The Multiverse blog

As teams across the UK return from summer breaks and lock into Q3 priorities, HR and L&D leaders face a familiar seasonal challenge: re-engaging employees, maintaining momentum on long-term development initiatives, and ensuring line managers are actively supporting their on-programme learners.

At Multiverse, we believe that world-class upskilling requires a world-class digital experience - and we've been busy building on your behalf. This back to school season, we're excited to share three key updates designed around three core goals: giving HR teams earlier visibility into learner progress, removing administrative friction from Off the Job (OTJ) time logging, and embedding line managers into the heart of the learning journey.

1. Improving engagement insights in the Learner Performance Dashboard 

The Learner Performance Dashboard provides HR and Operational leaders with full visibility across all apprentices in the organisation. This season, it has received its most significant refresh to date.

Historically, the first six weeks of an apprenticeship represented a data blind spot. We've solved this with our Engagement Model (Days 1-42 on a programme) so you can see how your apprentice is getting on and if they need any support. From Day 3, badge tooltips display clear indicators (On track, Almost there, Off track).

Furthermore, we have replaced legacy support factors with data-backed Engagement Levels and rewritten coach guidance to provide managers with concrete, actionable steps so they can decide whether to offer additional support. 

2. Making Off the Job logging smarter and faster 

Keeping a record of learning shouldn’t feel like a burden for you or your learners. To save your team valuable hours, attendance at live workshops is now logged automatically, with simple, seamless editing for any adjustments. If they finish a self-paced learning unit, a draft entry is ready for them to input into and save. Early results already show a nearly 50% reduction in late submissions, freeing up time for meaningful learning rather than chasing admin.

3. Embedding Line Managers into the Progress Review with their Learner and Coach

Line manager engagement is the biggest predictor of learner success. Every progress review is now a structured, live three-way meeting between Coach, Learner, and Line Manager, supported by platform-native AI to provide Managers with a pre-brief highlighting mastered skills, and post-session action summaries. This ensures time and attention is focused on the learner's achievements and the specific actions needed to stay on track.

These updates are a direct response to the feedback we’ve received from partners like you. By streamlining these core processes, we’re removing administrative friction so you can focus on what matters most: driving measurable learner success.

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Log in today to explore these enhancements and see the impact they can have on your team's development.

Store layout matters more than most shoppers realise. Get it right and sales rise, aisles stay clear, and customers find what they came for.

At a major UK retailer, one team decides where every product sits across every store. One of its members owned the feedback loop: gather responses from stores, spot the recurring issues, then summarise it for the senior team.

The process was slow.

"The sheer volume of data across two different platforms was a problem," Georgina explains, "and it was taking two hours to complete."

Two hours each round meant updates landed late and inconsistently. He needed a faster route - and AI gave him one.

"The team built a game-changing AI tool," says Georgina. "They open Copilot, upload the Excel file with all the feedback, and use a master prompt to analyse it. Then it creates a PowerPoint to send straight to the senior team for final decisions."

The tool sorts feedback into categories, writes the summaries, and sets out clear actions for the right colleagues in store. The learner still plays a crucial role - using his expertise to sense-check the findings and themes.

"The impact has been significant," Georgina says. "Besides turning a two-hour task into a fifteen-minute one, he can analyse store feedback daily rather than weekly. The senior team gets what it needs immediately, actions go out quicker, and stores feel like they're being heard."

One tool. Fifteen minutes. Better shop floors across the country.

Speedy Services, the UK’s leading tool and equipment hire services provider, is accelerating its digital transformation with the launch of a new AI Academy. The academy is designed to equip employees with the skills needed to operate more efficiently and elevate the customer experience.

Delivered in partnership with upskilling platform Multiverse, the academy will see 21 employees enrol on a 13-month AI-Powered Productivity programme. The training will help employees automate repetitive admin tasks, such as complex purchase order approvals, freeing them to focus on higher-value, client-facing work, including advising customers on complex machinery.

By mastering tools such as Microsoft 365 Copilot, employees will be able to streamline workflows, reduce administrative delays and deliver more consistent customer service. The programme will also support Speedy Services' broader goal of reducing revenue leakage by 50% through improved, standardised delivery. 

Dan Thompson, Managing Director, Power & Energy at Speedy Hire, said: “At Speedy, AI is reshaping how we operate. This partnership with Multiverse is about building AI capability with the individuals who'll help set the standard for how we work. By giving our people the confidence to use tools like Copilot, we can eradicate inefficient processes, standardise our service delivery, and ensure our workforce has the skills to thrive in a digital-first world.”

The launch builds on Speedy Services' award-winning "People First" culture. Having recently placed 57th globally and 11th in the UK as a Top 100 Inspiring Workplace, the business is ensuring employees feel supported, confident, and skilled in navigating the quickly evolving digital era. 

