Trust Gap Threatens Banks’ AI Adoption Progress, Study Shows

Trust has always been the cornerstone of banking. Yet, even as financial institutions accelerate their investments in artificial intelligence (AI), a new global study suggests that most banks are building their AI capabilities on fragile foundations, potentially putting that trust at risk.

Insights from the latest Data and AI Impact Report: The Trust Imperative by SAS Institute, with research conducted by IDC, reveal a growing disconnect between AI ambition and readiness across the banking sector.

Banking Leads in AI But Falls Short on Trust

Among the four industries analysed (banking, government, insurance, and life sciences) banking leads in both AI investment and adoption of trustworthy AI practices. However, the findings highlight a concerning imbalance.

While 23% of banks rank at the highest level of IDC’s Trustworthy AI Index, only 11% have achieved what the report defines as the ‘ideal state’ where strong internal confidence in AI aligns with demonstrably trustworthy systems.

Even more concerning, nearly half (47%) of banks fall into what IDC describes as the ‘trust dilemma’. These institutions are either underutilising reliable AI due to lack of confidence or over-relying on systems that have not been sufficiently validated.

According to Stu Bradley, Senior Vice President of Risk, Fraud and Compliance Solutions at SAS, the gap is significant.

“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. Roughly nine in 10 banks globally have yet to fully align trust with proof,” Bradley said.

Africa’s AI Opportunity Hinges on Trust

The report also highlights the Middle East, Türkiye, and Africa (META) region, where organisations are navigating similar challenges. Around 45% of organisations in the region face misalignment between confidence in AI and actual system trustworthiness, only slightly better than the global average.

For African markets, this issue is particularly critical. AI adoption intersects with broader priorities such as digital sovereignty, financial inclusion, and infrastructure resilience. Without deliberate investment in governance frameworks, representative datasets, and local talent, the region risks undermining its own digital progress.

On his part, Michel Ghorayeb, Head of Financial Services META at SAS, emphasised the urgency, “Across Africa, financial institutions and enterprises are at a pivotal moment. The region’s rapid digital adoption, combined with its young, tech-savvy population, creates enormous potential for AI to drive inclusion and resilience. But trust is as critical as currency.”

He added that embedding transparency and aligning AI systems with local realities will be key to unlocking sustainable innovation.

Rising Investment, Weak Foundations

Despite strong momentum in AI spending, the report reveals structural weaknesses that could hinder long-term success. Banks are outspending other sectors on AI, with 60% expecting budget growth between 4% and 20%, and 12% anticipating even higher increases. However, this investment is not being matched by improvements in foundational capabilities.

Key challenges include persistent structural weaknesses across the banking sector. Nearly one in five banks (19%) still operate with siloed data, the highest rate among all sectors studied, limiting visibility and efficiency. At the same time, 45% lack robust data governance frameworks, while 41% do not have centralised or optimised data systems, pointing to fragmented infrastructure. Compounding these issues, 42% of banks report shortages in specialised AI skills, further constraining their ability to effectively implement and scale AI initiatives.

While more than half of banks (52%) plan to expand their AI architecture and 43% aim to grow dedicated AI teams, only 31% are focusing on developing and refining AI models themselves—highlighting a misalignment in priorities.

Kathy Lange, Research Director for AI and Automation at IDC, warned, “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.”

Responsible AI Emerges as a Growth Driver

Contrary to common assumptions, the report finds that cost-cutting is not the primary driver of AI value in banking. Instead, product and service innovation is emerging as the leading source of return.

Organisations using AI to enhance customer experience reported the highest returns, $1.83 for every dollar invested, followed by those focused on market expansion at $1.74. Cost-saving initiatives delivered the lowest return at $1.54 per dollar.

Notably, organisations that prioritised trustworthy AI were 60% more likely to double their returns, underscoring the business case for responsible innovation.

Banks are also moving aggressively toward agentic AI systems, with nearly one-third planning increased investment in trustworthy AI to support more autonomous decision-making. However, this shift raises the stakes for governance and oversight.

Alex Kwiatkowski, Director of Global Financial Services at SAS, noted, “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.”

The Road Ahead

The report concludes that the future of AI in banking will not be defined by how much institutions invest, but by how responsibly they scale.

Banks that prioritise governance, transparency, explainability, and strong data foundations before scaling AI initiatives are more likely to succeed, not only in delivering ROI but also in maintaining the trust that underpins the entire industry.

As competition intensifies, those that fail to close the trust gap risk falling behind in an increasingly AI-driven financial landscape.