Episode 12

Cia: Welcome to Employee Activation, the podcast that takes you into the minds of some of the world's brightest workforce strategists to find out how they make both their employees, and their organisations thrive. I'm your host, Cia Kouparitsas. What happens when one of the most heavily regulated, risk averse industries in the world meets the breakneck pace of artificial intelligence.

The financial services sector is at a crossroads, forced to evolve fast or fall behind. But it's not just about upgrading tech, it's about rethinking the skills, mindsets, and structures that support it. To unpack this, we are joined today by Katharine Wooller, Chief Strategist for Financial Services at Softcat, one of the UK's leading technology solutions providers.

Katharine brings a sharp, pragmatic perspective on what the sector needs next, from digital capability to critical thinking and why legacy thinking might be the biggest risk of all. We'll explore the widening skills gap and what it means for talent development, organisational resilience, and future readiness.

And while this focus is financial services, the lessons reach far beyond, because this industry is often the canary in the coal mine.

Let's dive in, welcome Katharine.

Katharine: Hi. Thanks for having me.

Cia: Now, Katharine, you're Chief Strategist for Financial Services at Softcat, and you have had a, a fascinating career path that spans strategy, finance, and ops.

Can you tell us a little bit about your role today and, uh, how you view AI its influence in that role, but also more broadly in financial services?

Katharine: Yeah, sure. So I'm Chief Strategist in Banking and Finance for the reseller, Softcat PLC, which provides IT services and infrastructure to over two and a half thousand financial services firms.

So we support our customers in understanding and leveraging emerging technologies such as AI, amongst many others to drive innovation and efficiency within our industry. We actually support a huge variety of financial businesses. So there's a lot of variety within FS, Um, so I spend my day job talking to regulators, central banks, tier one banks, asset managers, insurers, retail financial services, fintechs, all the way through to tiny little kind of cooperative building societies.

So I sit outside our sales team, um, and I spend most of my day meeting with C-Suite and board members of our customers. And unsurprisingly, um, there is a huge bandwidth of conversation around technology, IT transformation and innovation dedicated to AI. Um, and as a business we've grown organically over 30 years, but earlier this year, we actually acquired a business, which is a data and AI consultancy. So that's a huge focus for us.

So AI for me right now within FS, has got significant attention at senior and board levels. Not to mention substantial budgets. So financial services is disproportionately represented in the growth of the AI industry and is actually expected to hit 97 billion by 2027.

So a huge wave of innovation. And in terms of magnitude, I see it like some of those earlier phases, whether it was the move to the cloud or cryptographic technology. So really it's a completely new way of thinking about data. And increasingly, as with many technologies, the cost drops over time or indeed, um, is sometimes free to the user.

So huge potential in financial services for reducing cost and risk with stacks and stacks of use cases across, whether it's optimising portfolios or finding fraud. For increasing automation and admin processes. So a huge amount, um, going on.

Cia: Yeah, it sounds like it. And what would you say is the comfort level for CEOs and boards with AI, because I think, as you rightly touched on, it is permeating every aspect of what we do, and financial services is very much at the coalface of that. How comfortable are CEOs and boards? Is it something that they know how to tackle? Are they just like everyone else? What's the position?

Katharine: As with any new technology, you tend to find the adoption and the enthusiasm is patchy.

So for example, we see a lot of acceptance in hedge funds because they use it, they invest in it to increase the return on their portfolios. We see a lot in insurance because, um, that essentially is about pricing risks. So they're very data focused. But if you kind of go down the scale towards maybe some retail financial services or private banking or asset management, there's less of it.

So I think there's huge interest at that kind of C-suite and board level. It reduces cost, it reduces risk. Um, it's a huge driver of efficiency, so loads of interest. So intellectual acceptance I think is good. How it actually works at the coalface, I think perhaps is sometimes, uh, less strong. And look, there's lots of reasons for that, whether it's, um, concerns about regulation or a very cluttered and complex and fractured landscape in terms of those vendors or really just proving those use cases, and look in terms of upskilling your board.

