Workers Are Overwhelmed, Most Consumers Don’t Want It: How Businesses Can Navigate AI Fatigue

Despite news of heavyweight tech investments, AI is hitting major roadblocks. From companies like Dell toning down AI language at CES 2026, to reports finding that two-thirds of consumers do not want AI on their devices. Internally, things in-house are not doing so well for workers either. A recent Harvard study found that AI tools didn’t reduce work, instead they consistently intensified it. 

These events and trends are all part of a broader wave, impacting markets, businesses, and consumers. AI Fatigue is real, and ignoring it is a risky roll of the dice. 

AI Accelerates Work Rate But Leads to Fatigue, Impacts Quality, and Weakens Decisions

On February 9, Harvard Business Review reported the findings of an eight-month study on how AI changed work habits. The study found that while AI accelerated the pace of work, it also led to cognitive fatigue, burnout, and weakened decision-making. This in turn, led to lower quality of work, turnover, and other problems. 

“Everywhere we turn today, we are surrounded by AI discussion and questions,” Jenny Sagström, founder and CEO of the B2B creative agency Sköna, told us.  

Sagström, who has worked for the past 20 years in the world of B2B tech branding and is currently working with companies like Snowflake, Cloudflare, and Witness.ai, said that while AI has introduced countless improvements to the workplace, it is also driving AI fatigue. 

“We’re constantly badgered with questions and comments about how to best — and how not — to use AI. So, yes, I believe AI fatigue is real,” said Sagström.

“AI can probably write better than I can, but unless I sit down and actually write myself, I won’t go through the thinking process of determining what my stance is,” she added

The Cost of the Never-ending Digital Transformation

“While AI fatigue is very real, it’s indicative of a broader issue impacting the workforce: transformation fatigue,” Fredrik Hagstroem, CTO of Emergn, a tech consultancy firm, told us. 

Transformation fatigue is a type of burnout workers experience from too many change initiatives happening too quickly and for too long, said Hagstroem. 

“From cloud computing and IoT to big data, machine learning, and now AI, the workforce has endured numerous transformations over the past 10 to 15 years — oftentimes with unclear results,” he added. 

Emergn’s own research found that 50% of employees have experienced transformation fatigue driven by frequent changes and transformations. More than half (61%) of U.S.-based CEOs recognized that transformation fatigue is a growing concern with the rise of AI.

An essay picked up by Business Insider and written by AI software engineer and developer Siddhant Khare gives us an inside look on what the AI transformation looks like at the individual level. 

Khare, who develops and engineers advanced AI systems, wrote in the essay that AI fatigue is “the kind of exhaustion that no amount of tooling or workflow optimization could fix.”

“I shipped more code last quarter than any quarter in my career,” said Khare. “I also felt more drained than any quarter in my career. These two facts are not unrelated.”

Two-thirds of Consumers Say They Don’t Want, Need, or Will Pay for AI

From the consumer’s point of view, AI has also lost its shine, with studies saying that most users do not want AI. A January 27, 2026 Circana report found that about 7 out of 10 consumers do not want AI on their device. The study revealed that many consumers feel they simply do not need the technology. Additionally, 59% of those who do not want AI have privacy concerns, and 43% said they do not want to pay extra for AI. 

“Workers and consumers are still immersed in lots of hype around new foundation model releases,” Mike Hulbert, CEO of Solvd, an AI engineering company, told us. 

Studies show that increasingly more consumers use chatbots to varying degrees to research and answer questions in daily life. From the perspective of these use cases, the capabilities appear to have plateaued, said Hulbert 

“As someone who regularly makes architectural decisions and is involved in implementing AI, I see it as a gap between what people expect and what they actually get,” Philip Tikhanovich, Head of Big Data Engineering Department at Innowise, a software development company, told us. 

“There are a lot of products on the market where AI has been added just for the sake of it, and people have to figure out how to use a new button or scenario (many of which don’t really make things easier),” said Tikhanovich.

As a result, consumers lose trust and become banner-blind to any AI features, even useful ones. “Within companies, it often leads to exhaustion and irritation among teams,” said Tikhanovich. 

“Instead of the promised acceleration, they have to double-check results, switch between tools, and learn how to use half-baked features”.

Business Leaders and Investors Have Their Own View on AI Fatigue and How to Mitigate It

On February 5, Wall Street closed sharply low, as AI worries took over investors’ confidence. The Nasdaq fell to its lowest since November, driven by losses in Microsoft (MSFT.O), Amazon (AMZN.O), and other big tech heavyweights, after Alphabet (GOOGL.O), said it could double capital spending on AI. What worries investors is that more big tech spending is expected to significantly impact free cash flow. 

Executives are also doubling down on AI spending. A recent annual survey from Teneo found that more than two-thirds (68%) of CEOs are doubling down on AI investments in 2026, even when most of their AI projects are not profitable. 

“I think that AI fatigue is real for workers and consumers, but not so much for business leaders,” Hulbert said. 

According to Hulbert, much of the fatigue is being driven by what people hear outside of work versus what they hear at work. 

For this reason, leaders need to communicate authentically about what is and isn’t working in their AI initiatives, provide staff tangible opportunities to participate in evolving their work, and begin to also focus on the opportunity to reduce external spend (vs only productivity), he advised. 

“Platitudes are really counterproductive – messages need to be framed by specific challenges in a company and how AI is helping to tackle those challenges,” he added. 

Tikhanovich said companies can start out with an “easy one” to reduce AI fatigue. 

“Instead of AI-first, switch to utility-first (i.e., only use technology where it really saves time or reduces friction),” he said. 

Training teams and building AI in a way that doesn’t require extra steps and always gives people a choice, including being able to turn it off or fall back to the old workflow, is the way to go, according to Tikhanovich.   

“A value audit is also critical … I suggest regularly reviewing AI features — keep only what actually saves time.”

With market analysts still crunching numbers and undecided on the AI bubble, big tech and businesses announcing big AI investments — even if most AI projects do not bring in revenue, and reports showing that consumers and workers are hitting an AI fatigue wall — experts agree that steps need to be taken. 

From transparency to building trust, empowering workers, and deploying only the features that work, business leaders need to step up to avoid the traps of AI fatigue.