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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteSome UK senior leaders may be overstating how much they know about AI, according to research by Emergn reported by TechRadar. The figure is a warning about possible gaps between confidence and competence—not evidence that any particular boss is pretending.
What the reported 23% figure does—and doesn’t—say
TechRadar reported on October 3, 2026, that Emergn research found 23% of UK senior leaders may be bluffing about their AI knowledge. The underlying survey report, including its sample size, field dates and exact question wording, was not available in the reporting. Treat the figure as a reported survey result, not a verified estimate of how many individual managers are knowingly misrepresenting their skills.
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“Bluffing” also need not mean deliberate deception. A leader might speak confidently about AI while having only a broad, non-technical grasp of it—or might struggle to distinguish familiarity with AI tools from the ability to assess their risks and uses. The reported figure does not tell us which interpretation respondents had in mind.
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Career pressure and training sit alongside the knowledge gap
The same Emergn findings, as reported by TechRadar, point to pressure around AI skills: 38% of respondents said their career prospects could suffer unless they significantly improved their AI skills in the coming year. Another 22% felt anxious or lost sleep because AI was changing their industry quickly, while 22% felt out of their depth because of AI’s impact on their role.
At the same time, 43% said they had received substantial AI training in the previous 12 months. That leaves a more complicated picture than simple ignorance: leaders may be under pressure to keep up, but the reported results do not establish whether training was adequate, what it covered, or whether career anxiety caused anyone to overstate their knowledge.
Other surveys suggest uneven workplace readiness, not proof of bluffing
Separate evidence from UK employers offers context, but measures different things. A UK government employer survey found that, among employers using or planning to use AI, 43% rated their business’s AI knowledge as intermediate or above, while 56% rated it beginner or novice. Only 36% rated senior leadership’s understanding of AI use in their industry as good, and 34% rated leaders’ ability to identify new AI opportunities as good. These employer assessments indicate uneven readiness; they do not independently confirm the Emergn figure about leaders overstating their knowledge.
Gallup reported a different organizational perspective in 2026. In a survey of 102 CHROs in its Global CHRO Roundtable, 50% were not very or not at all confident in managers’ ability to guide employees’ AI use, while 57% said their organizations were providing AI training for people managers. This is not a UK-specific result, and the respondents were CHROs rather than senior leaders describing their own knowledge.
These percentages should not be treated as directly comparable: one set concerns leaders’ reported training and feelings, another employers’ ratings of organizational knowledge and leadership understanding, and Gallup’s figures reflect CHROs’ confidence in managers. The UK government also cautions that its survey of the general public was a separate study, so those results indicate trends or differences rather than a direct comparison with the employer findings.
How to tell whether a manager understands AI well enough
A manager does not need to build AI systems or know every technical detail to lead responsibly. The practical test is whether they can make informed decisions about where AI might help, where it could cause harm, and when specialist advice is needed. Useful signs include whether they can:
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- Explain the specific work problem an AI tool is meant to solve, rather than promoting AI as a goal by itself.
- Ask how outputs will be checked, who is accountable for errors, and what data the tool uses.
- Recognize that a tool’s confident-sounding answer may still be wrong or unsuitable for a consequential decision.
- Involve people who understand the relevant technical, legal, privacy or security risks when those issues arise.
- Say what they do not know and support role-relevant training before asking employees to rely on a tool.
These are practical indicators, not a diagnostic test for dishonesty. Someone can be new to AI and still lead well if they are candid, curious and careful; confident claims without clear reasoning deserve follow-up, not an assumption of bad faith.
What employees can do when AI claims sound overstated
Ask for specifics without turning the conversation into a confrontation. For example: “Which task do you think this tool will improve, and how will we check whether it works?” or “What data can we enter, and who reviews its output?” A leader who can discuss assumptions, limits and safeguards is demonstrating useful judgment even if they are not an AI specialist.
If the answers remain vague, propose a small, low-risk trial with a clear owner and a way to review results. Keep sensitive or confidential information out of unapproved tools, and follow your organization’s policies. For high-impact decisions, ask for qualified review rather than relying on a manager’s confidence alone.
The most useful signal is not whether a boss uses AI jargon. It is whether they can connect a tool to a real need, acknowledge uncertainty, and create a responsible process for checking its use.
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