I see I've actually had a 10-year board career, I see loads and loads of content around actually, how is AI and how does it work? Some of that is, is rightly risk averse, which is actually how do we manage this actually, how do we upskill people, so very much about future proofing organisations, um, and, you know, that takes a, a fair amount of work.

Cia: It does and I'd really like to hone in on that point because I think that is a, a universal issue, which is that growing gap between AI ambition and workforce readiness in all sectors. Um, and I know that the Financial Services Skills Commission released, uh, and the AI report for 2025, which outlined that problem.

And I'm curious, um, I'm not sure if you've read that report.

Katharine: Yes, I have yep.

Cia: Excellent. So what, what do you think the sector is getting right or wrong when it comes to tackling the skills problem?

Katharine: So, I think the major headline for me is, when I read that report, is what is at stake for our industry and broader economy if we get it wrong.

So AI is, I'm in the UK so AI is expected to add 26 billion pounds to the value of the UK financials and professional services sector by 2030. So my personal view is that's probably a once in a generation opportunity for firms, the economies, and you know, probably society more broadly, let alone the people like me that are working in that industry.

So, it is likely that FS in the UK is the sector that will be most impacted by AI, and the UK is a service economy. We don't physically make much in the UK anymore, and we've always been very proud of our attitude towards innovation and the skills that we have in our workforce. So in respect of AI, the report is very blunt that the skills gap is a significant barrier.

So, despite the adoption, despite the enthusiasm, despite people using copilot or other models, that lack of skills is probably the biggest constraint in realising the potential of the technology. And interestingly, it drew out that it's unlikely that a broad selection of the workforce needs really deep AI expertise, it came up with 1.5% of the workforce, but that every employee needs a basic understanding of AI and how it works. And interestingly, um, we have the EU AI Act. So the UK regulator has been quite slow in giving us comprehensive rules, there are kind of bits of regulation that impinge upon it. The EU AI Act actually captures a lot of UK firms 'cause they often have European entities or they choose to match that standard today.

So one of the things the EU AI Act says is that you must train your team members about AI appropriately. So, for example, someone that works in marketing probably needs less detailed training than someone that's in data science and you know, using this each and every day from a technology point of view.

And the penalty for getting that wrong is massive, right? So you can have up to a fine of up to 35 million euros or up to 7% of global turnover at group level. So there's real pressure to get that right. So look, I think there is some light in that tunnel. I think regardless of seniority, leaders are looking to develop AI fluency. And I think you hear kind of once a day in my job that old adage, AI might not take your job, but someone that uses it might do.

So. I think there's lots of learning fixes out there, whether it's personalised learning or skills forecasting. And I think lots of firms are encouraged to embed AI in their learning and development. And actually, um, Softcat as a business is supporting lots of firms on getting that training out there, whether it's training Copilot to use better prompts or thinking about your long-term AI strategy. Um, we do see lots of demand for that.

Cia: I think that's fascinating, Katharine, and something that I've seen that really intrigues me across our financial services customers as well is that in many, uh, banks in particular, you've got the fabric of the workforce changing because they might have traditionally been operating in bricks and mortar and having, you know, employees who've had entire careers and show great loyalty and have incredible institutional knowledge.

But a lot of the work that they've done is being impacted by AI, whether that's augmentation or automation, and we're starting to see people explore how can they be re-skilling these workers from areas of the business that aren't needed, into these new emerging digital capabilities. Is that something that you've seen much of?

Katharine: So look, I think in financial services, I got my first job in financial services in 2000, so 20 or 25 years ago, there has been that kind of long march of digitisation. So one of the things I see in AI is, often when people say ai, they mean automation. So of course it is a next generation of automation, but actually there's much more demand for that reasonably simple automation rather than agentic AI, so definitely see lots more of that.

So look, it's a very different skillset, right? You know, I remember my grandmother saying to me in the late nineties, computers would never be a thing. And obviously she was in her eighties, right? So she was talking about it sort of through the lens of that, and I think, there's lots of focus on getting the right skills in the day job. So I'm not an HR professional as a day job, but clearly any firm needs a very broad L&D program to make sure those skills are cutting edge. And look, I see lots of focus within banks of staying competitive with relation to AI, right?

