Research shows: AI is growing, but support is declining

AI keeps getting better, yet sentiment about AI in the workplace seems to be deteriorating. That is what makes the recent Glassdoor figures both interesting and concerning. In 2019, 81 percent of employee reviews that mentioned AI were positive. In 2026 that figure is down to just 43 percent, while 53 percent are now negative. This is a development we need to take seriously.

The promise: room for meaningful work

At the same time, I am convinced that we urgently need AI. To become more productive, to absorb labour-market shortages and to meet societal challenges. At The Automation Group I see every day the positive impact AI and AI agents can have. It is not only about working faster or cheaper. In many projects we see repetitive and administrative tasks disappear, giving employees more time for customers, advice, collaboration and human contact. Work shifts towards activities that are closer to an organisation's values and purpose. To me, that is one of the most important promises of AI: technology that gives people room to do more of the work that truly matters.

The Matthew effect: those ahead pull further ahead

But that positive outcome does not happen by itself. Scientific research reveals several mechanisms that can explain why AI can also lead to more inequality and resistance. One of them is the so-called Matthew effect: people who already have more knowledge, skills, autonomy or access to technology can exploit new technology faster and thereby extend their lead. Recent research even speaks of an AI-specific Matthew Effect in this context.

At the same time, research by Erik Brynjolfsson, Danielle Li and Lindsey Raymond among more than 5,000 customer service employees shows that generative AI can help less experienced and lower-performing employees the most, relatively speaking. That is an important nuance. AI can narrow differences between employees, but it can also widen them. The technology itself does not determine that. The way we introduce AI within organisations, make it accessible and teach people to work with it is crucial.

Organisational culture as a second explanation

A second explanation therefore lies in organisational culture. In many organisations the frontrunners are made most visible: the AI champions, the employees with the best prompts and the most impressive applications. That can be inspiring, but it can also have the opposite effect. For virtually everyone, AI is new. When employees mainly see how far others already are, it can reinforce the feeling that they are falling behind. That can cause insecurity and eventually resistance.

Precisely for that reason we need a culture in which people are allowed to learn together, ask questions, make mistakes and share experiences. Research into psychological safety has shown for years that teams learn better when employees feel safe to voice uncertainty, experiment and discuss mistakes. In my view that applies to AI above all. We should not only show who is furthest ahead, but above all create conditions in which everyone can learn and develop along.

AI adoption is a social challenge

AI adoption is therefore not only a technology, strategy or data challenge. It is at least as much a social and organisational one. We must prevent AI from becoming a technology with which a small group pulls ever further ahead while others drop out. That means investing in broad access, training, time to practise and above all in a culture in which learning together matters more than showing who is in front.

That is why in my keynotes, alongside the practical application of AI, AI agents, strategy and the data foundation, I increasingly devote attention to another theme: AI for equality, not polarisation. From artificial intelligence to human progress.

Because ultimately the most important question is not only what AI technically makes possible. The real question is who benefits from that progress, who risks being left behind and how we ensure that AI brings people closer to meaningful work, customers, each other and the purpose of their organisation.

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About the author: Job van den Berg is an AI keynote speaker, tech entrepreneur and author of five books about AI. He puts agents into production himself every week and gives 150+ keynotes per year on AI agents and agentic commerce.