- Only 2% of workers say AI-generated content needs no revision
- Workers are spending hours every week cleaning up “AI workslop”
- AI training should be compulsory, and processes should be standardized
Despite the perceived productivity benefits, many businesses are spending time and money cleaning up “AI workslop,” suggesting the tech generates a lot of unnecessary noise, new research has claimed.
Data analysis and visualizations (55%), research and fact-finding (52%), long-form reporting (52%) and writing and marketing content (44-46%) are some of the most common areas where AI tools might not be as effective as companies once hoped.
Even though 92% agree AI improves their overall productivity, only 2% say that AI outputs need no revision.
AI is a noisy way to productivity
Three in five (58%) spend more than three hours per week revising outputs, with more than one-third (35%) spending more than five hours and 11% spending over 10 hours every week tidying up generated content.
The research from Zapier adds that AI generally lacks accuracy, context or usefulness despite appearing polished on the surface.
And it’s not just perception that’s down – many have experienced rejected work (28%), security or privacy incidents (27%), customer complaints (25%) and compliance or legal issues (24%).
Zapier’s data indicates two potential solutions – firstly, AI models must continue to be improved to improve the quality of responses. But in the meantime, workers should be upskilled to handle AI in its current format, and not what it should be.
“The companies seeing the best results aren’t the ones avoiding AI,” Senior AI Automation Engineer Emily Mabie explained. “They’re the ones who have invested in training, context, and orchestration tools that turn AI from a sloppy experiment into a managed process.”
Nearly all (94%) of trained workers say AI boosts productivity, but only 69% of untrained workers agree. As a result, only 1% of trained workers say their productivity has dipped.
Looking ahead, the report calls for AI training to be compulsory for all workers that handle it, prioritizing high-risk teams and tasks in the first instance. Companies can also help employees by providing prompt templates and formalizing reviewing processes.
“The solution isn’t fewer tools, it’s better infrastructure,” Mabie concluded.
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