There's a sense of if you don't, you'll be left behind. And I think, you know, there's lots of good sort of foundation blocks. So we often see great data science and analytics teams. Upskilling them with AI is clearly a skill set they need, but they've got a great bedrock. And even just, you know, regardless of function, whether they're sitting in compliance or they're sitting in HR or you know, they're sitting in a, in a legal team, they are likely to need day-to-day interaction with AI.

And look, I, I go back to what I always say, which is AI is just a different way of thinking about data. There are skills and a mindset that need to change, but equally, there's a lot that's kind of embedded in the day job. I think the thing that's more interesting for us from the day job that I have, is that AI has a number of very specific risks, whether it's, ethical or governance or regulatory or from a cyber point of view. And that's a really big ask. So we actually support our customers with a lot of that handholding because you know, to be blunt, there is a real shortage of those skills in the UK, So actually they often have to come to companies like Softcat to say, please support us with, with that expertise.

Cia: And I'd like to delve into that a little bit more because I think when people are considering the workforce and the impact of, uh, digital maturity, whether it's AI or something else, you straight away go to the technical skills, and as you mentioned, is that your data skills or AI literacy. Uh, but I do think we are seeing a shift from purely those technical digital skills to things like, you know, needing skills around systems thinking, ethics, governance, change readiness.

How are you seeing, uh, that play out for financial services organisations in their approach?

Katharine: So I think that they're often using people they've already got, which is fantastic. And going back to the fact that AI is a new way of thinking about data, the skillset you need around that to be successful does change.

So we see really great firms that have got really clever long-term strategic plans for AI. They've got a centre of excellence, they've got great policies, they've got great governance. If you look at that long list of skills and services you will need around that, you know, AI strategy and design, there's a very specific app design and solution architecture.

You know, for developing AI, you need to have really great data, which is ready for AI, so you can train those models. Monitoring, again, that's different to monitoring standard data. So from a governance, security point of view, you know, with that data management, who can see it, what's the controls around it, what's the integration?

Even just the infrastructure and services it sits on there's lots of focus on AI ready data centres. AI adoption piece, yes, it's strategic. You know, you've got to have great change management and brilliant user training, and a great way of kind of capturing that ROI and making sure you're getting good feedback.

And it's really unlikely that one person or one team will have all those skills deeply. So again, we're supporting lots of our customers on, actually we do have some of these skills, but here's the ones we don't. I sometimes refer to that list of what you need for AI like a bit of a Chinese takeaway menu.

And you might have some of it, you might have none of it. Um, and again, we support a large number of firms with that.

Cia: I love that you, you had me at Chinese takeaway menu.

Katharine: Yes.

Cia: And now I'm really keen to understand how this works in practice. And I know obviously you work with organisations all across the UK on solving this problem.

Are there any standout examples, whether it's an organisation, a team, or a particular initiative that you think is tackling this problem well?

Katharine: Sure. So we have customers all over the world. Um, we sign NDAs, so I can't talk about individual customers, but I'd love to mention some of my personal favourite use cases, all of which are in the public domain.

So I mentioned that there's a lot of variety within financial services. So the way that a hedge fund would use AI is very different to the way that a retail financial services firm would use AI. So a couple of my favourites, AXA in insurance has got a large number of proof of concepts. They're very forward, thinking in how they view AI.

Uh, Revolut, which is a really big digital Native Challenger Bank, has a number of, um, bits of AI in production. So for example, they have an AI powered financial assistant, so providing really tailored advice. They use AI for fraud detection and they estimate that that's prevented scams of over 550 million euros. So a brilliant example of, I'm not quite sure what they invested in it, but I would imagine the ROI on that is really strong.

Nationwide, which is a high street bank, has customer service AI which is fantastic. Visa obviously the credit card has some really interesting agentic AI, which of course is the, I say the, the really clever end of AI, but I think is kind of some of the more sophisticated and actually, um, Softcat as a business itself, we're a PLC with FTSE listed in the UK. We do drink our own fizzy pop. Um, we actually purchased the company that came in and did, um, a piece of work around our data. We've got copilot across our organisation, which we've been extensively trained on. So I've been privileged to have some of that training. And I'm ashamed to say that I was using ChatGPT, um, at home in my private life and actually being sort of, fully trained by an expert completely changed the way I used it. And I'm ashamed to say I was probably only using about 5% of what it was capable of, so.

