The Multiverse blog

Until recently, Gemma spent a large part of her day sorting through goods from corporate donations and listing them on eBay. As an eBay Administrator for Age UK, Gemma plays a key role in raising funds for the charity’s work including services like its Telephone Friendship Service, free and confidential Advice Line and The Silver Line Helpline.

“We work with companies like Amazon that donate large quantities of items,” Gemma explains. “It can be anything, from skincare products to furniture.” All profits go directly back to Age UK’s important work.

But keeping up with demand was a grind. Between researching unfamiliar products, crafting accurate descriptions, and finding the right keywords to drive visibility, listing 25-30 items could take up to two and a half hours per day on average - taking away from her other duties managing the donations warehouse.

The variety of donations made things even trickier. “I’m not an expert on many of the items listed, so I would often have to frantically Google to make sure descriptions are accurate,” Gemma says. Specialist items were a particular challenge: “If it’s something like a car part, that takes a lot more time - I’ve got to make sure it’s the right thing.”

So Gemma decided to build a smarter way of working, leveraging her new AI skills. Using Microsoft Copilot to craft her prompts, she set up a ChatGPT Enterprise tool and fed it eBay’s best practice and tone of voice guidelines, giving every listing the best possible chance of a sale. “Copilot helped me write the prompt,” she explains, “and then I went through about three or four iterations before I got to the one I use now.”

The workflow is now remarkably simple. Gemma submits an item’s barcode to the tool, and within seconds ChatGPT pulls product information from across the internet and generates a polished title, description, and recommended price. It doesn’t matter how obscure the product is - the output is consistently accurate, and Gemma only needs a quick check before each listing goes live. “The stuff that I won’t know about, the internet will,” she jokes. “So it’s definitely made it easier.”

The impact has been significant. Time spent researching and writing each listing has dropped from 10-15 minutes to around five - and that freed-up time goes straight back into managing the warehouse. The team has also been able to add five more listings per day, boosting their inventory and the charity’s prominence on the platform. “The more things you have listed, the more sales you get,” Gemma notes. “Essentially, it bumps you up in visibility on eBay.”

Better listings have also reduced the number of customer questions Gemma has to field. When product descriptions are clear and detailed, buyers already have the information they need - another small win that adds up over the course of a busy day.

For Gemma, the bottom line is straightforward. AI-optimised listings are driving more revenue for Age UK, and giving her valuable time back for other work. “In the long run,” she concludes, “it is going to make more money for our department, the charity, and ultimately help the people we support.”

On 1 August, several changes to Apprenticeship Levy funding come into effect. Most People and Talent teams know the changes are coming. What's less well understood is what they mean collectively for organisations trying to plan launches confidently in the months ahead.

The three changes that matter most for Levy-paying employers

Funds will expire faster

From August, new funds entering your levy pot expire after 12 months rather than 24. Funds already in your account before August keep their existing window, so from August, you'll have two parallel expiry tracks running simultaneously. Older funds on 24 months, newer funds on 12.

Think of it like a wallet full of gift cards, all loaded at different times, all looking identical. But from August, some expire twice as fast as others. The balance looks the same. The urgency isn't.

The Digital Apprenticeship Service automatically spends your oldest funds first, so staying active and launching regularly is your best protection against expiry. The complexity comes when you're not sure how much you have, or whether your current launch pace is enough to keep ahead of it.

The 10% government top-up is being removed

Currently, the government adds 10% to every pound entering your account. From August that stops. A small but real reduction in what you have available to spend each month.

Co-investment rises from 5% to 25%

If your Levy pot runs out and you want to continue launching learners, the employer co-investment contribution rises from 5% to 25% for any new learners launched from August onwards. This is not retroactive. Anyone already on the programme stays at 5%. But for new cohorts, the cost of overspending is significantly higher than before.

What this means for your planning

These changes mean timing matters more than ever. Your monthly contributions remain the same, but with the government top-up reducing, funds expiring faster, and co-investment more costly if you overspend, the gap between organisations who know their Levy position and those who don't is about to get a lot wider.

Do you know where yours stands?

