Research: Agentic AI Ambitions Expose Banking’s Manual Operations Problem

SaaScada research reveals the gap between agentic AI ambition and operational reality, as legacy systems, manual processes and fragmented data hold banks back.

21 May 2026, London – SaaScada, the cloud-native core banking engine, today released new research revealing a widening gap between banks’ agentic AI ambitions and their ability to execute, as legacy systems, fragmented data and manual processes continue to dominate key operational processes.

The report, Who’s Ready for Agentic AI in Banking?, includes findings from a survey of 150 UK banking innovation leaders. It shows that banks overwhelmingly believe agentic AI will reshape the industry, but very few are operationally ready to take advantage of it:

• 91% believe agentic AI will enable entirely new ways of designing banking services. Yet only 31% are actively deploying any type of AI in core operational or decision-making processes.
• 77% cite legacy systems restricting data availability, poor data quality (77%) and difficulty accessing real-time data (71%) as significantly limiting their ability to adopt AI.  
• 79% believe that without high-quality, explainable data, AI could worsen financial exclusion, rather than improve it. But only 12% are very confident their organisation could clearly explain and justify AI-driven decisions to regulators today.

“Trying to build AI on ancient legacy foundations is like racing an Aston Martin over cobblestones – it’s going to be a bumpy ride,” says Steve Round, Co-Founder and President at SaaScada. “If banks are serious about getting ahead with AI, they need data and core systems that are fit for purpose. Otherwise, all the ambition in the world won’t translate into results.”

One of the biggest challenges that banks face is that they are still heavily reliant on manual processes. Just one in ten banks fully automate key operational tasks, such as processing: 

• Standing orders, scheduled payments and direct debits (10%)
• Daily interest accrual and interest posting (11%)
• Account maturity instructions (13%)
• Scheduled interest rate changes (13%)

More than a third – between 37% and 42% – still rely heavily on manual processes and exception handling to complete these tasks. 

Overall, 61% of respondents (57-63%) find such tasks very or extremely painful in terms of cost, manual effort and risk. There is also a direct correlation between perceived pain and reliance on manual processes: 

• 85% of those who have minimal automation reported finding these processes very or extremely painful in terms of cost, manual effort and risk
• 55% for those with some automation, but regular manual oversight
• And 0% for those who fully automate 

“Banks can’t expect to innovate with agentic AI if they are still mired in manual processes,” comments Paul Payne, CTO at SaaScada. “The priority has to be maturing the infrastructure and driving automation first. Only then can banks layer in AI and start to see real operational gains.”

You can download the full report here.

Ends 

About the research

The data was gathered in March 2026 from 150 UK-based business heads/C-Suite staff at retail and business banks who are responsible for product innovation (e.g. Heads of Digital Transformation/CTOs/Chief Innovation Officers/Heads of Innovation/CEO). The banks had a balance sheet size of £0.5Bn – £100Bn.