AI Governance in Banking: Managing AI Risks and Scaling Responsible AI Adoption
Banks are accelerating artificial intelligence (AI) adoption, from generative AI applications to more advanced autonomous AI systems. However, many financial institutions are finding that their AI governance frameworks are not evolving at the same pace as AI capabilities. Strengthening AI governance is becoming essential to manage risks, meet regulatory expectations and enable responsible AI scaling.
As banks move from AI experimentation towards enterprise-wide adoption, they are unlocking opportunities to improve operational efficiency, customer experience and innovation. At the same time, financial institutions face increasing challenges related to data governance, cybersecurity, model risk, compliance and customer trust. In the Nordics and across Europe, these challenges are becoming increasingly important as organisations prepare for evolving AI regulation and supervisory expectations.
In this paper, Deloitte benchmarks AI governance maturity across Global and Domestic Systemically Important Banks (G-SIBs and D-SIBs), as well as other large banks, using Deloitte’s Trustworthy AI Governance Index. The index provides a snapshot of how global banks are progressing across key dimensions, including principles and policies, organisational structure, procedures and controls, people and skills, and monitoring, reporting and evaluation.
The findings suggest that while progress has been made, most banks still have significant room to strengthen their governance frameworks. The research also explores the link between AI governance and revenue outcomes and outlines practical steps for leading governance transformation.
Why This Matters for Danish and Nordic Banks
For Nordic financial institutions, these findings highlight the importance of building AI governance capabilities that enable innovation while managing regulatory, operational and reputational risks. As banks expand their use of generative AI and explore agentic AI applications, strong governance and effective controls will be critical to maintaining customer trust and ensuring responsible adoption.
The Nordic financial sector is known for innovative technology solutions built around a customer-centric approach. Danish banks have an opportunity to lead in responsible AI adoption by embedding governance excellence from the outset, rather than retrofitting controls as risks emerge.
Key takeaways
- AI Adoption is accelerating, but AI governance maturity is lagging: 63% of bank employees use AI weekly; 87% of banks could significantly improve governance and only 13% reach leading maturity.
- AI risk management and customer trust are becoming critical priorities: In H1 2026 the financial sector reported more AI incidents than in all of 2025. Globally, 84% of consumers say they would switch providers if their data were mishandled
- Organisational and talent gaps: Organisational structure scores lowest and workforce capability continues to lag, limiting consistent application of AI governance across the bank.
- AI governance frameworks must evolve with generative and agentic AI risks: Monitoring and oversight are weaker for more autonomous (agentic) AI than for traditional or generative AI
- Governance drives growth: Stronger AI governance is associated with wider deployment, more users and stronger revenue growth (econometric result: ~10 percentage points higher revenue growth for a +10 point increase in the Trustworthy AI Governance Index).
of consumers would switch providers if their data were mishandled
of banks provide regularly refreshed AI governance training to all staff
annual financial services AI incidents rose nearly eightfold between 2022 and 2025
How can banks close the AI governance gap?
- Make governance a precondition for scale, not a check at the end
- Put visible executive accountability (“tone from the top”) at the centre
- Treat AI as a transversal risk driver, not a standalone issue
- Move from ‘human in the loop’ to ‘human on the loop’
- Create a risk-reward culture around AI
Methodology
In 2026, Deloitte’s Trustworthy AI team surveyed 24 leaders from G-SIBs and D-SIBs across 14 countries to assess the maturity level of AI governance structure.
Following this a survey of 111 senior technology, AI and data employees for G-SIBs, D-SIBs and other large banks captured additional perspectives across 16 countries (including from major banks in the Nordic region). Data was collected using two purpose-built survey instruments designed to capture the perspective across the global banks, securing a total of 135 respondents