Earlier this month we announced the opening of Multiverse's new tech hub in Edinburgh, Scotland — and the leader who will build it. Colin Mackenzie joins as VP of AI Engineering, bringing a career that spans race car mechanics, professional magic, and building frontier AI systems at Amazon. 

We sat down with him in his first weeks to hear about the journey that led him here, what he believes AI is doing to the engineering profession, and what he hopes to build in Edinburgh.

Tell us about yourself. You've had quite a career path…

It's been a relatively non-traditional journey. I started out as a mechanic and performance tuner, building Japanese race cars, later pivoting into being a full-time magician, picking pockets and hypnotising people around the world. A final pivot into tech saw me work across start ups, fintech and latterly at Amazon building out the generative AI products.

The thread through them all is engineering: mechanical, social, and software. They all require systems thinking, problem solving, and figuring out how to innovate.

The last chapter moved extraordinarily fast. Working with the team at Amazon, we were building frontier AI systems in ads before the generative AI wave really hit. Every technology shift I'd seen in the past few decades, I've experienced ten times over in the last two or three. It's been quite a ride.

AI is changing what's possible in engineering at pace. What's your take?

The biggest shift is the collapsing of roles. Traditionally, there were clear boundaries between designers, product managers and engineers, and a well-worn process for passing work between them. AI is dissolving and reimagining all of that.

Knowledge is no longer a moat. If you deeply understand how to build systems, AI now gives you the ability to think more like a product person, ask better customer questions, and experiment with design. And the inverse is true: a designer, with solid systems thinking, can now build scalable products they couldn't before. The people who will thrive are the ones curious enough to explore at those edges.

The cycle time has collapsed too. We used to talk about two-week sprints. Now you can ship new features on a daily basis, get real customer feedback, and iterate the same day again. If we can set ourselves up to move at that speed, we can build something genuinely differentiated.

If anyone tells you they're a generative AI expert, take that with a pinch of salt. The technology changes week in, week out. The only honest posture is a beginner's mindset. Keep being curious, keep pushing, don't stagnate.

You’ve spoken about building a learning organisation within a learning organisation. What does that mean to you?

I came up through a traditional apprenticeship as a mechanic. I was paired with a journeyman — an expert who taught me everything they could. I had two or three of those over the course of that career, and I absorbed the best of what each of them had to offer.

There's a trend in the market right now that worries me: the idea that AI can replace junior engineers, so companies stop hiring them. But if we stop training the next generation, we lose the pipeline of people who will eventually become the experts. We need to operate like a learning factory. Knowledge might be freely accessible now, but only experience teaches you how to apply it thoughtfully. Creating an environment to disseminate the hard-won experience of tenured engineers into the people earlier in their careers, in a structured, thoughtful way, is critical. 

And it doesn't only apply to juniors. An exec who wants to get closer to design, an engineer who wants to understand the product side better — that model works for everyone when you have AI in the mix. The boundaries between roles are blurring. We should be helping people move across them.

What are you building in Edinburgh, and what excites you most about the mission?

The opportunity to build something in Scotland that has genuine economic impact — not just on this company, but on the next generation of builders and on the tech ecosystem. Edinburgh has a deep concentration of world-class engineering and AI talent. The universities are actively encouraging AI experimentation. There are ambitious companies already emerging here. It is a small city, but remarkably rich in the opportunities it offers.

What I want to build is a hub that attracts that talent, compounds over time, and becomes an employer of choice in Scotland. But I'm equally clear about what I don't want: an annex. I don't want Edinburgh to feel like a satellite office with a flag planted in it. Whatever we build here should be genuinely integrated with Multiverse as a whole — incubating ideas, levelling up skills, working as one team. If we get that right, I think we'll build something quite remarkable.

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Last year I spoke to a leader at a large retailer who told me she’d given up trying to hire young people. Not because she didn’t want to. But because every time she tried, something got in the way - the right programme didn’t exist for her team’s roles, the cost of a younger hire was virtually the same as for an experienced one, the admin took weeks. She ended up hiring someone in their thirties. Fine, but not what she’d set out to do.

