New Worker Woe: AI Impatience

When it comes to AI, if at first you don’t succeed, it appears that the next best step is to give up and revert to the old way. 

Despite businesses’ enthusiasm for using artificial intelligence, many organizations are struggling to translate investment into real productivity gains. One reason why: A new study finds that a striking nine out of 10 AI users admit to abandoning the technology because non-AI methods were easier or delivered a better outcome. The typical AI user expects a satisfactory answer within two prompts and gives up after the fourth. People have come to expect instant gratification from technology—and swiftly become impatient when that expectation isn’t met.

“Only a small proportion of prompts truly add value,” says AJ Van Den Burg, a Korn Ferry senior client partner who advises business leaders on how to navigate disruptive change and radically transform their organizations. “Most are exploratory, some are mediocre, and a few are genuinely powerful.”

The study featured American workers, but in a recent UK government report, only a fifth of UK workers reported they find the tech productive, is also cause for concern. That’s a troubling pattern at a time when the UK is staking billions on AI in public and private investment and positioning itself as a global AI capital. British AI firms attracted roughly £2.9 billion in private funding in 2024 alone, while the government has committed significant resources through initiatives such as a £2 billion AI Action Plan and broader plans to increase public R&D spending to £22 billion annually by the end of the decade. 

Valued at more than £70 billion, the UK’s AI market is already one of the world’s largest and Europe’s leading ecosystem for the technology. But experts say the return on that investment ultimately depends on how effectively people use the tools day-to-day. If employees disengage too quickly, the UK could underdeliver on its ambitions to lead both in AI innovation and AI adoption. One major reason people aren’t getting the results they want from the technology is that they aren’t taking the time up-front to refine and optimize prompts. 

The average user in the US study performed poorly on prompting, scoring 57 out of 100. Common mistakes included failing to specify tone or style, not asking for outputs to be challenged or justified, and not identifying a target audience. “Working with AI is an ongoing process,” says Drew Hill, a London-based Korn Ferry senior client partner who focuses on helping leaders accelerate revenue growth, build risk intelligence, and manage succession planning. He says people using AI understand what it can and cannot do, and how some AI tools, depending on what you want to achieve, are better than others. That’s where corporate culture—and a fail-to-learn mindset—come into play, says Bryan Ackermann, head of AI strategy and transformation at Korn Ferry. “Working with AI effectively is a process,” he says. 

In the UK, where organizations are under pressure to boost productivity and justify digital investment, building that capability at scale is critical. There are practical ways to reduce frustration. One simple step is to ask AI itself to review and refine prompts—yet fewer than half of users in the study tried that approach. Organizations can also identify what works and share it widely enough that the benefits eventually outweigh the time required for learning. Moreover, even when the issue lies with the tool rather than the user, rapid advances mean yesterday’s failed prompt may work today. 

Instead of abandoning unsuccessful tasks, AI users should keep going, says Emma Cornwall, a Korn Ferry senior client partner and solution lead for leadership and professional development in the UK and Ireland. “Keep exploring,” she says. “Those who aren’t put off are putting their back into learning and gaining new skills.”

Shanda Mints, Korn Ferry vice president for AI strategy and transformation, suggests maintaining a “not yet” list and revisiting it regularly. “In practice, you may try ten things and only get real value from two of them,” she says. “The difference is what happens next.” For the UK, that know-how could make a decisive difference. For the UK, achieving its ambition of becoming a global AI leader will depend not just on investment and policy, but also on whether people persist long enough to unlock the technology’s potential. 

Learn more about Korn Ferry’s Organizational Strategy capabilities. 

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