Many small and medium-sized businesses (SMBs) are eager to use artificial intelligence to automate processes, improve forecasting and gain insights from their data. Yet without a clear strategy and shared ownership across IT, finance and operations, those efforts can quickly stall.
That’s where an AI center of excellence comes in. An AICoE provides a structured way to coordinate people, data and technology so AI initiatives deliver real business value — even for organizations without large IT teams or enterprise budgets.
While the concept is often associated with large enterprises, the underlying principles are just as relevant for small businesses. In fact, SMBs may be better positioned to succeed thanks to fewer silos and faster decision-making.
Still, adoption remains limited. Only 31% of CFOs surveyed have launched an AICoE, according to IBM’s 2024 CFO Study.
“The primary challenges mirror broader obstacles to AI adoption, with many organizations still focused on improving data quality and modernizing systems before they can effectively launch a CoE,” says Monica Proothi, a vice president and global finance transformation leader at IBM Consulting. “The payoff is worth it, but it requires the same level of discipline and cultural change as any successful AI initiative.”
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AICoEs Require Governance and Cultural Change Even for Small Businesses
For SMBs, governance may sound like an enterprise-only concern, but it’s critical at any scale. Without clear guidelines for how AI tools are selected, trained and used, even well-intentioned pilots can create risk or confusion.
IT leaders should help define:
- Who owns AI decisions
- How data is accessed and protected
- What guardrails ensure responsible use
Just as important is culture change.
“Perhaps most significantly, establishing an AICoE demands organizational culture change, requiring new ways of working, breaking down silos and embracing more agile approaches,” Proothi says. “While the potential benefits make these efforts worthwhile, this combination of technical, governance and cultural challenges could explain why many organizations have yet to make the transition — despite recognizing the strategic value of AICoEs.”
Securing Buy-In Across the Business
In many small businesses, IT and finance teams already wear multiple hats. But they can still operate independently when it comes to technology decisions.
IBM found that fewer than half of CFOs said their finance teams were closely involved in developing technology business cases.
AI cannot be a side project owned by IT alone.
“It takes a truly holistic approach,” Proothi says. “When standing up a CoE, IT leaders and finance leaders should be working in tandem to identify the best AI use cases — things like automating reconciliations, improving cash flow forecasting or streamlining reporting — and then prioritizing them based on business impact.”
Finance teams play a critical role because they understand the numbers, processes and constraints of the business. Their buy-in ensures AI projects focus on practical outcomes, not experimentation for its own sake.
Leaders can empower teams by:
“When all stakeholders — from leadership to frontline employees — align around the CoE’s vision, organizations can more effectively navigate AI implementation and maximize return on their technology investments,” Proothi says.
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Why an AI Center of Excellence Matters for SMBs
For small businesses, an AICoE doesn’t need to be a large, formal department. Instead, it acts as a central coordination point that helps IT leaders:
- Align AI initiatives with business goals
- Standardize tools, data access and governance
- Reduce risk while accelerating innovation
An AICoE provides a controlled environment to test AI use cases such as customer insights, forecasting or operational automation before scaling them across the organization.
What a company can do with AI depends on how it selects, governs and applies data. AICoEs establish those guardrails early, helping SMBs avoid costly missteps as adoption grows.
“This structured approach ensures that successful pilots can be efficiently expanded across the organization through standardized methodologies, reusable components and consistent governance frameworks,” Proothi says.
