It seems likely that Generative AI has hit the part of the hype cycle that Gartner famously calls the “trough of disillusionment,” when the initial over-estimates of a new technology’s revolutionary potential clash with the disappointments of initial rollouts.
Citing surveys that found only 11% of Americans use AI at work, the Economist writes that, “Three years into the generative-AI wave, demand for the technology looks surprisingly flimsy.” In a similar vein, on No Jitter, Matt Vartabedian reports on a CompTIA survey that found, “Nearly 4 in 5 companies that attempted to substitute an AI solution for human work backtracked after AI failed to meet business criteria.”
“Companies backtracked largely because their expectations entering the rollout didn’t match what AI delivered,” Matt writes. “For example, 52% said the AI output quality was lower than expected, 50% said they couldn’t scale it to handle more sophisticated tasks, 48% said it was more costly than expected and 47% said it was more difficult to integrate into existing workflows, the report found.”
Matt goes on to note in his article that failure isn’t necessarily a bad thing. Failures only happen if you’re trying things, and trial-and-error is generally how we figure out how to use new technologies. If we’re experiencing more of the “error” part of the process now, it doesn’t mean we give up.
But the process does require learning from the errors, and that’s going to be a big focus at Enterprise Connect 2026. One reason we changed the focus of our conference track structure for the upcoming show is that we wanted to approach technologies like AI in the context of real-world problems and solutions, not just as pure technology. Many of our AI-related sessions can be found in the track titled, Tech Disruption Zone: Implementing Without Imploding, whose name reflects the practical approach we believe enterprises need to take when it comes to AI. Sessions in this track focus on real-world problems like ROI, security, project scoping, and user adoption, among others.
We’ve also got a Keynote panel planned, provocatively titled, What If AI Never Pays Off? Like any good debate topic meant to spark controversy, the issue is posed in stark terms, but the underlying challenge is real: Even if a given AI project achieves its objectives in terms of business processes, how do you make sure its implementation was worth the cost in money, time, and staff focus? And, pulling back to look at the big picture, just how transformative will AI, writ large, have to be in order to justify the gargantuan investments being made to implement it pervasively? What will it take to achieve such a payoff?
One answer, of course, is that the only real transformation with a payoff would come in the form of massive displacement for workers at all layers of society. And indeed, KPMG has found that more than half of workers fear just such displacement, according to CIO Dive. Though such effects are beyond IT’s remit or control, tech organizations themselves would be unlikely to escape any such enormous transformation in the shape of the workforce.
EC2026 won’t be gloom-and-doom for AI; our Tuesday summit will offer up-to-date lessons on the technology, as will conference breakouts on Wednesday and Thursday. AI represents a big change for everyone, which means its impact will be multi-faceted, good and bad, scary and promising. EC2026’s program is built to provide you with deep knowledge on as many of these facets as we can squeeze into three full days. I hope you can join us March 10 – 12 in Las Vegas.
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Our mission is to equip you with the tools, strategies, and actionable insights needed to address your organization’s unique challenges. With industry transformation in mind, this year’s program introduces fresh new conference tracks, including:
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- Tech Disruption Zone: Implementing Without Imploding
- Achieving Transformation: Architecting Your 3-5 Year Roadmap
- Future Shock: Communications Tech Beyond the Horizon
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