Transforming AI into Competitive Advantage – a fireside chat with Euan Blair of Multiverse
What is really going on with Artificial Intelligence and the world of work? Euan Blair, founder and CEO of Multiverse, the upskilling platform for AI and tech adoption, sat down with Dena McCallum (co-founder of Eden McCallum) for a wide-ranging conversation about AI usage and potential.
Multiverse has been valued at $2.1 billion, making it Europe’s only edtech unicorn. It has partnered with over 1,500 companies so far and trained 22,000+ workers, which has driven an estimated £2 billion of return on investment, and it was in that context that we were excited to speak with Euan.
Our discussion explored successful AI deployment, the regulatory context, public trust, and effective leadership through this transition.
Investing in people
Dena opened the discussion with a challenge. Euan talks about AI as a capability supercharger, painting a world in which tech skills unlock people’s potential and output, while others have talked starkly about a white-collar bloodbath. So which is it? “If you want to tilt the field towards supercharging, you’ve got to train people.” Euan’s biggest fear, he says, “is that we sleepwalk into a version of the apocalypse around AI because we’re not sufficiently intentional about what are we going to do to make sure workers don’t just get left behind.”
95% of organisations investing heavily in AI tools are not seeing real impact in their P&L, he observed, and it’s clear why. “You’ve got tools, but not capabilities… There are ways you can build training programs on the job to help people understand, how do I push the very limits of what AI can do within the confines and constraints that my employer or a regulator or whoever else is imposing? That requires genuine hands-on-the-keyboard training. It requires a lot of expertise and guidance from human coaches…. And it requires more than just executives saying, ‘Yeah, we’re pro-AI.’ It requires them actually doing something about it.”
So where to start? What do that 5% of organisations do differently? “Typically, most of them will start with some sense of what is it they’re trying to achieve with AI…And then you really need to understand to what extent is my workforce capable of achieving those goals based on the tools that I’ve brought in.”
Some of the greatest value from AI, Euan observes, is coming bottom-up. “The people who really need the skills but also can provide the most value are frontline workers,” Euan said, “often people who’ve been in the job for decades, who know the kind of work to be done that can be given superpowers with AI if they’re helped to navigate the constraints and actually achieve tangible things with that technology.” One Multiverse client is a UK retailer that has identified £180 million of return on investment linked to AI. “That involves everything from store managers basically changing how their store is run and what’s possible, through to people responsible for stock building automations make sure that they’re routing it as effectively as possible.” Similar examples come from construction, and manufacturing, “organisations that have often been at the forefront of physical technology and infrastructure and plant, who are now transforming their back office functions”
Some of the most striking examples of staff driving powerful outcomes come from cost constrained environments, perhaps most notably the NHS. “Literally their KPI is lives saved, right? We’ve helped an acute care ward at a London trust see double the number of patients as a result of better automating their inbound patient activity.“
Leadership from the top matters greatly, because employees need to know there is a purpose to the innovation and experimentation. “We’ve been doing apprenticeships for a while now,” Euan said, “and someone is much more likely to both complete their apprenticeship and deliver actionable business value if it is attached to a goal that they know their manager cares about, their manager’s boss cares about, and ultimately the organisation cares about, because it just makes it inherently more purposeful,” he said. “91% of employees say they want more AI training or experimentation.”
And to what extent is there resistance from staff who may ultimately be replaced? Rather than opposition, Euan finds employees seizing the opportunities that AI might give them, and has seen those who adopt AI successfully becoming “celebrities” within their organisations, for saving money or bringing about tangible improvements in service levels. “Employees are desperate to engage with it,” he said. And not just younger staff; in fact, Multiverse is finding that over 50s are adopting AI faster than the under 25s.
Regulation and consent
In the race for ascendancy in AI there is a contrast in approaches on either side of the Atlantic: a more permissive US approach and a stricter regulatory instinct in Europe. Which does Euan think is the right approach? Both, and neither. “Europe is being too risk averse, but the US is being too gung-ho,” he said. There is one advantage that Europe perhaps enjoys, he added. In the US “It’s very easy to shed labour, very easy to hire labour. There are way fewer incentives for employers to invest meaningfully long-term in their workforces. In Europe you have this really robust social contract between worker and employer. Often, it’s incredibly hard to displace people.
“In these circumstances you have to train your people,” he went on. “So Europe can use that advantage of this coalition between employer and employee to say we are going to make you the most AI-capable kind of skilled people. And Europe has a pretty highly skilled workforce in many areas, just often in legacy industries…Europe can have its own version of the AI revolution that is probably much more socially compatible with our values than what might happen in the US.” Britain, he feels, can split the difference and be a “third way” winner. “There is no world where we can fully restrict AI”, Euan said.
But what about the public’s fears and mistrust of AI? “I think we have a big problem with trust, full stop,” Euan said. “Politicians aren’t trusted, journalists aren’t trusted. Even trust in business leaders is going down. So trust in AI, I think, is suffering from the same challenge.”
“Everyone realises that completely unchecked AI is a problem,” he added. “But I think as the models get better, and as some of the safeguards get improved and the training data gets better, I think it won’t be long before people feel pretty comfortable trusting AI to do all sorts of things…Look, we’ve got autonomous vehicles on the streets of London..! My big fear is that this should be the number one thing being talked about by policymakers in pretty much every country, and it often seems to get relegated to a lower tier.”
Leadership
Finally the discussion turned to what the most successful business leaders in this AI transition are doing differently. “They are first giving permission to people to do things with AI. They’re celebrating those…who are actually demonstrating things they can do with it. We’ve sat in a few exec meetings where CEOs have said to their team, ‘You all need to lead the way on this.’ …And that kind of stuff helps people feel much more secure in delivering on this when it’s clear that, okay, my leaders are in this with me.”
There is also the question of risk. “You do need to give people permission to fail and get stuff wrong, but again, within safe parameters because there are some industries where even a failure rate resulting from AI of 1% is unacceptable for lots of reasons, and there are others where you can be more permissive…But I think leaders need to just be really explicit about where those boundaries lie.”
And the most successful leaders are also listening. “The best leaders we worked on with this realize that their top-down mandate will not go very far unless they’re getting something from their people, and they’re hearing that, and they’re listening to that, and they’re taking feedback on it.”
For the foreseeable future, then, from the front line to the boardroom, the most important factors in driving value are human.