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This column series takes a look at the greatest information and analytics difficulties dealing with modern business and dives deep into effective use cases that can help other companies accelerate their AI development. Carolyn Geason-Beissel/MIT SMR Getty Images MIT SMR writers Thomas H. Davenport and Randy Bean see five AI trends to take notice of in 2026: deflation of the AI bubble and subsequent hits to the economy; development of the "factory" infrastructure for all-in AI adapters; greater focus on generative AI as an organizational resource rather than a private one; continued progression towards value from agentic AI, regardless of the buzz; and ongoing questions around who should handle information and AI.

This suggests that forecasting business adoption of AI is a bit simpler than forecasting innovation modification in this, our 3rd year of making AI forecasts. Neither people is a computer or cognitive researcher, so we generally stay away from prognostication about AI technology or the particular ways it will rot our brains (though we do expect that to be a continuous phenomenon!).

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

It's tough not to see the similarities to today's circumstance, consisting of the sky-high appraisals of startups, the emphasis on user growth (keep in mind "eyeballs"?) over revenues, the media hype, the pricey facilities buildout, etcetera, etcetera. The AI market and the world at big would most likely benefit from a little, sluggish leakage in the bubble.

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It will not take much for it to occur: a bad quarter for an essential supplier, a Chinese AI model that's more affordable and simply as effective as U.S. models (as we saw with the first DeepSeek "crash" in January 2025), or a few AI costs pullbacks by large business clients.

This column series looks at the greatest data and analytics obstacles dealing with modern companies and dives deep into effective usage cases that can help other organizations accelerate their AI progress. Thomas H. Davenport (@tdav) is the President's Distinguished Professor of Infotech and Management and faculty director of the Metropoulos Institute for Innovation 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 leadership for over 4 decades. He is the author of Fail Fast, Find Out Faster: Lessons in Data-Driven Management in an Age of Disturbance, Big Data, and AI (Wiley, 2021).

Quantum computing has long seemed like science fiction. However scientists are entering a "years, not decades" age where quantum makers will start dealing with issues classical computer systems can't, states Jason Zander, executive vice president of Microsoft Discovery and Quantum. That looming advancement, called quantum advantage, might assist resolve society's most difficult challenges, Zander states.

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AI finds patterns in data. And quantum includes a brand-new layer that will drive far greater accuracy for modeling molecules and materials, he says.

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It's the very first quantum chip developed utilizing topological qubits, a design that inherently makes delicate qubits more stable and reliable. It's also the only quantum service engineered to capture and right errors. That architecture leads the way for machines with millions of qubits on a single chip, providing the processing power required for complex clinical and industrial problems.

Lead image developed by Kathy Oneha/ We. Illustrations produced with Create in Microsoft 365 Copilot.

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

, giving brand-new areas a competitive benefit. Over the last couple of weeks, IBM Think spoke with a dozen professionals in techresearchers, creators and leaders from IBM and beyondto get their insights on what to anticipate in the year ahead.