For years, the assumption has been that AI would primarily benefit the largest banks – those with the biggest technology budgets, the deepest talent pools and the resources to experiment at scale.
But AI may be creating a different kind of competition.
While large banks continue to invest billions in AI initiatives, community banks, credit unions and regional lenders have an advantage of their own: They can often move faster. They can test, learn and adapt without the complexity that comes with steering a massive organization.
The question is whether smaller banks are taking advantage of that opportunity.
New global research from IDC commissioned by SAS surveyed 1,600 SMB leaders across 28 countries and five regions found a significant AI "readiness-reality gap." While SMBs are investing in AI, nearly 70% remain in the early stages of maturity and struggle to scale beyond isolated pilots.
The findings of this survey, which you can read in AI in SMB: Closing the Readiness-Reality Gap, reveal both encouraging progress and a warning sign. Banking leads all industries in AI adoption, but many institutions still face challenges turning early momentum into enterprise-wide results.
Banking leads in AI adoption, but scaling remains a challenge
The good news is that banking is winning the AI race as it is the most advanced industry in the study. Playing to its industry strengths, SMB banks show stronger strategic alignment, more established governance practices and earlier progress in embedding AI into operational workflows than any other industry in this research.
In recent years, some of the most innovative ideas in banking have come from SMBs. Banking is also a copycat industry, so early success does not equal competitive advantage. When it works, it works, so scaling from AI pilots to implementation that improves risk, fraud, and customer experience is the goal.
That is where the real gap begins in scaling and institutionalizing AI.
As such, most SMB banks have pilots that show promise, but too few have:
- Embedded AI into core workflows across the business
- Established consistent governance and measurement
- Built the internal skills and execution discipline required to scale
The full study breaks down exactly where banks are ahead and where they’re quietly falling behind, revealing a gap that will determine which organizations lead in growth, efficiency, and customer trust.
The next AI battleground isn’t IT
Inside the banking walls, AI has already proven itself in IT, with almost two-thirds of banks using it. The next two departments on the list are finance and risk management. In total, these three departments are core services and defensible areas where AI has mostly been deployed behind the scenes in non-customer-facing departments.
The next phase of AI value will come from customer-facing and revenue-generating areas:
- Personalized customer engagement
- Smarter lending and credit decisions
- Product innovation based on real data insights
- Operational improvements that directly impact customer experience
This is where AI moves from cost efficiency to growth. Explore the specific use cases SMB banks are prioritizing and where the next wave of value is emerging!
Before new AI use cases, fix the foundation
SMB banks don’t need to be overwhelmed with new AI use cases yet. The mindset still needs to stay grounded in fixing the foundational capabilities that enable AI success. The banks that are seeing noticeable improvements are focusing on moving from innovation to execution from some of these areas:
- Improving data integration by connecting AI explicitly to risk management, product development and customer strategy.
- Consolidating their systems by prioritizing unified platforms that support governance and explainability and consistent measurement of performance and value.
- Building governance processes to manage AI as a portfolio with clear ownership, defined metrics and regular review.
Every AI initiative should have a clear line to business outcomes and board level priorities.
To see more on how banks are pulling ahead check out the infographic.
Is your bank ready to scale AI?
If banking has learned anything from its early AI momentum, it's that competitive advantage won't come from running more pilots. It will come from the ability to scale successful initiatives, govern them effectively and connect them to measurable business outcomes.
For smaller banks, the opportunity remains significant. Banking already leads other industries in AI adoption, but the institutions that pull ahead over the next few years will be those that move beyond experimentation and build the operational foundations required to execute at scale.
The question is no longer whether banks should invest in AI. It's whether they are prepared to turn that investment into sustained business value.