I’ve had versions of that conversation many times. The problem isn’t that employers don’t care about young people. It’s that the system has made it genuinely hard to act on that care.

A million young people locked out of work

Over one million under-25s in the UK are currently not in education, employment, or training (NEET). That number has been rising since the pandemic, at a cost of an estimated £20 billion in lost economic output. More than the macroeconomic number, there’s a human one: young people who spend extended time outside work or education face lower earnings and worse prospects for the rest of their lives. This is not a marginal policy problem.

We’ve been working in this space for nearly ten years. Thousands of young people have started their careers through a Multiverse apprenticeship and we have worked with over 1,500 employers. We know what works and we know what gets in the way.

Three forces reshaping early talent hiring

Three things are happening simultaneously that have led us to redouble our efforts here.

First, the economic squeeze. AI is optimising roles and reducing demand for entry-level work. Fewer vacancies mean more young people competing for less. The jobs that used to be natural on-ramps into careers are either disappearing or changing beyond recognition. The young people applying for them are just as capable and motivated as ever but the system isn’t keeping up.

Second, the policy shift. The Government has read the moment and is responding. It’s trying to build more incentives for under-25s, using cash and training subsidies to get young people into quality apprenticeships. The policy direction is clear. The challenge is whether the right programmes exist for that investment to flow into.

Third, the AI skills gap. This is the one that strikes me as most urgent. Young people know the jobs they’re entering look nothing like the ones their colleagues started in five years ago. They want future-proofed skills. But only 13% of early talent apprenticeships are in digital or business - the very skills they need most are the least available to them. That’s not a gap. It’s an open goal.

What Multiverse is launching: an AI-first apprenticeship for career starters

So we’re doing something about it.

This September, Multiverse is launching a new AI-first early talent programme. Built from the ground up for career starters. Designed around what employers told us they actually need from day one - not what existed when the last generation of standards was written. Our aim is to deliver 2,000 opportunities for young people annually.

It starts with data and AI literacy: the foundation. Then moves to responsible use - the guardrails and judgment that employers worry young people lack. Then to practical productivity and applying those skills to real workflows and processes from the outset. The goal is simple: a young person who starts with us should be able to contribute meaningfully, they should be fluent in the basics of data and AI. This means they are able to make data-driven decisions, derive insights from data, use data to tell stories, and optimise workflows with AI for themselves and those around them. It should give them the springboard they need and employers the confidence to hire them.

We’ve built this with four things in mind. Workplace readiness - behaviours and confidence, not just technical skills. Wraparound support - coaching, mentoring, and career guidance throughout. Structured AI literacy that’s practical, not theoretical. And Atlas, our 24/7 AI coach, so learners get help when they actually need it.

Our recommendations for government on early talent

We’ve spoken to hundreds of employers. The picture is consistent: they want to hire young people. They’re being held back by cost, complexity, and the absence of programmes that provide the foundational skills that young people need in the AI era.

We have views on what government should do to fix this structurally and we’ve published them. If you’re interested in the policy argument, including our seven concrete recommendations for reform, you can read the full paper here.

But policy moves slowly. What moves faster is employers deciding to act.

If you’re building a team and wondering whether an early talent programme could work for you, we’d like to talk. We’re opening early access to the September cohort now.
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Multiverse has launched a new AI and data training programme with Paragon, one of the UK’s biggest business service companies, designed to improve efficiency and strengthen growth opportunities across the business. 

The programme will train employees across 15 different departments in data and AI capabilities, embedding practical skills directly into daily workflows to streamline manual processes and increase productivity. By improving internal processes, Paragon's teams will be better equipped to enhance the services they deliver for clients.

The Academy also deepens the partnership between Multiverse and Paragon by creating new opportunities to enhance training capabilities, with Paragon's clients and their evolving needs at the centre.

David Phillips, COO at Paragon’s Outsourced Services division, said: “We’re now operating in an environment where efficiency and the ability to make faster, better-informed decisions have never been more important. At Paragon, we know that embracing technology, and giving our people the skills to use it, is crucial to meet this need. Our partnership with Multiverse is critical to this mission, helping us to enact our own digital growth strategy and unlock innovation that can improve the customer journeys for our clients across multiple industries.”

