Small Banks Lead SMB AI Use, Study Finds

SAS says small banks, credit unions and lenders lead other small and midsized business sectors in AI readiness, though wider deployment remains limited by infrastructure, governance and fragmented systems. The SAS research, conducted by IDC, surveyed 1,600 SMB leaders across 28 countries and five global regions. Among small financial institutions, 64% use AI in IT, compared with 47% in finance and risk, 44% in marketing, 42% in customer service and 39% in product development. The findings position banking as a relatively advanced sector while showing the work still needed to bring AI into customer-facing and organization-wide operations.

AI Use Remains Concentrated

The AI for SMBs: Closing the Readiness-Reality Gap study defined SMBs as organizations with 100 to 999 employees in the United States and 100 to 499 employees in other markets. It found that financial institutions had the strongest strategic alignment, most established governance practices and greatest day-to-day use of AI among the five industries examined.

Still, 39% of small financial institutions said their infrastructure was not ready for broader AI deployment or was too expensive. Security, privacy and compliance were the top barrier to scaling AI, cited by 40% of respondents, while 33% named the lack of a single data, analytics and AI platform as a challenge.

“For smaller financial institutions, scaling AI does not mean recreating the technology architecture of a global bank. The smarter path is to focus internal resources where they create the most value and lean on technology and implementation partners to extend what the institution can accomplish on its own. The right ecosystem and the right collaborators can turn integration complexity into a manageable, even accelerated, path forward.”

Practical Priorities Take Hold

Respondents’ leading near-term AI priorities were automating core business processes and reducing costs through efficiency and automation, both selected by 30%. Improving data quality and integration followed at 28%, while 26% cited product and service innovation.

SAS said the most advanced institutions are moving beyond disconnected pilots by improving the shared data, governance and infrastructure needed to use AI across business functions.

“AI pilots often become islands of innovation. One team builds a high-impact fraud use case. Another launches a sharper risk model. A third automates a process. Each initiative delivers tangible benefits, but they don't add up to an AI strategy.

“Real transformation requires organizations to bridge those islands, connecting siloed functions and decisioning capabilities through shared data, governance and infrastructure, so AI travels farther and faster across the organization.”

Assessment Tool for Smaller Institutions

Small and midsized banks and credit unions can use SAS’ AI Readiness Calculator, an 11-question assessment based on the SAS and IDC AI Readiness Index. The tool assesses planning, building, enabling and executing, then provides a personalized report on strengths, readiness gaps and recommended next steps.

SAS will also host an Oct. 16 webinar, AI Readiness vs. Reality: Moving Beyond the Hype in Banking and Insurance, focused on practical and responsible AI strategies for banking and insurance organizations.

Building Beyond Isolated Pilots

The research points to a clear opportunity for smaller financial institutions: extend AI from IT into finance and risk, marketing, customer service and product development. SAS’ AI in Banking resources cover applications across risk, fraud and customer experience for institutions planning that next stage.