The backlash against artificial intelligence continues to intensify. What was once heralded as a clever shortcut to automate routine tasks is now being recognized as a potential drag on performance. A recent study by resume services platform Zety, known as the Workslop Trust Report, found that 51% of US professionals say AI-generated content — or 'workslop' — has actually reduced their productivity. An additional 45% said workslop made them more cautious about using AI at work.

Workslop is defined in the report as AI-generated work that appears polished on the surface but lacks accuracy, substance, or human oversight. The consequences go beyond mere annoyance: 57% of respondents cited lower trust in AI, 51% reported reduced productivity, and 46% worried about damage to their company's reputation.

These findings present a paradox. Generative AI and agentic technologies were supposed to make workers more efficient. Yet, without proper governance and human judgment, the technology can backfire. Jasmine Escalera, a career expert at Zety, noted that the research reveals an uncomfortable reality: 'AI is reshaping how work gets done, but not always for the better.'

So what can professionals do to ensure AI becomes an asset rather than a liability? Business leaders from Thomson Reuters, Ricoh Europe, and Segro suggest two fundamental steps: rethink productivity and be persistent.

Rethinking productivity

Joel Hron, CTO at Thomson Reuters, emphasizes that adopting an 'AI-first' mindset is essential. This approach flips the traditional workflow: instead of humans doing the heavy lifting and AI assisting, professionals should let AI handle the initial draft or computation, then apply human judgment and intuition on top. Hron explains that his organization has seen this pattern gain traction, particularly in software engineering. 'An AI-first mindset means looking at every task and asking, "How do I get AI to do this first, so I can come in second with a higher layer of judgment or intuition?"'

This shift foreshadows similar transitions across other roles. The professionals who will thrive, according to Nick Pearson, CIO at Ricoh Europe, are those who take a sophisticated approach to measuring AI's value. Ricoh has built an internal AI marketplace where employees select tools, but each tool is evaluated against multiple vectors: business risk, financial return, and actual time saved. 'The model asks, "Does this thing help or not? Does it really save hours or days? Where does AI save this time?" If the output is just meeting notes that nobody reads, that's not adding value,' says Pearson.

Richard Corbridge, CIO at property specialist Segro, adds that success depends on creating a learning culture where employees understand both the risks of workslop and the genuine opportunities. 'Let's use AI as a tool to help educated, experienced colleagues. We make sure the workslop element is really understood and that if you don't use this tool wisely, the risks are much higher.' Corbridge advocates identifying what AI cannot do — such as inspire people or create genuinely novel ideas — and reserving those tasks for humans.

Being persistent

Implementing AI is only the starting point. Real productivity gains require sustained effort. Hron points out that at Thomson Reuters, some employees initially dismissed AI tools because the first attempts didn't deliver perfect results. 'When people just said AI wasn't ready and turned it off, they missed the mark,' he explains. The teams that succeeded were those who persisted: building systems around the AI, grounding it with context, and guiding it toward reliable outputs. Hron describes a pattern where one hyper-curious individual often does the heavy lifting, and the entire team eventually benefits from that investment.

Pearson notes that persistent professionals who master the blend of AI and human expertise will become highly sought after — and will also demand better tools from their employers. 'An employee experience is bubbling where people are saying that these are the tools and capabilities I expect to have in a company.' Companies that fail to provide effective AI tools may lose top talent to competitors that offer sophisticated, well-governed AI assistants.

Corbridge reinforces that persistence pays off because AI is not a passing trend. Despite occasional debates about a bubble, he believes the technology is here to stay. 'There's a lot of debate about when the AI bubble is going to burst. I'm not convinced. I think it's here to stay. AI isn't going to go away.' The key is for professionals to engage deeply with the technology, learn its limitations, and continuously refine their approach.

For organizations, the challenge is to strike the right balance between risk and reward. Pearson warns that employees who have experienced effective AI agents in one workplace will expect the same capabilities elsewhere. This creates a competitive pressure for companies to invest in AI literacy, governance frameworks, and user-friendly tools. Those that ignore the workslop problem risk not only a productivity hit but also a talent drain.

The path forward is clear: stop treating AI output as a finished product. Instead, treat it as a first draft that requires human judgment. Rethink what productivity means — not just speed of generation, but quality and insight. And be persistent. The organizations and individuals who invest the time to build robust systems around AI will unlock exponential gains, while those who abandon the tool after its first failure will be left behind.

As the Workslop Trust Report shows, 51% of professionals are already feeling the productivity drain. But with deliberate action, that figure can become a catalyst for change rather than a permanent liability.

Source: ZDNET News