- Workers will be wary of AI due to job loss narratives and this could impact how much they use it
- Many workers are seeing productivity benefits, and this could contribute to a positive reaction to using AI
- There is evidence that AI use can be demoralizing, especially if it takes away work that challenges and engages workers
This article is part of an interview with Dr. Matthew Call, associate professor of management at Texas University’s Mays Business School. This interview was conducted for Tech.co’s AI newsletter, The AI Strat. For more interviews, with AI experts on the latest trending topics, subscribe to the newsletter.
There are many reasons why a worker may not want to use AI. The potential for AI to cause mass layoffs is well-documented by the technology’s leaders. Plus, environmental concerns remain poignant, as are concerns about declining cognitive abilities.
There are workers who are seeing significant gains when using AI, and jumps in productivity could lead to more motivation and enjoyment at work.
However, others may feel differently. As AI takes over more and more tasks, it may end up replacing many of the more challenging and stimulating elements of a role, meaning motivation and ambition takes a hit.
How Do Workers Feel About AI?
The general message from businesses to workers has been to experiment with AI, and figure out how it can work for your processes. Mostly, AI’s strengths since then have been in the tedious, repetitve tasks that take workers away from valuable work. That being said, AI is still changing roles, beyond automation.
Dr. Matthew Call, associate professor of management at Texas A&M University’s Mays Business School, researches how human capital and talent can be managed in the AI era, and what this means for the future of the workforce.
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Mostly, Dr. Call told Tech.co, worker sentiment is mixed. It varies across roles, and definitely across different generations of the workforce.
Workforce Concerns Can Overshadow AI’s Capabilities
Dr. Call works directly with individuals coming out of graduate degrees, and are entering the job market for the first time. The entry-level job market is arguably where AI’s impact is already being felt.
Certainly, studies indicate employment among 22-25 year olds in highly AI-exposed roles is 19% lower than peers in less AI-exposed roles. Likewise, the current unemployment rate for recent graduates is higher than the general unemploment rate in the US.
There is a strong sense that what is being seen for entry-level job seekers will one day spill over into the wider job market. AI leaders have certainly made predictions that swing this way, and even if these were later revised, the narrative around job losses has contributed significantly to worker attitudes.
Dr. Call explained how some workers will have this in mind when it comes to AI. Workers will be saying to themselves: “I’m working with this AI tool…and it’s asking me all sorts of questions and taking very detailed notes, and remembering everything I do, and is able to replicate what I do within six months.”
Dr. Call says that to them, this is a “rational, self-protective reason” why workers will not want to engage with AI. If you’re training an AI to do certain elements of your job, it’s natural you’ll fear being replaced. And then, you wouldn’t want to use it.
Workers Are Seeing the Benefits
There is another worker profile I spoke about with Dr. Call: “They see the value show up, where they can be ten times more productive, and they’re power users, and they’ve institued AI across their processes and systems.”
These are the workers that have adopted AI broadly, and are seeing the benefits. These are sometimes “AI champions,” individuals within organizations that power and accelerate AI across their company. But, they can also be standard workers.
Typically, Dr. Call says existing domain expertise means you tend to be much more effective with AI. Plus, “you have good judgment around your content and area of application,” he told me. These workers are on the opposite side of those who have less experience and aren’t as good as, for example, catching AI’s mistakes.
Naturally, if workers start to see increased productivity while they’re using AI in their role, this could have a positive impact on motivation.
The Potential Link Between AI and Motivation
Dr. Call spoke to me about a “motivation curve” he sees with workers using AI: “Once they figure out what AI can do, it energizes them to ask questions and solve problems that they may not have figured out before. It gives them this sense of efficacy.”
“You get on that motivation curve,” he continued, “but eventually a lot of these folks find it hard to sustain, because they say yes to twelve different things and they’re constantly working with AI to do all of these jobs. And that can actually get demotivating afterwards.”
Mentally, working with AI can take its toll in other ways. A study from Tech.co identified a “rework tax” for workers using the technology, where a lot of time is spent reviewing, editing, and correcting AI-generated errors and hallucinations.
And, because AI isn’t yet perfect at doing everything a human worker can, the opportunity for error is rife. Constantly asking AI to complete tasks for you, and then repeatedly correcting it, could contribute to frustration and a lack of motivation in your role.
But, there’s also evidence that AI is removing some of the more interesting aspects of roles. A study from AAPL found that despite seeing performance benefits, users that collaborated on a task with generative AI, and then moved to completing a task independently, reported a decline in intrinsic motivation and an increase in boredom.
The researchers comment: “Collaboration with gen AI can remove the most cognitively demanding parts of a task, often the aspects that make work stimulating and personally fulfilling… When gen AI generates much of this content, the process becomes less engaging, and humans may feel disconnected from the task.”
Ultimately, it’s too early to know exactly how AI will impact motivation, as this is usually a long-term, gradual shift that can’t be measured in the short time AI has been around. However, worker sentiment around AI will be critical for its longevity in the workplace.
