8 Experts’ Work and Technology Predictions for AI in 2026

While there is no doubt that artificial intelligence is a boon to both business and life in general, it does have a significant downside. Dependence on AI replacing the labor that actually breeds intellectual experience —right now unreplicatable by AI — are just two aspects. Some think that the speed of the workplace which was geometrically increased with the advent of technology itself will now find itself at superspeed with AI, ratcheting up the stress level of the organization to the breaking point. And there are many other considerations to be made. How we handle them will be the new differentiator in the marketplace and propel some companies to new heights while causing those that cannot handle the new thinking and speed of business crash and burn. This is a critically important article to review.

FROM INC MAGAZINE / BY REBECCA HINDS

The new tools are rapidly changing the workplace, and these professors say many companies aren’t ready.

2025 has been a blur of AI breakthroughs and breathless hype, with the technology sprinting ahead of most leaders’ ability to keep up. So when I asked the Founding Members of Glean’s Work AI Institute what they expect in 2026, I expected a range of predictions. Instead, they converged on the same concern: AI is now generating work at a pace most organizations can’t metabolize.

Collaboration will rely on pairing AI with human expertise

Open your inbox — or wander through your digital workplace — and you’ll see a new corporate dialect: polished, confident AI prose that often says almost nothing.

Harvard professor Jackie Lane worries that as AI makes everything look more polished and confident, real expertise becomes harder to spot. Her research shows that when AI offers polished recommendations or convincing explanations, humans often defer to it — especially when under a heavy cognitive load. 

Lane says this is why 2026 will push leaders to rethink who does what: what can be reliably handed to AI, and what must remain human. AI can generate authoritative-sounding answers efficiently and at scale. Humans provide what AI cannot: judgment, scar tissue, and the instinct to poke holes in tidy solutions that fall apart in the real world.

Organizations will wake up to the costs of ‘botholes’

Bob Sutton, Stanford professor emeritus, warns that AI is flooding workplaces with “botholes”: AI tools that make it effortless to waste others’ time. These systems enable what he calls the “weaponization of friction,” spraying high-gloss workslop and automated pestering onto colleagues who must interpret or swat it away.

Sutton hesitates to predict what’s ahead for 2026 as he worries this problem will worsen. But he hopes organizations will grasp how much attention these botholes burn — and eventually deploy “friction bots” to shovel them out of the way.

Organizations will have to rethink their productivity metrics

The danger of AI slop isn’t just the noise. It’s the illusion of productivity that it fuels. 

Emory University professor Hancheng Cao expects AI to trigger a reckoning in how companies measure productivity in 2026. For years, organizations have clung to visible output — lines of code, documents, tickets closed — as a proxy for progress. But AI will force leaders to shift from counting output to evaluating real outcomes. His research, for example, shows that AI is more accurate when comparing two papers side-by-side than scoring them with a number, pointing to a future where evaluation relies less on tallies and more on the context that determines the quality of the work.

As AI gains a deeper view into how work moves through an organization, it will surface what truly advances KPIs and what’s merely performance dressed up as productivity.

AI will save time. Most organizations will spend it on more work

Steven Rogelberg, Chancellor’s professor of management at UNC Charlotte, predicts that in 2026, AI will keep delivering productivity gains. But most organizations won’t use the time saved to improve the employee experience or give people time back to invest in their families, communities, and broader society. They’ll use it to pile on more work and drive more productivity — and, he warns, “the promise of AI to elevate humanity will suffer.”

Rogelberg worries that as AI speeds things up, extra capacity will invariably get filled with new tasks and expectations, and a faster pace. Smart leaders will redirect some of the time savings into improving the work itself and the experience of doing it, rather than letting it all get swallowed by another flavor of grind. 

AI will erode the thinking work that keeps teams aligned

University College London professor Jen Rhymer warns that AI isn’t just sanding down content. It’s erasing the engagement teams need to stay aligned. Her research shows how essential “rich work trails” are: the messy context and back-and-forth behind decisions that keep distributed teams coordinated.

When AI wraps everything in a polished veneer, it strips out the grappling and questioning that create real alignment. The result is debate that looks settled but isn’t — and work trails that collapse under pressure.

AI will drive work intensification in subtle, easy-to-miss ways

Because AI makes many tasks feel effortless, it can pull people into doing more work than they realize. University of California Berkeley professor Aruna Ranganathan expects this to ripple through organizations in 2026. In a recent study with doctoral student Maggie Ye, they identified “voluntary work intensification”: people taking on extra work not because anyone asked, but because AI made things feel lighter and more doable.

That ease pulled people into adjacent tasks they’d never touched before — for example, engineers dabbling in design work. And because interacting with AI feels like casual conversation, that extra work spilled into lunch breaks, meeting gaps, and late nights.

Digital exhaustion will outrun digital adoption

Bloated and fragmented tech stacks only increase the cognitive burden on employees. UC Santa Barbara professor Paul Leonardi’s research shows that when work is distributed across multiple systems, teams spend significant time hunting for information and ping-ponging between tools rather than completing tasks — leading to digital exhaustion.

In 2026, Leonardi predicts that competitive advantage will depend not on stockpiling new technologies, but on absorbing and integrating them into everyday work.

Cutting early-career talent will put organizations at a disadvantage

As digital exhaustion rises, many organizations are cutting the people who may be best positioned to keep them nimble: early-career employees. Notre Dame professor Yong Lee — whose research finds that younger workers face greater negative labor-market effects from rising AI exposure than mid-career workers—warns that this will carry consequences in 2026 and beyond. 

Younger workers often adapt faster to emerging technologies, carry fewer sacred cows, and have the instinct to poke, question, and dismantle outdated workflows—exactly what organizations need as AI forces a ground-up redesign of work.

And that’s at the core of all of these predictions — a recognition that AI only works when organizations ground their efforts in a deep understanding of how work really happens.