Banks are increasing investment in artificial intelligence faster than other sectors, yet many lack the governance and infrastructure needed to ensure those systems are trusted, according to new findings from SAS’ Data and AI Impact Report: The Trust Imperative, with research by IDC.

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Across four industries studied, banking leads in both AI spending and the adoption of trustworthy AI practices. Around 23% of banks operate at the highest level of IDC’s Trustworthy AI Index. However, only 11% have achieved both strong internal confidence in AI and systems that are demonstrably reliable. Meanwhile, 47% fall into what IDC describes as a “trust dilemma”, either underusing reliable AI due to limited confidence or relying on systems that have not been sufficiently validated.

“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, based on a global survey of 2,375 IT and business leaders, highlights a widening gap between AI investment and the supporting structures required to sustain it. While 60% of banks expect AI spending to grow between 4% and 20%, foundational challenges remain. Around 19% still operate with siloed data systems, 45% lack effective data governance, and 41% do not have centralised or optimised data infrastructure. In addition, 42% report shortages in specialised AI talent.

Michel Ghorayeb, Managing Director at SAS UAE, said: “Banks in the Middle East are well-positioned to build on strong foundations, with robust data, clear governance, and effective oversight enabling AI investments to scale and deliver reliable results. At the same time, prioritizing transparency and making AI decisions easier to understand will play a key role in strengthening confidence. Banks that place responsible AI at the heart of their strategy will be best positioned to drive innovation, earn trust, and create sustainable long-term value.”

Despite these challenges, more than half of banks plan to expand their AI architecture, while 43% intend to grow dedicated AI teams. However, only 31% are focusing on developing and refining AI models, suggesting structural issues remain.

"The banking sector clearly understands AI's potential, but understanding and execution are not the same," said Kathy Lange, Research Director of the AI and Automation Practice at IDC. "Without strong data architectures, governance frameworks and talent pipelines, banks risk pouring money into AI initiatives that can't deliver ROI – or worse, that undermine the very trust they depend on."

The findings also indicate that innovation, rather than cost reduction, is driving AI returns. Banks prioritising customer experience and market expansion report higher returns than those focused on efficiency. Organisations emphasising trustworthy AI are also more likely to see significantly improved returns.

"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.”