Small and medium-sized businesses (SMBs) face a stark reality in 2026: artificial intelligence offers a path to compete with giants, but fragmented efforts often yield little return. A dedicated AI Center of Excellence (CoE) provides the coordination needed to harness AI for automation, forecasting and insights, even with constrained budgets. According to BizTech Magazine, only 31% of chief financial officers have launched such centers, per IBM’s 2024 CFO Study, citing data quality and system modernization as barriers.

“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, vice president and global finance transformation leader at IBM Consulting, as quoted in BizTech Magazine. SMBs, however, hold advantages like fewer departmental silos and quicker decision-making, positioning them to scale AI faster than larger firms.

Recent data underscores urgency. A Business.com survey of 1,009 U.S. workers at firms under 250 employees shows AI investment rising to 57% in 2025 from 42% in 2024, with 64% planning employee upskilling programs, per Business.com. Yet without structure, these investments risk stalling.

Governance Forms the Foundation

Establishing governance stands as the first pillar for any SMB AI CoE. This involves defining ownership for AI decisions, data access protocols and guardrails for ethical use. Proothi emphasizes in BizTech Magazine: “Perhaps most significantly, establishing an AICoE demands organizational culture change, requiring new ways of working, breaking down silos and embracing more agile approaches.” For resource-limited SMBs, this means lightweight frameworks rather than bloated bureaucracies.

Microsoft’s Cloud Adoption Framework recommends integrating AI practices into existing teams if a Cloud CoE exists, securing executive sponsorship for budget and credibility, as detailed in Microsoft Learn. Steering committees with business and IT leaders ensure alignment, holding monthly reviews with C-suite access.

Deloitte urges moving from ad hoc pilots to holistic strategies, creating use-case backlogs and nurturing them through the CoE for an “intelligent enterprise,” according to Deloitte US.

Securing Cross-Functional Buy-In

IT and finance must collaborate to identify high-impact use cases like automating reconciliations or cash flow forecasting. “It takes a truly holistic approach,” Proothi notes in BizTech Magazine. “When standing up a CoE, IT leaders and finance leaders should be working in tandem to identify the best AI use cases… and then prioritizing them based on business impact.” Fewer than half of CFOs currently involve finance in tech decisions, per IBM data.

Aligning stakeholders from executives to frontline workers maximizes returns. “When all stakeholders align around the CoE’s vision, organizations can more effectively navigate AI implementation and maximize return on their technology investments,” Proothi adds. For SMBs, this alignment leverages finance’s grasp of processes and constraints for practical outcomes.

KPMG outlines a process where the AI CoE reviews use cases by complexity and value, ranking factors like data needs, compliance risk and business impact before prioritizing with engineering teams, as described in KPMG.

Value Through Pilots and Scaling

An AI CoE acts as a central hub standardizing tools, data and governance while testing pilots in areas like customer insights or operational automation. “This structured approach ensures that successful pilots can be efficiently expanded across the organization through standardized methodologies, reusable components and consistent governance frameworks,” Proothi states in BizTech Magazine.

ANSR advises starting with small, clear projects for quick wins to build credibility before scaling, securing executive sponsorship for alignment, per ANSR. Ideas2IT highlights assessing AI maturity, defining governance and prioritizing use cases in partnership with enterprises.

IDC notes organizations using AI CoEs seek competitive edges through knowledge sharing and partnerships, with UST embedding data engineers alongside analysts for rapid execution, according to IDC.

SMB Advantages in Action

Adoption surges: 89% of small businesses leverage AI for tasks like automation, per Intuit & ICIC in ColorWhistle, while a Salesforce survey finds 91% of SMBs using AI report revenue boosts. Forbes predicts SMBs will form “AI Studios” linking tools to objectives, ending basic chatbots by 2026, as in Forbes.

On X, OpenAI’s Greg Brockman shared an “AI Jam” mentoring 1,000 SMB owners—from accountants to hair salons—in building tailored tools. BizTech Magazine highlights SMBs unlocking documents and enhancing chatbots with existing tools.

Tredence stresses focusing on high-value use cases with cross-functional teams blending technical and business skills, per Tredence.

Overcoming Barriers with Discipline

Challenges persist: data quality, cultural shifts and low adoption rates. PwC’s 2026 predictions emphasize responsible AI gaining traction, while Upwork research shows SMBs scaling AI report strong results, per HR Executive.

Microsoft, Oracle and AWS provide blueprints: Oracle’s CoE centralizes expertise for pilots and production scaling; AWS addresses scaling beyond proofs-of-concept via CoEs. For SMBs, starting vendor-hosted with simple guardrails suits limited resources, as BigSur.ai advises.

Proothi’s payoff rings true: discipline and change yield efficiency and innovation. As IDC forecasts 50% of SMBs adjusting IT budgets for AI by 2027, lean CoEs position them to thrive.