AI is already embedded in how UK businesses operate. But training has not kept pace. New research with over 2,000 UK tech workers shows where the gaps are and what organisations need to do now. 

The training gap no one is addressing

92% of UK tech workers now use AI in their roles. But a significant portion of the workforce has received no formal training in how to use it. 

Percentage who have received NO AI training:

  • Entry-level staff: 26% 
  • Intermediate staff: 34% 
  • Middle management: 17% 
  • Senior management: 14% 
  • Directors: 10% 
  • C-suite: 6% 

The pattern is clear. The more senior you are, the more likely you are to have been trained. The people closest to the day-to-day work are the least supported. 

The consequences are already showing

Without proper training, people make mistakes. And most are not checking their work. 

Only 37% of UK tech workers always verify AI outputs before using them. 

That means the majority are acting on AI-generated content, analysis, or recommendations without consistently checking whether it is accurate. When training does not teach people to question AI, errors get embedded, repeated, and scaled. 

The impact is measurable: 

  • 67% of tech workers have seen AI cause a mistake at their company 
  • 29% of C-suite report serious business impact from AI errors 
  • 32% of entry-level staff report serious business impact 

Junior staff are less likely to engage in risky AI behaviours. But when errors happen at the front line, the consequences can still be severe. 

Why people are anxious

Half of UK tech workers expect AI to lead to job losses at their company within three years. 

That anxiety is not irrational. But it is often misdirected. 

The threat is not that AI will replace people. It is that people without AI skills will be replaced by people with them. The question for every organisation is whether they will develop that capability internally or lose talent to competitors who will. 

Where to focus first

Closing the AI skills gap requires a structured approach. Based on our research, these are the priorities:

  1. Make training mandatory, not optional

Voluntary uptake creates uneven capability. The organisations seeing results are those making AI training a requirement, not a perk. 

  1. Tailor training by role

Generic AI awareness sessions are not enough. People need practical, role-based training that shows them how to use AI in their specific context. 

  1. Teach verification as a core skill

Every AI training programme should include how to check, question, and validate outputs. If people do not know when AI is wrong, they cannot catch mistakes. 

  1. Do not forget middle management

17% of middle managers have received no AI training. These are the people translating strategy into action. If they are not equipped, adoption stalls. 

  1. Invest in upskilling, not redundancy

The skills gap is real. But for most roles, the answer is development, not replacement. Organisations that upskill their existing workforce will retain knowledge, loyalty, and capability that takes years to rebuild. 

Take the next step

The gap is clear. The question is what you do about it.

La Fosse Academy works with organisations to build real AI capability, through structured upskilling programmes for your existing workforce and AI-enhanced apprenticeships that develop deep, role-based skills over time.

Whether you want to bring your team up to speed quickly or build long-term capability through a funded apprenticeship programme, we can help you work out the right approach.

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Read the full research

This article draws on findings from AI in the Workforce: The Hidden Risk for UK Businesses, our independent research with over 2,000 UK tech workers.

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