Jay Richman, Chief Technology and Product Officer at Multiverse, said: “Many companies buy AI tools and hope adoption follows. Speedy Hire is going a step further, building the capability to actually put those tools to use. Twenty-one employees are now getting hands-on with Copilot, learning it inside their actual jobs, not in a classroom. That's how you close the gap between what a business buys and what it actually gets out of AI.”

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Yesterday, the government announced that public spending will judge suppliers on the skills and jobs they create. From January 2027, local social value's weighting on government contracts worth £5m or more doubles, from 10% to 20%. Every organisation bidding for a share of the £90bn spent on public contracts each year will now score points for building good jobs, tackling local skills shortages, and helping young people into work.

We welcome it. Here's why, and what it means if your organisation bids for public sector contracts.

Why we welcome the government's procurement changes

For years, social value in procurement has worked like a form to fill in rather than a promise to keep. First Secretary of State Louise Haigh put it plainly: it's "been a tick box exercise that fails to deliver the positive change that people feel in their pocket and see in the places they live." Skills and jobs are now worth a fifth of the score on major contracts: enough to decide who wins.

Two priorities stand out to us.

The first is the focus on young people not in education, employment or training (NEET). Over a million under-25s in the UK currently fall into this group and we’ve published our own plans to support that group here. A procurement rule that specifically rewards suppliers for building pathways for young people is a direction worthy of support.

The second is the accountability mechanism. For major contracts, government departments will increase transparency for performance against these goals and publish annual progress reports. This makes it doubly important that social value commitments are actually upheld.

This is procurement finally rewarding the organisations that build real capability in their workforce, not just the ones that write a good bid.

How Multiverse already invests in skills and early talent

We've worked in this space for ten years, training over 40,000 learners with 1,600+ employer partners, including more than 150 public sector organisations such as NHS Trusts, local councils and police forces. In June, we announced a new AI-first early talent apprenticeship launching this September, aimed at exactly the group this policy is designed to reach: young people who need AI and data skills to compete in today’s job market.

None of this is new work for us. It's the same work, with government now backing it through how it spends £90bn a year.

What the new social value rules mean if you bid for government contracts

If your organisation supplies central government, or wants to, this is worth building into your strategy now.

From January 2027, a fifth of the score on contracts of £5m or more will come from local benefit, including skills development, apprenticeships and support for young people. That means the strength of a company’s commitment to workforce development, backed by real numbers, becomes a genuine differentiator in the bid itself. Vague commitments to social value won't hold up against a competitor who can show concrete plans. 

Three things are worth doing before the rules take effect:

• Get your skills investment measurable. If you can't show pay rises, promotions, or productivity gains linked to training, you can't evidence it in a bid.

• Build youth pathways now, not after you've won the contract. Suppliers will likely benefit from a credible pipeline for NEETs and young people before they're asked to prove one.

• Treat public reporting as part of the deal. The government will hold suppliers to their commitments publicly. Bids should only promise what can be delivered and shown.

This is the same discipline we apply to our own impact reporting. Our 2026 Impact Hub shows what that looks like in practice: 57% of our learners gain a promotion, pay rise or increased responsibility, and 77% say their programme made them more productive.

Backing British jobs and skills, together

Public spending backing British jobs and skills, in every postcode, is a change worth supporting. We've built our business around the same premise: that skills investment produces measurable returns for people, employers and the country. Government just decided to score for it.

If you're preparing a bid and want to talk through what a credible skills and early talent story looks like, get in touch.

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Europe has hit an inflection point. AI infrastructure spend has run into the billions, but economic growth hasn't followed.

High interest rates, tight fiscal policy and a stubborn productivity problem is the backdrop every business leader is working against right now.

And that’s why the AI mandate has shifted. Experimentation is over. Outcomes are everything.

Every year, we produce an Impact Report - like an annual report, but without the finance charts. It describes, through data, the outcomes we’ve driven for our learners and for our customers, through developing their capabilities in tech, data and AI.

And this year's Impact Report focuses on the metric that matters most in the age of AI: productivity.

Skills are the engine of productivity

We believe skills drive economic output, and our data backs this belief. Every pound and every hour invested in workforce capability feeds a flywheel: pay rises and job security for people, efficiency and revenue for employers, and higher, more sustainable growth for the country. Break the cycle at any point and everyone loses out.

But there’s challenging context to this too. Employer investment in training has fallen by nearly £10 billion in real terms over the past decade. And more than a quarter of employer vacancies today are skills related.

We want to change that.

Our impact in numbers

Across 40,000+ learners and 1,600+ employer partners, we've tracked £2bn+ in confirmed ROI.

Last year alone, Multiverse learners generated £340m in projected revenue and £557m in projected cost savings for their employers, as well as saving two working months per learner through efficiency gains.

That's £181,970 in projected financial return per learner.