The programme is structured to support learners with varying digital skill levels, from technical beginners to established practitioners. By embedding training directly into daily workflows, newly acquired skills are applied immediately to real operational challenges, accelerating Paragon's digital transformation from the inside out. The result is a workforce where everyone, at every level of the business, is empowered to contribute directly to the company's innovation-led transformation strategy and long-term growth ambitions.

Jay Richman, Chief Product and Technology Officer at Multiverse, said: “Paragon sits at the centre of complex, high-volume business services, and the opportunity to apply AI and data skills to those workflows is enormous. That’s what we’re doing together: giving their people practical capabilities applied to real operational challenges, so they can streamline how work gets done, make faster decisions, and deliver stronger outcomes for their clients."

Multiverse, the upskilling platform for AI and tech adoption, today announced the opening of a new technology hub in Edinburgh. Following its recent $70m funding round, the hub marks an expansion of Multiverse's engineering footprint, placing an additional centre of technical excellence outside of London. Former Amazon leader Colin Mackenzie has been appointed as the company’s first VP AI Engineering to lead it, and will focus on developing agentic products.

Mackenzie brings more than a decade of engineering leadership experience to the role, most recently spending six years at Amazon. For the last three years he has built the generative AI platform that powers Amazon’s AI advertising products. Prior to this he held senior engineering roles at Virgin Money and Clydesdale Bank, saw a startup through to a successful exit, and founded his own business. Throughout his career he has had a focus on developing high-performing, high-agency teams that innovate around the latest technologies. He will oversee the Edinburgh hub's growth and bring his expertise to Multiverse’s AI talent development programme.

As part of its broader expansion, Multiverse will create 200 jobs in the next year across the new office and its London HQ, while continuing to grow revenue per employee. This will fuel its mission to translate AI’s potential into practical outcomes for employers across the UK and Europe. 

Colin Mackenzie, VP AI Engineering, Multiverse, said: "AI is changing how people work faster than they can retrain for it, and without equitable access to AI skills a lot of people get displaced and left behind. We need to innovate at pace to solve this problem, and thankfully Scotland has the world-class AI talent required to help us do it. When we get it right, we change lives at a national scale."

For incoming and existing tech talent, Multiverse is also launching an internal upskilling model, pairing high-agency junior AI engineers with senior engineering leaders. This approach treats mentorship as a core engineering function, accelerating the development of practical AI skills through on-the-job learning alongside experienced practitioners. 

Paired with delivering its AI product and data engineering apprenticeships, this reinforces the company’s commitment to equipping the whole workforce to win in the AI era, from frontline workers to frontend engineers.

Jay Richman, Chief Product & Technology Officer, Multiverse, said: "We're building the AI adoption layer for UK and European employers. That requires depth in the product, and in the team building it. The market problem is significant: AI capability is advancing faster than workforces can absorb it, and employers are under real pressure to close that gap. Edinburgh gives us access to additional world-class engineering talent, Colin brings the track record to lead it, and our model of pairing high-agency junior engineers with senior practitioners means we're building capability as well as headcount."

The announcements come as governments and employers intensify their focus on AI adoption as a driver of productivity and economic growth. Multiverse's model, combining employer partnerships with structured, outcome-focused learning, is directly aligned with that agenda.

Across the UK economy, businesses, public sector organisations and universities are driving ahead with AI adoption, supported by the skills delivered through Multiverse programmes. In the past six months, employers like BT, Pan Macmillan, Addison Lee, Capita, Evri and Keltbray have launched significant upskilling efforts, rolling out hundreds of AI, data and engineering apprenticeships between them.

Multiverse, Europe’s only EdTech unicorn, announced a partnership with Synthesia, the world’s leading AI video communications platform.

Under the partnership, Synthesia’s AI video platform will be formally integrated into Multiverse’s AI Learner Toolkit - a suite of tools its learners can explore to scope, build and deliver AI projects inside their organisations. Learners across Multiverse’s programmes will now have additional resources and guidance to implement Synthesia as a tool to design and deploy AI video solutions for their employers, alongside a range of other no-code, low-code and generative AI tools.

