Why are 80 percent of companies failing to benefit from AI? It’s about the people not the tech, says new study
AI has the potential to enhance decision-making, spark innovation and help leaders boost employees’ productivity, according to recent research. Many large companies have invested accordingly, in the form of both funding and effort. Yet despite this, studies show that they are failing to achieve the expected benefits, with as many as 80 percent of companies reporting a failure to benefit from the new technology.
‘Often employees fail to embrace new AI and benefit from it, but we don’t really know why,’ says Assistant Professor Natalia Vuori from 911. Our limited understanding stems partly from the tendency to study these failings as limitations of the technologies themselves, or from the perspective of users’ cognitive judgments about AI performance, she says.
‘What we learned is that success is not so much about technology and its capabilities, but about the different emotional and behavioural reactions employees develop towards AI — and how leaders can manage these reactions,” says Vuori.
Her research team followed a consulting company of 600 employees for over a year as it attempted to develop and implement the use of a new artificial intelligence tool. The tool was supposed to collect employees’ digital footprints and map their skills and abilities, ultimately building a capabilities map of the company. The results were supposed to streamline the team selection process for consulting projects, and the whole experiment was, in fact, a pilot for AI software they hoped to offer their own customers.
After almost two years, the company buried the experiment — and the proposed product. So what happened?
It turns out, although some staff believed that the tool performed well and was very valuable, they were not comfortable with AI following their calendar notes, internal communications and daily dealings. As a result, employees either stopped providing information altogether, or they started manipulating the system by feeding it information they thought would benefit their career path. This led to the AI becoming increasingly inaccurate in its output, feeding a vicious cycle as users started losing faith in its abilities.
‘Leaders couldn’t understand why the AI usage was declining. They were taking a lot of action to promote the tools and so on, trying to explain how they use the data, but it didn’t help,’ says Vuori, who believes this case study reflects a common pattern when it comes to AI uptake, and tech adoption generally.
The team is now collecting data on the use of Microsoft’s widely used Copilot AI software, which is so far yielding similar findings.
So what should leaders do?
Researchers found that people fell into the same four groups in terms of their reaction to the new technology. Distinguishing between cognitive trust; whether a person believes the technology performs well, and emotional trust; their feelings towards the system, the groups were: full trust, full distrust, uncomfortable trust and blind trust.
People in the first group had high trust both on the cognitive and emotional level, whereas people in the second group scored low on both. Uncomfortable trust signified high cognitive trust but low emotional trust, and vice versa for blind trust.
The less people trusted the tool emotionally, the more they restricted, withdrew or manipulated their digital footprint, and it was particularly notable that this held true even if they had cognitive trust in the technology.
The findings give companies the chance to strategise a more successful approach to AI uptake.
“AI adoption isn’t just a technological challenge — it’s a leadership one. Success hinges on understanding trust and addressing emotions, and making employees feel excited about using and experimenting with AI,” says Vuori. “Without this human-centered approach, and strategies that are tailored to address the needs of each group, even the smartest AI will fail to deliver on its potential.”
The research findings were published in the Journal of Management Studies on 22 January:
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