Leaders have precise insights for every department. Why not for AI capability, and the barriers to adoption?

Ask a finance director where the business stands on cash and you will get a number, to the penny. Ask a sales director about the pipeline and you will get it by the week.

Now ask the Board what their people can do with AI. Most can’t tell you very precisely. That matters, because companies are spending heavily on AI tools without knowing whether their teams can use them. Our latest data shows what the gap costs.

The numbers: 28 working days lost per worker

Our annual Skills Intelligence data, drawn from 6,690 workers this year, shows British workers now lose an average of 28 working days a year to inefficient work with data. That is almost six weeks. It has risen for the third year running:

• 25 days in 2024
• 27 days in 2025
• 28 days in 2026

We estimate this costs the UK economy £53.37 billion a year in lost productivity, based on the self-reported proportion of the working week spent inefficiently on data, and multiplied by the 8.1 million knowledge workers most affected. The findings arrive two weeks before a Budget that bets on AI lifting productivity: our data suggests the workforce is not yet equipped to deliver that.

The appetite is there. The training isn’t.

Workers want to learn:

• 97% of workers in our study want to improve their AI skills, up from 91% last year
• Yet three in four UK adults have never had any AI training, formal or informal (based on Focaldata polling of 1,830 UK adults, commissioned by Multiverse)

The widest gaps sit in the skills that turn AI tools into results for the business:

• Scaling AI: 80% of self-ratings for AI adoption were “a new area for me”. Just 1% ranked themselves as experts.
• Agents: among learners on our more advanced AI programme, 57% have spotted where an AI agent could help their work. Only 16% have built one.
• Strategy: 70% of self-ratings for data strategy were “a new area for me”, twice the rate for data governance (35%).

There are signs of progress: healthcare cut the share of data time its workers spend inefficiently from 41% to 35%, the biggest improvement of any sector. But financial services and councils moved the other way.

Why employers can’t see the gap

A traditional skills audit usually means a survey that not everyone finishes and a spreadsheet that is out of date before anyone reads it. So leaders have to guess, and what’s missing goes beyond skills - skills can’t fix a procurement problem, or the silos between teams that mean the same thing is being developed in two different places.

That is the problem our voice agent is built to fix. It lets workers pinpoint what is blocking them, and leaders hear it played back. Each employee has a short conversation with the agent, by voice or chat, about their actual job and how they use data and AI. The agent identifies their skills gaps against our skills framework, built on insights from more than 40,000 assessments, and gives each person a view of where to build skills next.

These insights are then anonymised, aggregated and played back, so leaders can see the full picture across a team or the whole organisation, and tell what needs to progress to unlock AI adoption, and why. The technology was developed in our newly opened Edinburgh AI Hub.

Jay Richman, our Chief Product and Technology Officer, said: “Every working week holds an honest account of what's slowing a business down, but most companies never hear it. The agent listens to every person, finds the hours lost and the tools left unused, and plays it back across the whole organisation. That means that leaders can stop guessing where to invest and start knowing.”

Questions every leader should be able to answer

Euan Blair, our founder and CEO, said: “Workers have far greater context on their workplace challenges than anyone else, but until now that rich seam of intelligence has never properly been surfaced. We want to give employers visibility, and workers the opportunity to explain the challenges they’re facing.”

Start with these:

• Where are our people losing time, and what’s blocking them? If you can’t name the teams or the tasks, you can’t fix the problem.
• Which skills do I need to build within my team? Being able to use a tool and being able to roll it out across a team are different skills. You need to know where the gaps are.
• How would we know if it’s working? If the answer is course completions, that measures activity, not evidence.

See your own skills picture

If you want to know what your people can do with AI, talk to Sales and we will show you how it all works.

Frequently asked questions

How many days a year do UK workers lose to inefficient data work?

UK workers lose an average of 28 working days a year to inefficient work with data, almost six working weeks. That’s up from 27 days in 2025 and 25 in 2024. The figure comes from Multiverse’s Skills Intelligence data from 6,690 workers and is based on self-reported hours.

How much do poor data skills cost the UK economy?

Poor data skills cost the UK economy an estimated £53.37 billion a year in lost productivity, according to Multiverse. The estimate is based on self-reported time lost and covers the 8.1 million knowledge workers most affected.

Do UK employees want AI training?

Yes. 97% of workers in Multiverse’s study want to improve their AI skills, up from 91% last year. Yet three in four UK adults have never had any AI training, according to Focaldata polling of 1,830 UK adults commissioned by Multiverse.

What AI skills are UK workers lacking?

The widest gaps are in scaling AI, building AI agents and data strategy. In Multiverse’s data, 80% of self-ratings for AI adoption were “a new area for me”. Among learners on its more advanced AI programme, 57% have spotted where an AI agent could help but only 16% have built one. 70% of data strategy self-ratings were “a new area for me”, twice the rate for data governance (35%).

How does Multiverse’s voice agent work?

Multiverse’s conversational AI voice agent has a short conversation with each employee, by voice or chat, about their actual job, what’s costing them time, and how they use data and AI. It identifies their skills gaps against Multiverse’s skills framework, built on insights from more than 40,000 assessments, and gives each person a view of where to build skills next. The insights are then anonymised and aggregated, so leaders can see what is holding their teams back and where to invest their time.

What do employers get from the agent?

Employers see anonymised, aggregated results across a team or the whole organisation, so they can tell where AI adoption needs to progress and why.

How do I measure my team’s AI skills?

Start with three questions. Where are our people losing time, and what’s blocking them? Which skills do I need to build within my team, and where are the gaps? How would we know if it’s working? If the answer to the last one is course completions, that measures activity, not evidence. Multiverse’s conversational AI voice agent, gives leaders a clearer picture of where help is needed most.