
As AI rapidly transforms the modern workplace, employees must move beyond learning how to operate AI tools and develop critical thinking skills required to challenge its outputs, according to a leading education charity.
Data from the Office for National Statistics shows that workplace AI adoption across the UK has accelerated significantly, with the proportion of businesses employing 10 or more people using AI nearly tripling from around 12% in late 2023 to 35%.
Furthermore, ONS figures reveal that 55% of employed and self-employed individuals now use AI for work or education. Yet only 11% of businesses report that more than half of their workforce has received formal AI training.
Gray Mytton, Assessment Innovation Manager at education charity NCFE, warns that as the technology becomes deeply embedded across industries, true AI literacy must encompass scepticism, judgement and oversight.
“Workers need to be able to challenge what AI gives them, interpret the information and decide whether it is accurate and appropriate,” Mytton said.
“That means technical familiarity with AI needs to sit alongside skills such as critical thinking and judgement. We need to develop those skills together rather than treating them as separate things.”
Mytton’s remarks coincide with the launch of NCFE’s two new Level 2 qualifications in Artificial Intelligence for the Workplace, which focus heavily on AI literacy, ethical use and critical evaluation.
This emphasis aligns with Skills England’s 2026 AI foundation skills benchmark, which stresses that employees must understand the risks of the technology and know when to rely on their own independent human judgement.
While AI is automating routine tasks and driving productivity, experts emphasise that human oversight remains irreplaceable. Mytton notes that helping workers build practical experience, curiosity and adaptability will be vital for navigating a shifting job market, ensuring employees are equipped to manage technology responsibly, rather than accepting automated outputs at face value.
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