Denmark's AI bank shot: An interview with Richard Davis and Kasper Tjørntved Davidsen

EVIDENT: Why update the strategy now? What’s changed that’s made it a good time for this kind of a refresh?

RICHARD DAVIS: It's the halfway mark, and it really is around making sure that we can go out there and give updates to the market. We are pivoting towards enabling our strategy using Gen AI. Some of the customer outcomes are the same. The way we’re delivering is more optimal by embedding Gen AI in those technology journeys. 

What’s embedding AI into those journeys actually look like?

KASPER TJØRNTVED DAVIDSEN: If you want to embed AI into the workflows, into the culture of a company of our size, you have to address it from multiple angles. At the strategic level, we’re now putting our money where our mouth is, meaning that we have specifically put numbers to the market based on our AI ambitions. Another equally important lever is cultural, making sure every employee sees AI as a capability enhancer that helps them deliver better outcomes, both in their day-to-day work and for the bank. We do that from hackathons, with Gen AI Week (editor’s note: the bank-wide AI conference), with demos, with a network of ambassadorships and champions, supported by a narrative and incentives that make it easy for people to get involved

DAVIS: When it comes to large-scale transformations, you have the top down – similar to how we did cloud – but then also bottom up. We set a strong strategic course, then empower champions and thought leaders across the organization, use targeted demonstrations to show the art of the possible and anchor the change through HR and a deliberate mindset shift. There isn't one approach that will work in isolation. It's joining all those up, and then having a Gen AI team – the central function – and the operating model around that as well. And to be clear, if we had not done the cloud transformation, what we are able to do today would not even be remotely possible. We want to be a frontrunner, but being a frontrunner means that we're probably going to be learning as we go as well. Making sure that we're not afraid of stopping or saying, hey, this isn't quite working, let's have another look and adjust how we go. It's really an exciting journey here. When I joined two years ago, I was looking at the cloud journey and the cloud transformation. I would say 80% of my time is now spent on Gen AI. Now there's a correlation with the cloud journey as well; it’s enabling us to be a lot faster when it comes to some of the products that are coming out, especially when we look at AI City and the core capabilities behind it.

You’re building this AI city. Where did the idea come from? And how’s it different from what other banks are doing?

DAVIS: When we start talking technology – Bedrock agents, AgentCore, all this stuff – to operational users, you can see their eyes glaze over. The idea behind the AI City came from a simple realization: To scale AI across a bank with 20,000-plus employees, you need shared infrastructure – reusable platforms, built-in security, governance, orchestration and development blueprints. The AI City metaphor helped align executives quickly because just like a real city needs roads, utilities and building codes before it can scale, enterprise AI needs strong foundations.

TJØRNTVED DAVIDSEN: It definitely comes from a practical scaling challenge that we have. We've seen momentum with Gen AI tools and pilots, but if you look at a bank of our size with all the individual use cases, that's not enough for us to reap the benefits that we committed to the market. The AI City is how we make capabilities reusable across teams and actually deploy workflows with the right evaluation and controls built in so that you can embed these things at scale and at a cost point that is significantly lower than if everyone went out there and did things on their own.

Tell me more about what the AI City actually is.

TJØRNTVED DAVIDSEN: At its core, AI City is 50-plus shared capabilities built on a small number of chosen platforms. Therein lies the secret to scalability, the reusability. These capabilities underpin what individual use cases need to run in the organization. It also keeps us adaptable. That's why we're creating the opportunity for immense modularity. AI is moving fast, so we don’t want to be locked into specific choices. If we change a tool, or adopt a better way to monitor agents, we change it once in the foundation, not separately in every use case. That's the power of the city where you can put in these new capabilities as they come to market.

Tell me more about observing, the measurement piece. How are you judging what’s working around the city?

TJØRNTVED DAVIDSEN: For the strategy refresh, we have a series of big programs that consist of use cases underneath that. We started with “enterprise AI,” AI for everybody, and we’ve also been driving “tactical AI” for a while now, with close to 40 live use cases already supporting the business across the bank. With the refresh, we’ve been clear to the market that the next step is to combine use cases to reinforce each other, so the impact is greater than the sum of the parts. They will all leverage our asset registry, observability, traceability, meaning that, from a corporate point of view, we can always see what has been put into production, where it runs, how it performs and how we can pick it up and redeploy it elsewhere. There's a very clear prioritization mechanism that is rooted in the value that is being created. We are always focusing on the largest, the most strategic initiatives. It has to have clear outcomes for the bank that we can actually put a KPI towards. The requirements are a material business problems, clear ownership from business, measurable outcomes and the ability then to scale beyond a single team

So how do you draw that line between what’s worth pushing into different lines of business versus where you need to go back to the drawing board to reengineer something?

