a decade anywhere else.

, offering new areas a competitive advantage. Over the last couple of weeks, IBM Think spoke with a dozen experts in techresearchers, founders and leaders from IBM and beyondto get their insights on what to expect in the year ahead.