Endava: Why AI Adoption is Lagging in Financial Services

Financial institutions are ready to adopting agentic AI. They just aren’t funding it yet.

Endava surveyed 1,000 senior leaders across nine countries and found 92% say their organisations are prepared to deploy autonomous AI. However, only 36% have earmarked budgets to make it happen.

The obstacle between ambition and implementation isn’t conviction. Leaders grasp the technology and its uses. What’s missing is the infrastructure, governance and technical capability to run these systems at scale.

Agile processes create bottlenecks

Three in four surveyed leaders say agile methodologies are slowing them down. Frameworks built to accelerate software delivery now struggle to accommodate AI systems that operate on different timescales.

Regulatory complexity and ecosystem integrations are where the friction shows up.

Nearly half of respondents (49%) say these are the areas where agile can’t keep pace. An AI system plugging into multiple third-party platforms while threading cross-border regulations and compliance doesn’t slot neatly into two-week sprints.

Agile still has a role. Some 86% see value in these methods for specific tasks. The question is when to apply them and when to route around them. Most leaders (76%) expect their organisations will need AI-native operating models within two to three years.

Nearly all (94%) believe this shift will define competitive position.

Few have made the leap. Only 16% of organisations describe themselves as AI-native.

Italy leads at 25%, followed by the United States at 24%. France sits at 6% and the UAE at 4%. The UK matches the global average of 16%.

Agentic AI expected to unlock market potential

More than eight in 10 surveyed leaders expect agentic AI to open new markets or create new revenue streams. Immediate applications centre on fraud detection, financial crime prevention and operational continuity.

Banks lose billions each year to fraud. Regulators keep tightening anti-money laundering and know-your-customer requirements.

System failures – however brief – trigger penalties and erode customer trust. Agentic AI can process transactions and identify anomalies faster than human teams.

The longer view is continuous operation. Leaders anticipate 24/7 service, faster product launches and more personalised customer interactions.

Some expect autonomous systems to handle routine tasks without human involvement, freeing staff for work that requires human judgement.

Part of this is defensive. Digital banks and fintech firms built their operations around speed and user experience. Traditional institutions carrying legacy systems and deeper regulatory obligations are working to close that gap.

Data privacy and regulatory uncertainty top concerns for financial leaders

Data privacy, regulatory uncertainty and decision transparency surfaced most often when leaders discussed concerns about deploying agentic AI.

When an AI system approves a loan, blocks a payment or flags an account, customers and regulators expect explanations. That gets harder as systems learn and adapt autonomously.

Data privacy also becomes more complex when models need access to data across jurisdictions with differing rules.

Nearly half of organisations (47%) are embedding ethical guidelines into AI development.

The same share are implementing transparency and explainability measures. Another 46% are tightening data privacy protections, while 44% are putting governance frameworks in place for AI use.

About 42% of firms are working to align agentic AI with regulatory requirements. Just more than a third (37%) are training employees on responsible AI use.

The numbers suggest organisations recognise that governance failures could turn the technology from asset to liability.

Matt Cloke, CTO at Endava, says: “Agentic AI represents a step-change in how financial services organisations operate and innovate. The opportunity is clear, but so is the responsibility. Our research shows that those who build AI-native operating models, backed by strong governance, will be the ones to lead the next era of financial services.

“At Endava, we’re already adopting this approach with Dava.Flow, our AI-enabled engagement lifecycle. We know that success lies in adapting quickly, embracing multidisciplinary teams and balancing innovation with organisational health.”