The next generation of financial services will be built with AI, not replaced by it

Artificial intelligence is changing the way companies operate, but the most important question is not how much work AI can replace. It is how much better people can work when AI becomes part of their everyday environment.

This distinction is especially important in financial services. Across insurance, credit, investments and other financial activities, our work is built on information, judgment and trust. Every customer interaction, claim, credit decision, investment analysis and business process creates data that can help us make better decisions and serve customers more effectively.

AI creates a cascade of possibilities across every domain. The opportunity may look different in insurance, credit, investments, service or operations, but the underlying potential is the same: to give people better tools to understand information, generate insights and make better decisions. Unlocking that potential requires strong data foundations, digital capabilities and, above all, people who know how to use them.

At Phoenix Financial, this is the philosophy guiding our AI and digital transformation. We do not see AI as a sophisticated calculator that simply performs an existing task faster. We see it as a tool that can challenge thinking, provide new insights and help employees take their own capabilities and professional judgment to a higher level.

The real potential of AI is not in reproducing yesterday's processes more efficiently. It is in helping us re-imagine better ones.

In claims, for example, AI can help structure information from documents and images, identify missing details, support coverage or fraud checks and recommend next actions. The result can be a faster and more transparent experience for customers, while allowing claims professionals to focus on complex cases where judgment and empathy matter most.

In underwriting, AI can help organize large volumes of structured and unstructured information, surface relevant insights and support more consistent decision making. In customer service, it can help employees better understand the customer's context and respond more quickly and personally.

The same principle extends across the group. In credit, AI can help professionals synthesize information and prepare decisions. In investments, it can accelerate research, surface relevant insights and make knowledge easier to access. The applications differ from one domain to another, but the underlying opportunity is the same: giving people better tools to elevate their own expertise and thinking.

The objective in all of these cases is not to remove people from the process. It is to give them better tools. When technology handles repetitive information gathering and synthesis, employees can spend more time on judgment, problem solving, creativity and customer relationships.

That is why we think of AI as a thought partner, not a thought replacement.

Technology alone does not create transformation. The harder challenge is creating an organization that is willing and able to use it.

One of the ways Phoenix Financial has approached this is by building an internal community of AI Champions. Around 100 employees and managers from across the group, spanning insurance, investments, credit and other areas, are helping lead AI adoption within their own domains, translating new capabilities into practical tools and everyday ways of working for their teams.

The community went through a structured period of training, hands-on experimentation and ongoing mentoring, with the aim of turning AI from something employees hear about into something they can actively use and shape.

We have also used initiatives such as an internal AI hackathon, where nearly 90 ideas were submitted from across the Group and 18 teams moved from business needs to working AI agents. Importantly, these solutions were shaped and built by employees from the business itself, based on challenges they encounter in their daily work.

This is fundamentally a cross-divisions, cross-domains transformation. There is no single AI playbook for every function, and there should not be. The value comes from giving each part of the group the capabilities to apply AI to its own needs, while allowing ideas, knowledge and reusable solutions to travel across organizational boundaries.

These efforts matter because large transformations often create natural resistance. New technology can feel distant, threatening or imposed from above.

The goal is to create the opposite dynamic. When employees participate in the change, experiment themselves and see how AI can help them in their own work, resistance can turn into curiosity and adoption. AI becomes something people want to use, rather than something they are told to use.

This cultural shift is just as important as the technology itself. It also changes the role of an AI program. Instead of innovation sitting with a small central team, knowledge spreads through the organization, closer to the business problems, customers and employees it is intended to serve.

This does not mean every employee becomes a developer. It means that business expertise becomes more actionable. The people closest to the problem can help define, test and improve the solution, while technology teams provide the secure foundations, integrations and governance that allow it to scale.

AI does not operate in isolation. Its usefulness depends heavily on the quality, accessibility and governance of the data underneath it.

For a diversified financial group, this is particularly important because critical information exists across many systems, business units and formats. Building strong data infrastructure, improving digital journeys and creating the right governance, with clear guardrails around security, privacy and responsible use, are therefore part of the same transformation.

Phoenix Financial's AI efforts are developing alongside a broader evolution in digital capabilities, marketing and data infrastructure across the group. Together, these foundations make it possible to move from isolated experiments to tools that can become part of real business processes.

The ambition is not to accumulate dozens of disconnected AI pilots. It is to rethink entire domains and ask how they should work if we were designing them today with the capabilities now available to us. The answer will look different in insurance, credit, investments or service, but the principle is the same: use AI where it can meaningfully improve how people think, decide and operate.

AI technology will continue to evolve quickly. Generative AI is already progressing toward more agentic systems that can complete sequences of tasks, interact with tools and support increasingly complex workflows. The specific technologies will keep changing.

For companies, that makes adaptability more important than any individual tool.

The organizations that benefit most from AI will be those that build strong data and digital foundations, create the right governance, develop their people and make experimentation part of the culture. They will also be the ones that remain clear about where human judgment matters most.

For Phoenix Financial, the transformation is ultimately about building that kind of organization. One where AI does not narrow the role of employees, but expands what they can do. One where technology makes information more accessible and decisions more informed. And one where innovation improves not only productivity, but also the experience of customers and employees.

At its best, AI gives every employee, regardless of function, a new set of capabilities to take their own expertise, judgment and thinking several levels further. When that happens across divisions and across domains, individual adoption can become an organization-wide transformation.

Written in collaboration with Phoenix Financial