Tired of “AI slop”?Learning scientists at AI skills platform Multiverse suggest a solution: employees who proactively reshape their roles around AI—rather than just using it to speed through tasks—show higher engagement, motivation, and creativity at work. Multiverse’s June–July study surveyed 295 UK full-time professionals across finance, government, and tech sectors, all with at least six months of generative AI experience. It found that those who “job craft” by redesigning tasks and workflows to integrate AI demonstrate significantly greater engagement compared to passive users. Barry Goulding, an organizational psychologist at Multiverse, explains that job crafting involves reexamining and reshaping job components to improve task execution—shifting from “this is my job” to “this is how I can do my job better. ” The team views “AI slop, ” the flood of low-quality, generic AI output, not as a technology flaw but as a sign of employee disengagement. Goulding notes that merely copy-pasting AI-generated reports without review reflects low engagement and poor collaboration with AI tools. Conversely, job crafters critically evaluate AI output, catch errors, and ensure high-quality results. Training employees to think critically about AI’s fit in their roles can thus reduce sloppy work and boost output quality. The research challenges the common belief that AI diminishes cognitive engagement. While some studies suggest AI use can reduce deep thinking, Multiverse’s data shows that intentional AI use actually increases focus and dedication. Goulding emphasizes that if AI is used for low-effort automation, cognitive and employee engagement drop.

However, when employees actively and purposefully integrate AI into their jobs, their absorption, dedication, and vigor—key engagement factors—rise. For example, a customer service manager might use AI not just to handle tickets but to analyze trends and recommend improvements, sparking greater work engagement. To unlock these benefits, Goulding argues AI adoption must go beyond tool rollout. Simply distributing AI licenses without training leads to low-quality output, poor engagement, and minimal productivity gains. Instead, AI strategies should embed training, measure outcomes, and allow employee experimentation. Leadership plays a vital role by setting expectations, modelling behavior, and empowering staff to reshape roles within guardrails. Goulding cites Capita, which made AI adoption a strategic effort; after training, one employee created an “Ask Me Anything” assistant that handled over 70, 000 company queries. Rather than measuring job crafting itself, leaders should focus on the outcomes it drives—such as improved productivity and higher engagement scores—as tracking behaviors alone misses the point. Training employees to use AI effectively fosters curiosity, problem-solving, and quality collaboration with the technology. Goulding believes job crafting will soon be a fundamental skill in the AI era: “AI will change how we all work. Those who take control will succeed faster and bigger, with benefits multiplying across organizations when such behaviors are embedded through tech training. ”