Your employees have AI brain fry & it’s affecting your business: BCG on fixing the problem

A central argument for AI in the workplace is that automation will give workers more time to focus on meaningful work.

The vision sees workers no longer be bogged down in boring, mundane, and routine tasks, instead having time for the deeper, strategic work that, historically, gets pushed to the bottom of the to-do list.

While there is some truth to this, new research from BCG identifies a worrying reality: employees are grappling with ‘brain fry’ from intensively using AI.

Of the 1,500 US workers working at large companies studied by BCG, 14% said they had experienced brain fry, defined as “mental fatigue that results from the excessive use of, interaction with, and/or oversight of AI tools beyond one’s cognitive capacity.”

This exhaustion caused employees to be unable to think clearly; they suffered with information overload and too much task and tool switching, as well as slower and worse decision-making.

Those with brain fry had 33% more decision fatigue than those without it – and minor and major errors were up 11% and 39% respectively. Brain fry also increased workers’ desire to quit their jobs.

Given these findings, AI brain fry is a huge business risk that organizations urgently need to take action on.

UNLEASH interviewed Gabriella Kellerman, one of the authors of the study and BCG Expert Partner and Director, about precisely what organizations need to do to alleviate the cognitive load that comes from AI, and why it’s the HR function’s responsibility to lead the charge.

Brain fry is an ‘early warning indicator’ for AI downsides

Brain fry is an “early warning indicator” for the negative impact of intensive use of AI.

“There’s such a thing as using AI too intensively,” Kellerman tells UNLEASH. “We cannot make an infinite number of decisions per day.”

“What we have to offer as humans is so powerful and unique, but it has real limits.

“In order for us to do high quality work, we have to honor that.”

This early warning of brain fry provides an opportunity for organizations to get ahead.

Kellerman tells UNLEASH that employers need to identify the “middle ground”.

This is where AI is increasing employee productivity and helping people “achieve that incredible impact that they can have on the business”, but it is not about going so far that it’s actually creating mental strain and risk for those negative outcomes, like more decision fatigue, errors and intention to quit.

“I do see HR leaders as incredibly essential in leading the way in this moment,” shares Kellerman. This links with BCG’s 10-20-70 rule – where 10% of organizational AI efforts should be on algorithms, 20% on technology and data, and 70% on people.

Kellerman’s message to HR is: “As always, we have to put on their own oxygen masks first.”

BCG’s data found that HR was one of the functions with the highest rates of brain fry. While the average rate of brain fry across functions was 14%, in HR it rose to 19.3% – the only department with higher rates in the study was marketing (25.9%).

It makes sense that HR would be grappling more with brain fry because the function is at the “leading edge” of AI use within organizations – transforming itself with AI, while also on the frontline of AI adoption across workforces.

As a result, HR needs to be “navigating [brain fry] first themselves, and learning best practices,” before they scale that to the rest of the organization, notes Kellerman.

UNLEASH asked Kellerman for some best practices to help get HR leaders started on their journey to alleviate brain fry in their organizations. What are standout organizations doing differently?

HR, here’s how to stop AI brain fry

The first step in tackling brain fry is understanding precisely what it means, and that it is different from burnout.

“Burnout is a measure from the previous world of work” – while it is important to look at and monitor, it is not the same as brain fry.

This may seem illogical, but that’s because of how the term burnout is used colloquially.

When it comes to true psychometric definitions of burnout, it is about emotional and physical exhaustion from work – that is different from “the intensity of cognitive overwhelm,” explains Kellerman.

Traditional work was about emotional labor, and the potential for conflict, but “we’re not having AI conflict,” instead “we’re draining a very different type of brain capacity.”

In fact, BCG’s data found that those with brain fry did not have burnout, and in many instances, AI actually helped reduce burnout because “AI can alleviate some of the challenges of more traditional knowledge work.”

This means that if HR is “looking for burnout signals as a measure of whether people are doing okay with AI, they won’t see the brain fry.”

HR needs to focus on measuring them both, which will require “a whole new branch of people analytics that’s about cognitive strain”, in addition to emotional and physical exhaustion.

Gabriella Kellerman, Expert Partner and Director, BCG.

Once organizations have figured out the true scale of brain fry across their employee base, the next focus is to clearly define AI’s purpose in an organization.

“People are craving a lot more clarity about why they’re doing what they’re doing, and how current actions will ladder up to the long-term success of the company”.

Employers need to produce (and communicate) a clear AI strategy. It must not incentivize quantity of AI use, but, instead, focus on quality and work-life balance.

The study found a “huge impact when organizations were driving home the message of work-life balance – this is highly protective against brain fry.”

“We have to be really thoughtful about cognitive health and fitness” – there’s a need to “make sure that our employees aren’t making too many decisions per day”, and that requires “thinking about what is on their mental plate” and protecting their mental wellbeing.

A final call to action from BCG’s data is for HR leaders to shift the organizational AI mindset from the individual to the collective.

Not only did the risk of brain fry reduce when teams worked together, helped each other, and AI tools were embedded in team processes and workflows, but productivity also went up. The productivity benefits of collective AI use was also picked up by Jaime Teevan, Chief Scientist at Microsoft, during her UNLEASH America keynote.

Kellerman asks: “How do we help organizations come together to understand that this is not a competitive opportunity, this is about collective growth?”

The answer is for HR to really empower and upskill managers. For Kellerman, the most important thing that managers can do is to “help the individuals on their team feel supported through this transition”.

Now is the time for HR to focus on the “new leadership capabilities that we need” – “a really pivotal question today is what does leadership look like in that AI-first reality?”