After a year when artificial intelligence seemed to be everywhere, the question heading into 2026 is no longer whether AI matters, but how the story evolves. Is this the early stage of a productivity revolution, or the crest of a familiar boom-and-bust cycle? And if an AI bubble exists, as many investors and economists fear, should we be worried?

We asked Mike Lenox, Interim Dean and University Professor and Tayloe Murphy Professor of Business Administration at the University of Virginia’s Darden School of Business, to weigh in. Lenox co-hosts the “Good Disruption” podcast with fellow Darden vice dean and professor Yael Grushka-Cockayne, where they discuss technologies and practices challenging the status quo.

Are we in an AI bubble?

Yes, I believe we are in a bubble. This should not be feared and should be quite expected. This is common when we have the emergence of a major technological disruption. 

What is technological disruption? 

Technology disruption is the process by which new technologies replace old, reshaping competition, markets and society. Such disruptions are a hallmark of market-based economies and follow a common set of patterns: learning curves that drive S-curves of technology improvement and diffusion, market entry by existing market players and new entrepreneurial ventures that drive competition, and shakeouts that result in new business models and a new competitive ordering.

Where are we on the disruption timeline? 

We are already beginning to see a productivity revolution driven by AI in some sectors. I suspect that in the next 12 months, we will begin to experience the shakeout phase of the AI lifecycle where some high-flying start-ups and once successful incumbents will fail in the face of increased competition. Some will interpret this as evidence of AI being overhyped, but this is exactly what one would expect as the forces of disruption unfold.

This feels a lot like the dot-com bubble in 2000.

I believe that similar to the dot-com bubble, there are numerous AI companies that have suspect business models. Many have merely rebranded existing practices as “AI” in an attempt to gin up their valuations. Others are simply building wrappers around core AI technology from the likes of OpenAI and Anthropic. The key for investors is to identify those firms who have capabilities and offerings that create some barriers to imitation and competition.

How do companies position themselves for the potential burst?

The key to managing such major disruptions is to keep an eye on the big picture and not to overreact to the daily news cycle. Pay attention to the patterns of disruption that are well documented. Continually ask not only where market opportunities are being created, but ask how do your evolving set of capabilities create valuable competitive positions in a transforming marketplace. There may be many market opportunities that others are better positioned to capture. Have the discipline to recognize where you may be able to uniquely create competitive advantage.

 

About the Expert

Michael Lenox

Interim Dean; Tayloe Murphy Professor of Business Administration

Lenox’s expertise is in the domain of technology strategy and policy. He studies the role of innovation in helping a business succeed. In particular, he explores the sourcing of external knowledge by firms and this practice’s impact on a company’s innovation strategy. Lenox has a longstanding interest in the interface between business strategy and public policy as it relates to the natural environment; his work explores firm strategies and nontraditional public policies that have the potential to drive green innovation and entrepreneurship.

In 2013, Lenox co-authored The Strategist’s Toolkit with Darden Professor Jared Harris. His latest book, 

Lenox is a prolific author; his most recent book, Strategy in the Digital Age: Mastering Digital Transformation, examines how digital technologies and services enable the creation of innovative products and services, as well as identifying new competitive positions.

B.S., M.S., University of Virginia; Ph.D., Massachusetts Institute of Technology

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