Everyone is talking about AI – but very few banks are truly using it in their everyday operations. During our recent webinar, AI in Banking – From Pilots to Real Impact, one thing became clear: the institutions that turn AI from experiments into execution will shape the next decade of banking.
An exciting talk from two leaders shaping AI in finance
We were thrilled to welcome Simon Kriss, co-founder of Sovereign AI and one of the world’s most respected voices on AI adoption in financial services. His talk at the Finshape Business Conference in Athens was a standout moment – bold, pragmatic, and refreshingly honest.
This time, he returned to the (virtual) stage alongside Josef Dvořák, Finshape’s AI Director, known for helping banks turn advanced technologies into tangible business outcomes. Together, they delivered a candid, highly practical discussion that resonated with hundreds of banking leaders.
What emerged was a clear picture of where the industry stands – and where it must go next.
1. Most banks are still stuck in pilot mode.
PoCs and experiments are everywhere, but few institutions connect AI to real business processes with measurable outcomes.
The insight? It’s no longer about proving AI works-it’s about scaling what already does.
2. Customers are adopting AI faster thanbanks.
People increasingly rely on tools like ChatGPT for investment advice, mortgage guidance and financial planning. Expectations for instant, personalised and understandable advisory are rising – with or without the industry’s readiness.
3. There is no single “right” path to AI adoption.
Successful banks combine:
- a focus on specific processes (e.g., call centres),
- practical governance frameworks,
- and fast experimentation that brings visible wins.
Momentum beats perfection.
4. Start with the use case, not the technology.
Too many teams fall in love with an AI tool first and then look for a way to deploy it. The most effective institutions reverse this: Define the business problem, then choose the right technology.
5. AI fails without strong data governance and people enablement.
Clean, well-governed data is essential – but so is preparing your workforce. Employees need clarity on how AI supports their roles, augments daily work, and shapes future responsibilities.
6. Begin with “low-risk, high-impact” use cases.
The quickest wins often come from:
- product-knowledge assistants,
- call summary automation,
- complaint handling assistants,
- AI copilots for relationship managers,
- or adding an AI layer to existing automation.
These build trust, internal capability, and organisational confidence.
7. Plan in 12-month cycles, not 5-year strategies.
Technology, regulation and customer behaviour shift too fast for rigid planning. A rolling 12-month roadmap, reviewed annually, keeps teams adaptive and aligned with reality.
If you missed the webinar and want to dive deeper into all insights, frameworks and real-world examples discussed, get the full recording – just click here!
And if your bank is considering moving from pilots to real AI impact, reach out to Josef Dvořák (josef.dvorak@finshape.com) Finshape’s AI Director, to explore where AI can deliver measurable value fastest.