TJØRNTVED DAVIDSEN: There's a very clear prioritization mechanism that is rooted in the value that is being created. We are always focusing on the largest, the most strategic initiatives. It has to have clear outcomes for the bank that we can actually put a KPI towards. The requirements are a material business problem, clear ownership from business, measurable outcomes and the ability then to scale beyond a single team.

DAVIS: This is a strategy refresh that enhances an already strong growth agenda. AI and technology further accelerate that growth, which means we can now raise the bar on what we can achieve. The business cases have all been looked at as part of the original Forward ‘28 strategy, but embedding Gen AI in those technology solutions to deliver those outcomes either faster or more productively. And then from the technology solution perspective, we are pragmatic. We buy over build where the market offers proven scale through our strategic partnerships, and we build where it differentiates us. That balance lets us move at pace and focus our talent on the highest-value opportunities.

You’ve talked about the technology piece of the strategy and the organizational piece of it. How do you balance the effort between changing the way people use the tech vs. developing new tools that facilitate that way of work?

DAVIS: That's that million-dollar question, isn't it? The tech is pretty much proven with regards to what it can do. We spend as much time changing how people work as we do building the technology itself. We focus heavily on embedding AI directly into existing workflows. But also, how do we reimagine, reinvent, rewire the whole organization to optimize the outputs that we can get from this technology?  The technology is moving so quickly, even quarterly reviews or two week sprints, maybe the technology is outpacing that as well. So reimagining how we do things like that: How do we do three-day deliveries? Or rather than a team of eight, how do we do the same delivery with a team of three so the rest of the team can take on other projects?

You’ve told the market AI and tech are going to generate 2 billion Danish kroner – $315 million – in productivity benefits annually by 2028. Where’s that coming from?

DAVIS: We continue to invest significantly in our tech transformation and AI tools, with investments rising from around 4 billion Danish kroner (roughly $630 million) last year to about 4.5 billion ($707 million), and staying at roughly that level through 2028. Those investments allow us to size the benefits to a 2 billion Danish kroner ($315 million) run rate in 2028. And it’s not a hockey stick, it’s fairly linear, with meaningful run-rate benefits already in 2027. Broadly, it comes from three areas: developer productivity, frontline tools and back-office and enterprise productivity.

TJØRNTVED DAVIDSEN: That drives the improvement in cost-to-income ratio from AI and tech. The AI City contributes to this by allowing us to reuse capabilities, apply common controls and monitoring, and deploy solutions across teams instead of rebuilding from scratch –  taking out cost by optimizing on the back end in our processes. But it is also driving increased customer engagement that will then drive revenue for the bank.

If a competitor read this and saw the AI city framework and aimed to replicate it, why do you think Danske Bank is uniquely suited to execute on it? 

TJØRNTVED DAVIDSEN: We have had the period of experimentation. We let several thousand colleagues get hands-on with GenAI and we learned what actually works in practice, and what doesn’t scale. That is why we developed the AI City, because we knew that we needed to have that framework in place where we can move at pace but at scale. And we would not have been able to do that had we not had the past experiences. I think other companies will either miss that mark, or they will need to find their own mark in time and then take that opportunity to build that repeatable platform. The hard part is industrializing it while the technology keeps moving and still being disciplined enough to deliver on the targets you’ve communicated to the market.

DAVIS: We're small enough to be agile, we're big enough to be relevant. We're in that sweet spot of size to pressure test some of the technologies. We are a 150-plus-year old bank operating in a highly regulated environment, so what we build has to be secure, resilient, and able to serve at enterprise scale, not just work in a lab environment. The fact that we are predominantly running on cloud, and some of our tooling is running on cloud, and we've got our data programs as well allows us to move quickly while staying grounded in the realities of banking. The AI City is designed to continuously adapt as AI becomes a core part of how we work and serve customers. The final thing is our CEO is all in. Executive-level sponsorship really does drive that mindset through the organization.