40% of AI-generated content is 'workslop', and it drives over $9 million in lost productivity annually, finds BetterUp

AI is undoubtedly improving worker productivity, but organizations as a whole are struggling to reap the rewards from the technology.

The issue is that many companies have “indiscriminate AI mandates, when leaders encourage people to ‘use AI everywhere’ without clear guidance”, as Jeff Hancock, Director, Stanford Social Media Lab, and Professor at Stanford University, exclusively shares with UNLEASH.

This means that much of the content produced by AI is bad quality and unhelpful; in fact, a survey of 1,000 US workers by Stanford Social Media Lab & BetterUp calls this ‘workslop’.

“While it may look good on the surface, workslop is often bloated, confusing, or just plain wrong”, which “ends up creating more work for their co-workers”, according to the report.

40% of those surveyed believe they have received workslop in the past month, they estimate that 15.4% of what they receive from others is workslop, and 53% admit that at least some of the work they send may be workslop.

Workslop is more than just annoying, it has “significant financial, workforce, and culture implications”, Hancock tells UNLEASH.

Workers surveyed said they spent almost 2 hours dealing with each instance of workslop.

This wasted effort equates to almost $186 per month per employee; for an organization of 10,000 employees, this equates to over $9 million in lost productivity every year.

Hancock adds: “Beyond wasted time, it strains team dynamics: employees receiving workslop are annoyed and perceive colleagues as less capable, creative, or trustworthy, and are less likely to want to work with them again.

“That erosion of trust and collaboration, combined with productivity losses, makes workslop a hindrance to realizing AI’s full ROI.”

The data shows that when employees receive workslop they feel annoyed (54%), frustrated (46%), confused (38%) and offended (22%).

“AI may also exacerbate the volume of sloppy work colleagues have to deal with, and if employees see low-quality AI outputs being accepted or overlooked, it lowers the standard for everyone, weighing down workers, teams and the organization at large,” adds Hancock.

So, what’s the solution? How can organizations ensure AI use isn’t leading to workslop?

Be ‘pilots’ not ‘passengers’ to reap the rewards of AI

As Hancock establishes, indiscriminate AI mandates are a major cause of workslop – that approach “models poor discernment, and employees mirror it”.

In contrast, “organizations that set thoughtful guardrails, define use cases, and reinforce human judgment are far less likely to experience workslop”.In contrast, “organizations that set thoughtful guardrails, define use cases, and reinforce human judgment are far less likely to experience workslop”.

However, previous BetterUp and Stanford research that studied 12,000 workers also shows that employee mindsets have a role to play.

That data found that in the age of AI, there are two types of workers – ‘Pilots’ and ‘Passengers’.

Hancock shares: “Our research identifies ‘Pilots’—those with high agency and optimism—who use AI to boost creativity and impact, versus ‘Passengers’, who may have fear or reluctance towards AI and may only rely on it to cut corners.”

Ultimately, ‘Pilots’ are more confident with AI, and they use it more purposefully, which leads to them being 3.6x times more productive.

By setting clear expectations, building optimism and agency, and modeling responsible use, leaders can ensure AI enhances creativity and collaboration rather than replacing meaningful work,” concludes Hancock.By setting clear expectations, building optimism and agency, and modeling responsible use, leaders can ensure AI enhances creativity and collaboration rather than replacing meaningful work,” concludes Hancock.