AI trust gap widens as banks scale deployment

By Vriti Gothi

Trust in artificial intelligence (AI) is becoming a defining challenge for the banking sector, as institutions accelerate deployment without fully establishing the governance, data infrastructure and oversight required to ensure reliability.

New research from SAS, with insights from International Data Corporation (IDC), highlights the scale of the issue. The Data and AI Impact Report: The Trust Imperative, based on a global survey of 2,375 IT and business leaders, finds that only 11% of banks have achieved both high internal confidence in AI and systems that are demonstrably trustworthy.

Despite leading other industries in AI investment and adoption, most banks remain far from what IDC defines as the “ideal state” where trust in AI is matched by proven, accountable performance. While 23% of banks operate at the highest level of IDC’s Trustworthy AI Index, nearly half (47%) fall into a “trust dilemma”. This includes institutions that either underutilise AI they have validated or over-rely on systems that lack sufficient testing and governance.

“On trustworthy AI, banking leads every sector in this study and even so, most banks’ foundational readiness is nowhere near where it needs to be,” said Stu Bradley, Senior Vice President of Risk, Fraud and Compliance Solutions at SAS. “Roughly nine in 10 banks have yet to fully align trust with proof, and about one in five are still running on siloed data. Closing the gap between AI ambition and AI readiness should be a top-down priority for all banks.”

The report identifies several foundational weaknesses underpinning this gap. Around 19% of banks still operate with siloed data infrastructure the highest rate among sectors studied while 45% lack effective data governance frameworks and 41% do not have centralised or optimised data environments. Talent shortages are also a constraint, with 42% of banks reporting gaps in specialised AI skills.

At the same time, investment in AI continues to rise. The study finds that 60% of banks expect their AI spending to grow by between 4% and 20%, with a further 12% anticipating even higher increases. However, Kathy Lange warned that without strengthening core data architectures and governance frameworks, banks risk investing in initiatives that fail to deliver return on investment or, in some cases, erode customer trust.

The findings also challenge assumptions about how AI generates value in banking. Unlike other sectors, banks increasingly view AI as a driver of product and service innovation rather than cost reduction. Cross-industry data shows that AI initiatives focused on customer experience generate the highest returns, delivering $1.83 for every dollar invested, compared to $1.54 for cost-focused use cases. Organisations that prioritise trustworthy AI are also 60% more likely to double their overall returns, reinforcing the link between responsible innovation and financial performance.

In the Middle East, AI adoption is gaining pace alongside broader digital transformation initiatives, including national strategies such as the UAE’s Vision 2031. Michel Ghorayeb said banks in the region are well positioned to scale AI effectively, provided they focus on strong governance, transparency and explainability to build confidence among customers and regulators.

The report also highlights a growing shift towards agentic AI systems, with nearly one-third of banks planning to increase investment in trustworthy AI to support more autonomous decision-making. However, this evolution is expected to heighten regulatory scrutiny and amplify the risks associated with weak oversight.

“Regulators are watching. Customers are watching. And right now, nearly half of banks are using unproven AI or hesitating to tap AI they’ve validated,” said Alex Kwiatkowski, Director of Global Financial Services at SAS. “No bank wants to become an ‘also-ran’ in this highly competitive race, and cost savings alone won’t keep them in it. The banks that win will be ones that invest in governance, explainability, transparency and strong data foundations before they scale, not after something breaks.”

Overall, the findings point to a critical inflection point for the banking industry. While AI investment continues to accelerate, the ability to translate that spending into trustworthy, transparent and well-governed systems will determine whether banks can realise sustainable value and maintain customer trust in an increasingly AI-driven financial ecosystem.