Invisible AI, visible costs

These findings align with our own recent research on AI use at work. In a representative survey of 32,352 workers across 47 countries, we found complacent over-reliance on AI and covert use of the technology are common.

While many employees in our study reported improvements in efficiency or innovation, more than a quarter said AI had increased workload, pressure, and time on mundane tasks. Half said they use AI instead of collaborating with colleagues, raising concerns that collaboration will suffer.

Making matters worse, many employees hide their AI use; 61% avoided revealing when they had used AI and 55% passed off AI-generated material as their own. This lack of transparency makes it challenging to identify and correct AI-driven errors.

What you can do to reduce workslop

Without guidance, AI can generate low-value, error-prone work that creates busywork for others. So, how can we curb workslop to better realise AI’s benefits?

If you’re an employee, three simple steps can help.

1. start by asking, “Is AI the best way to do this task?”. Our research suggests this is a question many users skip. If you can’t explain or defend the output, don’t use it

2. if you proceed, verify and work with AI output like an editor; check facts, test code, and tailor output to the context and audience

3. when the stakes are high, be transparent about how you used AI and what you checked to signal rigour and avoid being perceived as incompetent or untrustworthy.

What employers can do

For employers, investing in governance, AI literacy, and human-AI collaboration skills is key.

Employers need to provide employees with clear guidelines and guardrails on effective use, spelling out when AI is and is not appropriate.

That means forming an AI strategy, identifying where AI will have the highest value, being clear about who is responsible for what, and tracking outcomes. Done well, this reduces risk and downstream rework from workslop.

Because workslop comes from how people use AI – not as an inevitable consequence of the tools themselves – governance only works when it shapes everyday behaviours. That requires organisations to build AI literacy alongside policies and controls.

Organisations must work to close the AI literacy gap. Our research shows that AI literacy and training are associated with more critical AI engagement and fewer errors, yet less than half of employees report receiving any training or policy guidance.

Employees need the skills to use AI selectively, accountably and collaboratively. Teaching them when to use AI, how to do so effectively and responsibly, and how to verify AI output before circulating it can reduce workslop.