An NHS worker used data modelling to cut an assessment waiting list from 25 patients to one. A council employee built an AI tool that flags illegal landlord eviction notices on the spot. A retail assistant created a stock-out alert system saving hundreds of thousands in lost revenue. None of them had a computer science degree. None of them were new hires. All of them did this during an apprenticeship.
Before Multiverse, what was the alternative for a 42-year-old whose role is being automated? An evening course? A YouTube tutorial? In too many cases, the answer was nothing at all.
I started Multiverse nearly ten years ago because I saw an acute problem: a huge gulf between the skills workers had and the skills the economy needed. Ten years on, that problem has got harder. Employer investment in training has fallen by nearly £10 billion in real terms. Hundreds of thousands of vacancies in the NHS, social work and teaching go unfilled. More than a quarter of all employer vacancies are skills-related. And now we face something genuinely existential: AI-driven displacement that will impact every worker, in every sector.
The OBR's March 2026 forecast shows a £90 billion swing in public borrowing depending on whether productivity improves - and names AI adoption as a key factor. UK output per person has flatlined since 2019. The cost of inaction is not abstract.
Last year, Multiverse accounted for more than half of all growth in apprenticeship starts across the entire system. That growth brings responsibility, and accountability where we fall short. So let me be direct about both.
On completion rates: ours are too low, and I want them higher. Our last published QAR (the government gathered metric for completion) sits at 52.6%. Our highest-level programmes complete at c.70%, our software developer programmes complete above 80%, and our data degree apprenticeship has topped the National Student Survey for satisfaction two years running. The gap elsewhere reflects deliberate choices that I stand behind, with caveats.
For our AI programmes, we chose an inclusive approach to enrolment. Employers asked us to reach frontline workers - the people who typically get passed over for formal training. The result is a 50/50 gender split on our two biggest AI programmes and genuine reach across the country. That approach comes with a real tradeoff on completion, but even among those who withdraw, 70% have already generated measurable value for their employer. One of our NHS apprentices reduced missed appointments in a hospital department by 30%. A pay rise or promotion during or after the programme is the majority outcome for our learners.
We also hit friction because the regulated apprenticeship system hadn't caught up with AI. The release of the first general purpose AI apprenticeship is now imminent; but nearly four years after ChatGPT launched. The right answer was never to simply ignore AI from an apprenticeship perspective - but we paid a price in our QARs for innovating ahead of the programmatic standards available. We're working to close that gap.
On whether we take more than we give: Multiverse has put $500 million of investment capital into the skills system — the largest non-governmental investment in the skills system anywhere in the world. Our learners have driven more than £2 billion in measurable ROI for their employers. Our AI coach, Atlas, now handles 15 million queries with a 98% satisfaction rate. Since 2020, we've contributed £102 million in Income Tax and National Insurance through our employee payroll alone.
And we train apprentices aged 16 to 70. That's not a mission drift — it's the most urgent expression of our mission. The cost of a Multiverse programme is a fraction of the cost of redundancy, rehiring, and starting again from scratch. Apprenticeships for a 45-year-old facing automation and apprenticeships for an 18-year-old who can't afford university are both responses to the same broken system. We shouldn’t pit them against each other; the country needs more of both.
On growing too fast: I accept that growth creates strain, and that in regulated markets innovation creates friction. We haven't always managed that strain as well as we should. We weren't prioritising formal careers advice for experienced workers, as an example - assuming they wouldn't want it from us. The regulator sees it differently, and we're now embedding it across all programmes. Where we've created friction, we'll own it and adapt.
But the apprenticeship system's core problem is not that providers have grown too fast. It's that the system hasn't grown at all. The NHS starts c.20,000 apprentices in a workforce of 1.4 million. Its own Long Term Workforce Plan targets 22% of clinical training through apprenticeship routes by 2031. It’s only 7% today. Funds available for apprenticeships expire unused every year. Total starts remain below pre-levy levels. We employ a sales team that is unashamedly relentless in trying to persuade every employer who will listen that educating their workforce is a good thing, and that it’s a worthwhile investment to make - both for them and for their workers.
In that context, growing too fast is not the right criticism. The right question is: why isn't everyone growing faster?
We are reinvesting everything we earn into building a reskilling infrastructure that didn't exist before. We are not going to stop. There is an alarming world where workers facing automation have nowhere to turn. They deserve a pathway, and we're proof that when you build one, people will take it. The skills gap is not inevitable. The question is whether we'll move fast enough, and boldly enough, to close it. And ten years on, there’s still a lot more for us to do.
— Euan Blair
