AI in Banking is Moving from Experimentation to Accountability
Banks are scaling AI at record pace. The next challenge is proving what it's delivering.
Artificial intelligence has moved beyond the pilot stage in banking. Across the industry, organisations are embedding AI into customer servicing, onboarding and fulfilment journeys, as well as fraud prevention, software development and operational decision-making. Investment continues to accelerate, and the conversation has shifted from whether banks should embrace AI to how quickly they can scale it.
Yet amid the excitement, a critical question remains: how many organisations can clearly demonstrate the value their AI investments are delivering?
The latest Evident AI Index for Banks, widely regarded as one of the sector's leading benchmarks of AI maturity, offers an interesting perspective. The Index evaluates 50 of the world's largest banks across measures including talent, innovation, leadership and transparency, providing an independent view of AI maturity across the sector.
Three findings stand out:
- Average AI maturity scores increased by 26%, almost three times the previous pace.
- Just 12% of reported AI use cases are linked to an operational KPI.
- Only 1% report a direct financial outcome.
Taken together, these numbers tell an important story. Banks are investing in and deploying AI at unprecedented speed, but their ability to measure business value is struggling to keep pace. For banking leaders, that distinction matters.
The challenge of proving value
As AI moves from experimentation to deployment, expectations are changing. Boards want evidence that AI investments are generating measurable returns. Regulators want confidence that AI is being deployed responsibly. Executive teams want to understand where the technology is improving productivity, reducing costs and delivering better customer experiences. But proving impact is difficult.
Most banks operate within complex ecosystems of technology, suppliers and processes. Customer journeys span multiple channels and teams, making it challenging to establish a clear link between AI activity and business outcomes.
The challenge isn't deploying AI. It's measuring what it changes.
Why customer servicing and onboarding matter
For many banks, the clearest opportunity to demonstrate AI's value lies within customer servicing and onboarding journeys. These are high-volume, high-impact processes that influence customer experience, operational efficiency and regulatory performance.
Crucially, they also generate measurable outcomes.
Whether supporting service agents, streamlining onboarding, automating fulfilment processes or personalising interactions, AI can be linked directly to metrics such as servicing costs, completion rates, complaint volumes, customer satisfaction and retention. In a Consumer Duty environment, the ability to evidence those outcomes becomes increasingly important.
This is where organisations need more than individual AI solutions. They need visibility across the customer journey and clear accountability for the outcomes they are trying to achieve.
Three priorities for banking leaders
As AI adoption continues to accelerate, leaders should focus on three priorities:
- Start with outcomes, not technology.
- Create end-to-end visibility across customer journeys.
- Align accountability for delivery and outcomes.
The next stage of banking's AI journey
The banking sector has made remarkable progress in advancing AI capabilities, and the question now is not when AI will transform the industry. It already is.
The real differentiator won't be AI adoption. It will be proving value, and when only a small proportion of AI initiatives can demonstrate a direct financial return, the challenge facing the industry is clear. The banks that pull ahead won't automatically be those deploying AI fastest, but those that can demonstrate measurable outcomes and scale what's proven to work.
That's particularly true in customer servicing and onboarding, where customer experience, operational efficiency and regulatory expectations converge.
At Paragon, we work with many of the world's leading financial services organisations to transform customer servicing and onboarding journeys, bringing together communications, digital experiences, fulfilment and operational delivery under a single accountable model. As AI adoption accelerates, that end-to-end visibility will be critical to helping organisations measure outcomes, evidence value and realise the full potential of their investments.
If you're building your evidence for next year's Evident AI Index for Banks, I'd be interested to compare notes. I’d love to speak to you about how banks can measure AI's impact across the customer journey and turn individual improvements into clearly evidenced outcomes.
Because in banking, success won't be defined by how much AI you deploy. It will be defined by what it delivers.
Ross Kittlety
CTO, Paragon
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