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Small Banks Lead SMB AI Adoption but Infrastructure Lags: SAS/IDC Study

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Small Banks Lead SMB AI Adoption but Infrastructure Lags: SAS/IDC Study

Cary, N.C. – September 25, 2026 -- Small financial institutions rank ahead of similarly sized insurers, government bodies, health care providers and life sciences firms on AI adoption, with 64% of small banks and credit unions using AI in IT operations, according to a new SAS and IDC study.

The report, "AI for SMBs: Closing the Readiness-Reality Gap," surveyed 1,600 small and midsized business leaders across 28 countries in five regions. SMBs were defined as organizations with 100 to 999 employees in the U.S. and 100 to 499 employees elsewhere.

AI adoption in small banks concentrates heavily in IT functions

Among small financial institutions, 64% report AI use in IT, compared with 47% in finance and risk, 44% in marketing, 42% in customer service and 39% in product development.

Infrastructure costs block 39% of institutions from wider AI rollout

About two in five respondents (39%) say their infrastructure is not ready, or is too costly, for broader AI deployment. Security, privacy and compliance concerns rank as the top barrier to scaling AI, cited by 40% of small financial institutions. One-third (33%) point to a lack of a unified data, analytics and AI platform as a further obstacle.

Banking outpaces other SMB sectors on AI governance and integration

Despite these constraints, financial institutions showed the strongest strategic alignment and most established governance practices among the five SMB industries examined, and the greatest integration of AI into daily operations.

Chris Marshall, Vice President of Financial Services at IDC, said smaller institutions do not need to replicate the technology architecture of a global bank. He said the smarter path is focusing internal resources where they create the most value and leaning on technology and implementation partners to extend capacity.

Banks prioritize cost reduction and process automation over novel AI use cases

Banking respondents' top near-term AI priorities favor practical capabilities: automating and streamlining core business processes (30%), reducing costs through efficiency and automation (30%), improving data quality and integration (28%), and increasing product and service innovation (26%).

Alex Kwiatkowski, Director of Global Financial Services at SAS, said AI pilots often become isolated "islands of innovation" — a fraud use case here, a risk model there — that deliver tangible benefits individually but fail to form a coherent AI strategy without shared data, governance and infrastructure connecting them.

SAS releases AI Readiness Calculator for banks and credit unions

SAS has launched an 11-question AI Readiness Calculator, based on the SAS and IDC AI Readiness Index, allowing small and midsized banks and credit unions to benchmark their AI maturity across planning, building, enabling and executing stages. Each participant receives a personalized report on strengths, gaps and next steps.

SAS will present findings at Sibos in Miami from Sept. 28 to Oct. 1, with sessions on AI readiness, trust, agentic AI, payments and financial crime at Booth I073. A follow-up webinar, "AI Readiness vs. Reality: Moving Beyond the Hype in Banking and Insurance," is scheduled for Oct. 16.

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