J.P. Morgan says AI hype era is officially over

For years, Wall Street has poured billions into AI-focused companies on the strength of strategic promises. Now one of the most influential voices in global dealmaking says the technology has moved from hype to real execution and scaling.

That era of speculative betting on flashy presentations and vague roadmaps may be reaching a turning point, and one of the most influential voices in global dealmaking is calling time on it.

Kevin Brunner, JPMorgan Chase’s global chair of investment banking and mergers and acquisitions, told Bloomberg Television that the technology sector has entered a new chapter.

His message to investors, executives, and the broader market carries significant weight because JPMorgan sits at the center of the largest technology transactions happening worldwide.

JPMorgan’s Brunner declares AI has entered the execution and scaling phase

Brunner made his remarks during JPMorgan’s 54th Annual Global Technology, Media and Communications Conference in Boston, a three-day gathering running May 18 through 20 that draws the most powerful technology executives and institutional investors.

“We’ve actually gone from hype to real execution and scaling,” Brunner told Bloomberg TV’s Lisa Abramowicz on the sidelines of JPMorgan’s conference in Boston.

He told the conference audience that the bank is seeing every single client actively evaluate where they stand in the AI landscape and how they need to adapt long-term strategies accordingly.

For the average investor, that shift matters. The market may soon reward companies that demonstrate real AI productivity gains, rather than those that simply announce AI initiatives without proof.

AI is reshaping JPMorgan’s M&A pipeline and driving major consolidation

Brunner’s comments carry particular credibility because his division oversees the mergers and acquisitions that define how corporations allocate hundreds of billions of dollars in capital across the technology sector.

He explained that the availability of capital has not slowed the pace of dealmaking, with corporate leaders pursuing large-scale transactions designed to position their companies ahead of the broader artificial intelligence transformation.

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That trend aligns with broader industry data showing global M&A volumes reached $1.22 trillion in the first quarter of 2026, representing a 26% increase over the same period last year, FinancialContent reported.

For consumers and workers, accelerating consolidation in the technology sector could reshape which companies control the tools and platforms they need for everything from banking to everyday health care services.

AI-driven dealmaking is accelerating tech-industry consolidation as corporations race to secure dominance in the next wave of artificial intelligence.

Nitat Termmee/Getty Images

Enterprise adoption data shows AI execution is mixed

Independent research reinforces the picture Brunner painted at the Boston conference, with multiple reports showing that corporate spending on AI is shifting from experimental pilot programs to full-scale deployment.

CB Insights tracked 266 AI-related mergers and acquisitions that closed in the first quarter of 2026, a 90% jump from the same quarter a year earlier, according to its State of AI Q1’26 Report.

The transition from hype to deployment does not guarantee that every company will succeed; however, investors should recognize that execution risk is replacing speculation risk as the primary concern going forward.

A May 2026 report from HCLTech estimated that roughly 43% of major enterprise AI initiatives are expected to fail in 2026 because many organizations are moving faster than their internal capabilities support, BusinessToday reported.

What JPMorgan’s AI shift could mean for technology investors

Brunner’s comments suggest the investment calculus for technology stocks may be shifting from speculation about AI potential to execution and measurable productivity gains.

Ivan Nikkhoo, managing partner at Navigate Ventures, offered a complementary perspective in a February 2026 analysis, writing that the underlying AI transformation will persist because it is tied to fundamental modernization rather than short-term excitement.

I think 2026 will be a great year for AI…. Productivity will grow faster than almost anybody realizes. I think the market is underestimating that on earnings.

PwC’s US Deals 2026 outlook confirmed that technology M&A is entering a new phase defined by the pursuit of AI capabilities and the infrastructure needed to support them, with buyers targeting data centers and chips.

Brunner’s comments suggest investors will increasingly scrutinize whether companies in their portfolios demonstrate measurable AI productivity gains rather than relying on prior announcements.

The next several months will separate AI winners from the rest

Brunner’s framing positions the AI market as entering a sorting phase rather than a settled one. The capital is flowing, the deals are getting done, and the deployment intent is widely shared but the gap between ambition and operational follow-through is where the next wave of winners and losers will be defined.

Which companies translate AI investment into measurable productivity gains, and which find their execution outpaced by their ambition, is the question the rest of 2026 is set to answer.

Related: J.P. Morgan examines if AI is really after your paycheck

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