31% of employees are actively ‘sabotaging’ AI efforts. Here’s why

A significant proportion of the U.S. workforce is pushing back against Artificial Intelligence adoption at their jobs.

According to a new study by generative AI platform Writer, 31% of employees—including 41% of Gen Z workers—admit to “sabotaging” their company’s AI strategy by refusing to adopt AI tools and applications. As a result, roughly two-third of executives say Generative AI adoption has led to tension and division within their organization, with 42% suggesting it’s “tearing their company apart.”

“There’s active resistance where it’s like, ‘I really don’t believe in this strategy whatsoever, and I’m either going to completely ignore it, or do my own thing,’” says Writer’s chief strategy officer Kevin Chung. “And the passive resistance is often, ‘I’ll give it a try, but I’m not going to put my hand up and say here’s how to improve it. I don’t want to waste my time and effort on it.’”

Different reasons, same results 

As the technology matures, the most common fears associated with AI adoption have evolved, though the end result is still the same. 

“Two years ago, nine times out of 10 it was about ‘why am I training the robot that’s going to take my job away from me?’ and today maybe one or two out of 10 concerns I hear are about job displacement,” Chung says. Instead, he says workers are shying away from the technology because it hasn’t yet proven its usefulness. “Now that they’ve had a chance to play with it, [many employees] are quite disappointed in the results they’ve seen, and that’s why they are disillusioned by it.”

That observation is consistent with another survey of 1,100 executives and managers from 2023. It was conducted by Leadership IQ, wherein just 10% said their employees were “excited” about the technology, and another 35% were “cautiously optimistic.” The remaining 55% were either “in denial,” “resistant,” “reluctant” or “indifferent.”

Though the results haven’t yet been made public, the research and consulting firm’s founder and CEO Mark Murphy says a recent follow-up study (set to be published next month) found similar results.

“The numbers [of those who are “excited” or “cautiously optimistic”] are looking mildly better, but not drastically. There was still a shocking amount of denial,” he says. “The percentage of people who have no experience with AI has dropped considerably, but we haven’t made a dent in [increasing the proportion on] the intermediate and advanced side of things. We’ve just shifted a lot of people from ‘no experience’ to ‘beginner.’”

As more American workers utilize AI tools for the first time, Murphy has also found the most common motivations for pushing back have evolved from fear to disappointment.

“We’re still playing with it as a one-off tool—something we depart from our normal job and play with for a few minutes, have it answer a question or two, rather than fully integrating it into our work,” he says. “We’re still in that early stage of AI use.” 

A tense time for employee-employer relationships 

At the same time, Murphy suggests the adoption push has coincided with a period of strained relationships between workers and their employers, which is likely making it harder for them to proceed with their AI plans.

“A potential wrinkle in this right now is that there is . . . a little more of an adversarial dynamic between management and frontline employees,” he says. “You can see this with return-to-office initiatives, for example, and I think this is sort of a harbinger of things to come with AI.”

Just as some employers are forcing staff back into the office under threat of losing their job, some are also taking a similarly harsh approach to AI adoption. That could explain some of the high rates of disengagement and active resistance.

“There was a little bit less empathy for what employees might be going through,” Murphy says of RTO mandates. “My guess, based on everything else we’ve seen, that a similar mindset will be adopted—and already is, in some cases, being adopted—when it comes to AI.”

Finding the right approach 

Murphy advises employers looking to make an AI push to really emphasize the benefits that adoption will have for the individual employee, as well as the broader organization.

“The litmus test is, ‘what sort of training are you providing such that my AI skills are not just sufficient to implement your particular AI, but take me a level up?’” he says. “Getting people to the level where they can essentially train their replacement is one thing. There will also be an abundance of people that master AI to the point where they are fluent and can use it to pursue new strategies that add to their value.”  

The high rate of AI resistors may be a function of the high rate of AI beginners, who don’t feel like the skills they’ve developed really add anything to their personal value and employability. Getting more people excited about AI, Murphy argues, requires providing the kind of training that they can put on their résumé or showcase in a performance review.

“If it feels like a black box that’s sprung on the frontline worker, they probably won’t trust it,” adds Sarah Elk, Bain & Company’s AI, insights and solutions practice leader for the Americas. “You’ll get results far faster if you take the time up front to engage in a thoughtful process with the people who will be impacted.”

AI adoption is about people

Elk says organizations looking to adopt AI solutions often run into challenges when they focus on the technology rather than the people who will use it, and ultimately determine its success.

“If I’m just unleashing [an AI tool] to my entire population without any thought as to how that is helping them or helping the company, I shouldn’t expect dramatic outcomes,” she says. “I believe in broad access. But that has to be paired with leadership and sponsorship, top-down, around areas of value that we’re driving towards.”

To make those integrations successful, Elk says organizations need to explain how the technology will solve specific problems for staff, while giving them some latitude to experiment and find new ways to use it to their advantage.  

“If you’re applying AI with brute force and not being thoughtful about how it relates to the work, to the process, to the outcome, to your competitive advantage—when that isn’t clear—then yes, I could understand why it might be confusing to a frontline worker,” she says. “When you’re doing it right, you don’t face resistance.”