The numbers coming out of Multiverse’s latest funding round tell a story about where enterprise investment is heading. The AI upskilling platform raised $70 million in primary funding on May 15, led by Schroders Capital, with participation from existing investors including General Catalyst, Lightspeed Venture Partners, D1 Capital Partners, Index Ventures, Bond, and StepStone Group. The round values Multiverse at $2.1 billion — a $400 million increase from its previous raise.

The company is reporting 50% revenue growth year-over-year and achieved its first cash-positive quarter between January and March 2026.

That combination — institutional investment at scale, real revenue growth, and a path to profitability — is the kind of signal that cuts through the noise in a crowded market.

Why AI Upskilling Is Getting Serious Capital

Workforce training is not historically a venture-scale business. The rounds that generate this kind of institutional interest, at this valuation, reflect something bigger than a product bet. Investors are pricing in a structural shift in how companies view talent development.

IBM’s 2026 CEO Study, surveying 2,000 senior leaders across 33 countries, found that 53% of employees will need upskilling to perform their current role effectively between 2026 and 2028 — and another 29% will require reskilling for an entirely different role. The same study found that 83% of CEOs say AI success depends more on human adoption than on technology capability.

Those numbers reframe the problem. The bottleneck to enterprise AI ROI is not access to AI tools. It’s the human layer. Companies that invest in AI infrastructure without building workforce capability tend to see pilots stall, adoption lag, and transformation programmes that generate good presentations but little operational change.

Multiverse is betting that enterprises will pay premium rates to accelerate that capability build. The acquisition of Berlin-based StackFuel earlier this year — an AI and data training company — signals they’re building substance, not just a platform.

What This Means for Business Leaders

The funding news is interesting. The business context behind it is what matters.

Microsoft’s 2026 Work Trend Index found that organisations they categorise as “Frontier Firms” — those deliberately redesigning how work gets done across human and AI systems — are pulling away from the rest. But Frontier Firms represent only 19% of AI users. The gap between them and the median enterprise is widening every quarter.

The difference is not technical sophistication. It’s workforce capability. Frontier professionals run multi-step agent workflows, redesign processes, and create shared standards across teams. Most employees don’t yet do any of that. They use AI reactively, when it’s convenient, rather than as a foundational part of how they work.

Training organisations like Multiverse, EDNA Learn, and others are trying to close that gap at scale. The $70M raise — and the valuation that comes with it — reflects institutional belief that the demand is real and durable.

A few things stand out about this moment in the market:

Speed of change is compressing training timelines. The skills that mattered in AI eighteen months ago are already partially obsolete. Organisations need continuous learning infrastructure, not one-off training events. Platforms that can update content and delivery quickly will win enterprise contracts.

The European focus is notable. Multiverse’s expansion plans are explicitly aimed at Europe. EU AI Act requirements, combined with strong regulatory pressure around AI transparency and documentation, have made workforce capability a compliance issue in some jurisdictions — not just a competitive one.

Apprenticeship models are gaining ground. Multiverse built its reputation on vocational apprenticeships tied to real job roles. Applied learning beats passive consumption. Enterprises are increasingly recognising that workshops and e-learning modules alone don’t change behaviour at scale.

The EDNA Perspective

Enterprise DNA has trained over 220,000 data professionals across 50 countries since starting in structured learning. The core lesson from that experience holds: people who can genuinely work with data and AI tools outperform those who can’t, and the gap compounds over time.

The Multiverse raise validates what we’ve believed for years — that AI literacy is not optional for businesses that want to remain competitive. But there’s a distinction worth making between general AI adoption training and deep technical upskilling in data, analytics, and applied AI.

General adoption training — understanding what AI can do, how to prompt effectively, how to review AI outputs — is now table stakes. The organisations seeing the most durable ROI from AI are the ones that have also built genuine data skills across their teams: the ability to structure data questions, evaluate outputs critically, build models that connect to real business problems, and design workflows that actually improve decision quality.

That second layer is where EDNA Learn specialises. Power BI, Python, SQL, and applied AI courses designed for people doing real analytical work, not just consuming dashboards. For businesses building teams that can work alongside AI systems rather than just use them as a convenience tool, the business learning pathway is built for that outcome.

The Multiverse raise suggests the market agrees: AI upskilling is not a one-time spend. It’s becoming a permanent line in enterprise operating budgets.

What Happens Next

Multiverse will use the capital to scale its European operations, build out its AI-focused curriculum, and expand its enterprise sales team. With $72 million in total funding and a clear path to profitability, they’re positioned to move from growth-stage to category leader in the European market.

The broader pattern is consistent. Capital is flowing toward companies that help enterprises actually operationalise AI — not just deploy it. Workforce development is increasingly understood as a core part of that operationalisation, not an afterthought.

For any business leader looking at an AI transformation agenda, the question is no longer whether to invest in workforce AI capability. It’s how to build it in a way that sticks.

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Enterprise DNA trains data professionals and business teams in the skills they need to work effectively with AI systems. If you’re looking to build genuine AI and data capability across your team, explore our business learning programmes or talk to us about a custom AI upskilling programme for your organisation.

Related reading: What 220,000 professionals taught us about learning data skills, why we stopped just teaching data and started building AI systems, and the Excel-to-AI upskilling path that’s actually realistic for most teams.