Learners have already begun applying Synthesia independently to drive real business impact across industries:

• Two local government learners deployed Synthesia to meet high-demand content needs - one halving production time entirely, another creating accessibility-compliant resident communications that shifted service delivery from assisted to digital channels
• A customer operations professional at an insurance company redesigned training for vulnerable customers, replacing manual live delivery with standardised AI-generated video modules - improving consistency, reducing workload and strengthening auditability
• A programme director at an international real estate company is using Synthesia to produce multilingual training materials at scale, replacing text-based content with engaging video, without the time and cost of traditional filming and voiceovers

The partnership formalises an existing relationship. Synthesia is already embedded in Multiverse’s own learning content, used to produce AI-powered video at scale across its programmes. This capability allows Multiverse to deliver dynamic, multimodal content that can be updated in real time, keeping pace with rapid technological advances. By blending this cutting-edge AI with its signature human coaching, Multiverse creates an AI-powered, human-led learning experience.

The announcement was first made at Synthesia Live London, where Multiverse CEO Euan Blair joined Synthesia CEO Victor Riparbelli for a fireside conversation on AI adoption and the future of workforce transformation.

Euan Blair, Founder and CEO of Multiverse, said: “The true power of AI occurs when brilliant tech meets human capability. Together with Synthesia, we are turning that vision into reality, putting world-class video AI straight into the hands of our learners to become creators and innovators. They are finding the real-world use cases that improve productivity and create tangible outcomes. And this is how widespread AI adoption actually happens.”

Victor Riparbelli, Co-founder and CEO of Synthesia, said: “We’re at a rare inflection point: AI is becoming genuinely capable, and at the same time, upskilling and reskilling workforces is now a board-level priority. The question isn’t whether organisations need to transform - it’s how fast they can build the human capability to make it real. Synthesia and Multiverse sit at exactly that intersection. Embedding Synthesia into Multiverse’s programmes means tens of thousands of learners will learn to create, communicate and share knowledge, enhanced by AI.”

The partnership reflects a shared conviction that AI can supercharge what humans are able to achieve. With more than 30,000 learners across the UK, Multiverse works with employers across financial services, public services, professional services and beyond to equip workforces with the practical AI capability needed to compete. Synthesia’s platform is used by more than 65,000 businesses globally, including 90% of the Fortune 100.

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We didn't set out to be a skills provider who always solved the same problems for the same people: we optimise for adoption, adapt to what customers really care about, and ultimately help build the workforce of the future. 

It’s approaching ten years that we’ve been delivering apprenticeships and the most important lesson we’ve learned is that you have to solve for customer value if you want to effect long-lasting change in the skills system. You might have killer content and incredible coaching expertise, but if your programme doesn’t solve a problem or address a pressing skills need it won’t deliver enduring impact.

And sometimes that means anticipating what’s next, not just what’s currently working. That’s exactly what we did with AI – developing training programmes to meet emerging customer needs, before the apprenticeship infrastructure was set up for it. This has now changed with the rollout of a new AI apprenticeship standard, but we’re now three and a half years on from the launch of ChatGPT.

At the same time, when you start to innovate at scale, scrutiny from the existing systems isn’t merely inevitable; it’s necessary. Regulation is there for a reason – it’s not a critic to be ignored, it’s a guardrail to keep standards high.

What the Ofsted inspection found

We set out to build a new system for technical training that works for everyone – from an 18-year-old retail worker on the shop floor to a 68-year-old NHS clinician. To date, we’ve supported tens of thousands of learners and more than a thousand employers across all sectors of the economy. 

Our report demonstrates that there is plenty to be proud of, and these are all things that our customers will recognise:

The achievements of our learners, who “gain substantial new knowledge and skills in artificial intelligence, use of data and business analysis and management, having in many instances started their apprenticeship with little or no prior experience.”

Our inclusive learner experience, “where apprentices, including those who are disadvantaged, feel welcomed and well supported.”