Cia: The common scenario, like I, I know in LinkedIn I'm constantly getting these feeds with these hacks on the different things I could be doing, and it's a light bulb moment every time.

But of course, like we know that AI is capable of these things, so it's nice to receive the training to be told, you know, just how much you can unlock it for, for your own role. And just for you personally, because you know, listening to you talk today, you are a wealth of information on this stuff. And I think, it is a topic that has many people feeling nervous because it is so vast and so new and so rapidly evolving.

How do you personally stay sharp and continuously develop your own skillset in this area knowing that it's changing every day?

Katharine: For my career, um, has very much been on sort of the bleeding edge, um, bit of technology within financial services. So, I see the industry is kind of waves of disruption, whether it was crowdfunding or migration to cloud or blockchain or the move back to slightly less in the cloud. So, AI is the next wave of disruption. Quantum computing is probably another layer on top of that. So, I'm from an academic background originally, so I'm really motivated to constantly learn.

I probably read for an hour a day. I try to digest a wide range of sources, whether it's mainstream media, specialist press, stuff that comes out of government or relevant trade bodies, but there's no replacement for talking to our customers who are in the thick of it. Which I'm very privileged to do so, and luckily, I work for an organisation that is obsessed with its customers, you know and providing great products and services in that space. So, if I don't get that feedback from the ecosystem, um, I don't think I'd be anywhere near as up to date. So really interesting work, but of course, constantly changing.

Cia: Definitely. Now I am very curious, again, noting that you have so many customers you've been supporting through this journey. What is the one piece of advice that you would, you would give these customers if they're at the start of the, the AI journey. So, introducing new systems, processes, but particularly trying to tackle that people problem.

What is the key piece of advice that you have for anyone starting off?

Katharine: So, I think a lot of our customers are early in that journey. The adoption and enthusiasm is quite patchy across the industry. So, I would say the majority of our customers are kind of earlier on in, in that journey. So look, financial services is an industry which is ripe for disruption.

Um, but innovation is a great thing, particularly for the consumer, driving cost, um, reduction and competition. So I think just to be positive about AI, and I think I would caution that with all sorts of things that we have to manage risk with, but just to be mindful that it's a really great journey to be on with huge potential.

So, um, embrace the journey and I think because we are at the foothills of that adoption, there are parts of the story that are still unfolding. Um, and to be blunt as an industry that we're probably still working out.

Cia: Love it. That is great advice. Now, just the last piece that we like to close on with all of our guests, Katharine, is around the name of our podcast, which is Employee Activation, and this idea that, um, every organisation should be focused on aligning the aspirations of their people with the objectives of the organisation, and that's how you can make people thrive.

What's your advice for organisations trying to do that?

Katharine: So, I caveat that I am not, um, in HR as a day job, but I have had large teams, I've worked anywhere from tiny little startups to a, a FTSE listed company. So, for me that employee activation is a stage beyond just engagement, and it's about giving your people everything you need to be the best versions of themselves.

So that puts culture front and centre and allows anyone in your organisation to bring their authentic selves to work, express their own ideas and expertise in a way that makes the group bigger than the sum of its parts. So, for me, that's a, a culture piece, um, but it just gets the best outta everyone.

Cia: I think that's great and echo that you do not need to be an HR leader to be able to get the best outta your people. In fact, every leader should be trying to do that. So, I think there's some very sage advice in there. Look, Katharine, I just wanted to say thank you. The conversation has been enlightening and also extraordinarily topical. I know so many leaders and organisations are trying to build out strategies, whether it's about digital maturity or AI programs, or just workforce skilling.

So thank you for sharing your unique insights into how the financial services sector is tackling this. I do think it's got broad relevance across a whole range of areas, and we do appreciate your time.

For anyone else wanting to learn more about the topic or about Katharine or Softcat, we will have lots of resources available on our website so just head to the WithYouWithMe website and find the Employee Activation page and feel free to connect with Katharine through LinkedIn as well. Thank you everyone, we'll see you next time.