Meanwhile 77% said their programme made them more productive, and 57% secured a promotion, pay rise or increased responsibility - pushing them up the career ladder.

Data, not dreams.

Real people, real outcomes

Behind every stat is someone who used new skills to move their career forward. Take Cali who went from experiencing homelessness at 21 to having a Data Analyst role created for her by her employer today. She built a chat app for an internal function now used by more than 2,000 people across her organisation - and her employer took notice.

Or Olly, an AI learner at brickmaker Michelmersh. Through Multiverse's AI programme, he moved from learner to leader, helping his team use Microsoft Fabric to cut gas consumption and energy costs. "I can analyse what's happening on the factory floor and connect it to the wider business strategy," he says. "That shift in perspective is what got me promoted."

Built for employers who want proof, not promises

More than half of CEOs say AI isn't delivering. But we think the question was never whether AI works. It was whether the workforce was equipped in how to use it.

One in three FTSE 100 organisations, 70% of Russell Group universities and 100+ NHS Trusts have worked with us to make that change. And every learner is backed by our 240+ coaches and instructors, as well as our AI coach, Atlas, which has fielded 2.25m chats from 25,000+ users to date.

Skills are a cause of economic growth, not a by-product. This report shows what happens when organisations, and the people inside them, treat capability building like the investment it is.

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The workload of a teacher can be incredibly demanding: beyond delivering lessons, there’s planning, administrative work, student support, and countless other tasks competing for time. All this can quickly become unmanageable.

As a Multiverse coach working with an education charity, Rachel O'Hehir sees this first-hand. “What every teacher has told me is just how demanding their role is,” Rachel explains. “They’re under a lot of pressure which can easily lead to burnout. So, removing the administrative burden is a no-brainer, allowing teachers to reinvest that time into what’s important.” 

Teachers lose 2-3 hours each week on manually preparing and reformatting slide decks, so it was no surprise that one teacher Rachel was coaching wanted to find a smarter way of working. That’s why she enlisted the help of AI to transform the way lessons are planned.

She built a new AI tool: a slide engine that automatically creates lesson decks, applies standard formatting templates, and pulls in the government-required literacy and vocabulary homework content.

“By inputting all the key resources needed for a lesson, teachers receive a slide deck that’s 80% ready for teaching,” Rachel explains, “and from there, they can easily tailor each deck to make sure it’s ready for different lessons and students.”

With the heavy-lifting done for them, the slide engine saves teachers at least an hour a week each – a massive cumulative saving of time across the organisation. It also enforces quality control, automatically integrating school and government requirements without creating extra work.

“At the minute, it’s the teacher’s department using the tool, but the plan is to roll it out to the wider organisation, and ultimately the wider federation of academies, based on how successful she and the team have found it.” A huge achievement for her and her fellow teachers.

For prospective Multiverse clients, being able to share confidential information is essential, so they can confidently discuss skills gaps in their business, how they’re currently using AI, and where they need the most support. They typically ask for a non-disclosure agreement (NDA) - something Sam and the Multiverse Legal team were ready to handle. 

But this was a slow process.

“When a customer needed an NDA,” Sam explains, “they would often share their own templated version. That required a manual legal review, and due to the volume, it would create a 1-3 day turnaround time.”

Sam and the team would spend an hour thoroughly reviewing each NDA. This didn't just eat up time, it meant teams had to wait longer to start conversations and get to work with clients. In short, the longer an NDA took to approve, the longer customers waited to start upskilling their teams.

Sam knew this needed to change, and saw an opportunity to connect two systems using AI: Ironclad, a contract management system, and Wordsmith, a legal AI tool that reviews contracts against a pre-submitted customer playbook. “The key for me was to get Ironclad and Wordsmith talking,” Sam says. “How do we get that file between one tool and the other? And how do I get it back?”

So, Sam got to work. To start with, he developed the NDA playbook with the Legal team, defining exactly what was acceptable and what needed flagging. “I uploaded the playbook to Wordsmith,” Sam says, “and turned it into an AI agent, which can review and edit NDAs, generate a summary of any potential areas to address, and populate our company details.” He then built an automated trigger in Ironclad, which sends the NDA to Wordsmith once uploaded, and back again once reviewed by the AI agent.

“The turnaround time dropped from 72 hours to five minutes”, Sam explains. “Now instead of fully reviewing NDAs ourselves, we’re reviewing the AI agent’s first pass at them.” This has freed up time for both the Legal and customer facing teams, so they can focus on areas where they can add deeper strategic value.

Beyond speeding up the process, Sam also reflected on how it’s inspired a cultural shift in the wider team. “It’s definitely motivated colleagues to lean more into automation. For example, teams across the business now go to the Ask Legal channel in Slack.” This AI-powered Slack chatbot uses an internal knowledge base to answer queries. “We just need to review and approve the output it shares.” Win-win for Legal, win-win for Multiverse.

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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