The quality of our expert coaches and instructors, who are “skilled, effective teachers.” 

And the tangible benefits we bring to our apprentices and their employers: learners gain promotions or increased responsibility by the time they complete, improve productivity, and “produce complex, meaningful projects that they successfully apply in the workplace”.

However, the report also flagged areas where we need to pay more attention. 

In the tech world, there’s a habit of attacking regulators when their feedback is constructive. We won’t be doing that. We’re using this as an opportunity to sharpen our delivery.

What we're changing following the Ofsted report

We’re taking the feedback on board - here’s a few specific examples of how:

1. Hiring more coaches and equipping them better, with workloads already back down: Our coaches and expert instructors are the backbone of what we do. We’ve invested in better internal tools to strip away admin so they can focus on the coaching conversations that matter. And we’ve already hired more than 40 new coaches and instructors in the last quarter alone, so we can continue to grow and support our learner base.
2. Career guidance for every learner: We’ve always believed in lifelong learning, but we didn’t prioritise offering specific careers advice for everyone, given some of our learners  are twenty or thirty years into their career. We’re now making sure our platform offers career support for every learner, regardless of their seniority.
3. Improving our offering for line managers: a crucial predictor of learner success is how much their managers engage with the projects and work they’re doing with us. Going forward we’re improving the manager experience on our platform and redesigning the progress review process.

Looking ahead: skills, AI, and the UK's productivity challenge

Relevant skills are the most important asset we can give workers today – just as they’re the most important lever we have to solve the UK’s productivity challenge. To make that a reality, we have to be willing to hold ourselves to the highest possible standards.

We will invite Ofsted back for a re-inspection before the end of the year, and we already know we have the best people ready to deliver that change.

In the meantime, we remain focused on the goal: ensuring that in the AI era, no one is left behind.

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Qualification Achievement Rate (QAR) is a metric used by the Department for Education to measure the proportion of learners who successfully complete an education or training programme. In the government’s own framing, it gives “one measure” of a provider’s performance.

Multiverse’s current apprenticeship completion rate is 52.6% — below where we want it to be, and below its peak in recent years. It will improve by June, when the current academic year ends, and more improvements will follow as we invest in other changes required to get QAR back to where it belongs.

But we also believe, as the regulators do, that QAR is one measure of training quality. It is not the complete picture. There are specific reasons why ours sits where it does, and those reasons are tied to our mission to build a world where tech skills unlock people’s potential and output.

Three reasons for Multiverse’s current QAR

We’re an AI training pioneer

Multiverse invested early in making AI skills training available, before the apprenticeship system had created a designated AI standard. This created a structural mismatch between what employers needed and what the regulated framework prescribed — an almost inevitable consequence of a disruptive technology moving faster than the system designed to support it. 

We acted fast and first because our view is that when AI can already automate tasks someone has spent twenty years mastering, the responsible response as a technology training provider is to make training available to them now, not after they’ve been made redundant. But innovating ahead of the regulatory system has a cost, and some of that cost shows up in our QAR.

The launch of a designated AI apprenticeship standard has addressed this directly. And when the regulatory framework catches up with businesses' needs, so too will our QAR.

We prioritised inclusive enrolment

The single biggest driver of completion rates, whether it’s apprenticeships or degrees, is who you allow to start. On our AI programmes, we made a deliberate choice to optimise for access and tolerated lower completion rates as a result. We thought it more important to give as many people as possible a shot at AI readiness than to filter for those most likely to complete. That’s a decision we stand by, even if we’ve subsequently taken steps to create a more even balance.

The success of our more inclusive approach is reflected in a 50/50 gender split across our largest AI programmes, at a time when external research shows women are significantly less likely than men to engage with AI. Across our entire portfolio, 40% of learners did not previously hold a degree, and  26% of our learners have a contextual flag, meaning they meet one or more markers of socio-economic disadvantage, such as being care-experienced. 

Our impact-first programme design

Multiverse apprenticeship programmes are designed so learners start solving real problems at work from day one, not after 18 months of theory. Many learners deploy new skills during their programme, earn the promotion or pay rise they came for, and then leave before completion. QAR registers that as a dropout but we see it differently.

