Financial Leaders Sure but Slow to Pay for AI Projects
Endava’s most recent study shows a big difference between how hopeful the banking sector is and how much money it is putting into artificial intelligence. 92% of the CEOs who were asked think their companies are ready for agentic AI, but only 36% have set aside money for it.
The results show that people are far more confident in AI’s potential than they are willing to spend money on it. This shows a big gap between strategic ambition and operational preparedness.
Infrastructure and Governance Remain Key Obstacles
Executives know what AI can do, but not many companies have the infrastructure to enable autonomous systems. Most organizations have a hard time using AI in complicated regulatory and compliance systems.
Endava says that governance frameworks and technical maturity will decide if trust can lead to real changes in business.
Agile Processes Slowing Down AI Deployment
Ironically, agile frameworks that were meant to speed things up are actually slowing down the adoption of AI. 75% of those who answered claimed that agile techniques slow down deployment for agentic systems that work on continuous, changing cycles.
Almost half said that ecosystem interconnections and cross-border compliance are two instances where agile methodologies don’t work well with AI’s complexity.
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The Push Toward AI-Native Operating Models
There is a growing agreement that banks and other financial organizations need to move toward AI-native architecture. Seventy-six percent plan to switch to AI-first operating models within three years, seeing the change as necessary to stay competitive.
But just 16% of them are AI-native right now. Italy is the most likely to embrace it, with 25% of people doing so. The US is next with 24%, while France and the UAE are far behind.
Agentic AI Seen as a Gateway to New Revenue Streams
More than 80% of CEOs think that agentic AI will help them find new markets and ways to make money. Immediate uses are mostly for finding fraud, stopping crime, and making sure operations run well.
Agentic AI can improve security and speed up financial services by automating the process of finding anomalies and checking for compliance.
Bridging the Gap Between New Banks and Old Banks
Digital-native banks have already set up quick, user-friendly platforms, whereas older banks are still working on updating their old infrastructure. Now, traditional companies see agentic AI as the way to narrow the gap in innovation.
Banks could offer individualized services and free up human workers to do more valuable work if they could run all the time and make decisions on their own.
Privacy of Data and Openness of Rules Still Important Issues
Leaders always said that data privacy, lack of transparency, and unclear rules were problems that made it hard to scale AI. Being able to explain automated judgments is becoming more and more important for both following the rules and gaining customers’ trust.
47% of companies are adding ethical rules and ways to be open to AI systems, and almost half are making their governance structures stronger.
Responsible AI Use Defines the Future of Financial Innovation
According to Matt Cloke, Endava’s Chief Technology Officer, agentic AI will change the way financial companies do business and come up with new ideas. He stressed the need for good governance and responsible design.
Dava.Flow, Endava’s own AI platform, is a good example of this method. It combines new ideas with cooperation across fields to make sure that AI is integrated in a fair and ethical way.