Our data shows that 45% of learners receive a promotion during or within 12 months of their programme, and 60% secure a pay rise. These are strong proxy measures for employers receiving the outcomes they commissioned. If someone achieves what they set out to achieve, for themselves and their business, and then moves on, we don’t consider that a failure.

What the data really shows

The countless individual, impactful learner outcomes that sit alongside our QAR tell the full story of the value Multiverse delivers.

In a typical example, a Royal Free London NHS Foundation Trust administrator digitised an entire patient journey during his apprenticeship — doubling his department's daily caseload from 30 to 60 patients, reducing non-discharged patients by 93%, and cutting waiting times from over 30 minutes to 10. He was promoted to data coordinator as a result. That is a meaningful measure of success, and the kind of return we routinely track for our customers.

Additionally, across our customer base, 98.4% of learners who complete their course achieve a pass or above. Net Revenue Retention stands at above 100%, meaning employers consistently invest more with Multiverse after their first programme. Last year, Multiverse accounted for more than half of total growth in apprenticeship starts across the entire system. This is the side of the story that completion rates don’t capture.

Working with the system, while sticking by our convictions

As one of the largest apprenticeship providers in the country, Multiverse takes its responsibilities to the wider system seriously. Wherever regulators identify areas for improvement, we will act on them. Not as reluctant concessions, but because that’s how a serious provider engages with a regulatory framework that it’s committed to improving alongside. 

We know what it takes to have high completion rates and we know what we need to do to get back there. Elsewhere, our completion rates are higher: our degree-level programme completes at c.70%, and our software engineering programme sits well above national average at 90%.The changes underway to our apprenticeship programmes in enrolment criteria, programme design and how we support learners through to the finish line are already moving the dial and will be reflected in our numbers following the end of this academic year.

What will not change, however, is our conviction that programme completion is a means to an end, but not the end in itself. Our mission is to create a workforce equipped to win in the AI era. Everything we build, measure and invest in is pointed towards that.

Read our latest Impact Report to discover how Multiverse is transforming the way people learn and work, and helping thousands of workers unleash AI's potential. Or get in touch to learn more about how Multiverse can support your workforce.

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RSK has launched a strategic partnership with upskilling platform Multiverse to train an initial cohort of 33 employees in advanced AI applications. The partnership is designed to support RSK’s ongoing emphasis on innovation and technological advancement.

With more than 200 businesses, RSK Group will benefit from AI fluency across core functions and divisional teams. By empowering staff to embed advanced AI capability to support their work, teams can shift their focus to the strategic, high-value work that drives revenue.

Gary Eimerman, Chief Learning Officer at Multiverse, said: "We’re proud to partner with RSK, turning AI literacy into a shared language across its businesses. This mastery of AI will serve as a force multiplier, allowing teams to unlock hidden efficiencies and scale their impact. Together, we’re building a future-proof foundation that supports RSK as the group continues to find solutions to complex environmental challenges."

Dr. Ian Goodacre, Group Divisional and Board Director at RSK, said: “At RSK, our strength lies in our vast, multi-disciplinary expertise. This partnership with Multiverse is about empowering our people to harness that collective intelligence. AI support will allow our teams to focus on the high-value, creative problem-solving that helps us achieve efficiencies, stay competitive and continue to deliver outstanding results for our clients."

The 33 learners are enrolled across three programmes with Multiverse’s AI portfolio:

• AI Strategy and Leadership, Level 5: Designed for leaders to align AI initiatives with specific business areas and broader strategic goals.
• AI for Business Value, Level 4: Empowers teams to identify and implement tailored AI solutions that drive measurable business impact, focusing on process optimisation.
• AI-Powered Productivity, Level 3: Boosts team productivity by integrating GenAI tools into daily tasks to automate repetitive workflows and drive measurable efficiencies.

This partnership is part of an important step in RSK’s digital transformation. In fostering a culture of mastery and technological confidence, RSK is positioning its team to navigate the accelerating pace of the global working world and solve complex client problems with innovative, bold solutions.