How Small Businesses Can Build a GenAI Strategy for Immediate Impact and Sustainable Growth

Short-Term GenAI Wins for SMB IT Leaders

Phil Carter, general manager and group vice president for AI, data and automation research at IDC, recommends identifying high-impact use cases across three broad categories: personal productivity, functional use cases and industry-specific applications.

For SMBs, personal productivity tools such as Copilot and other AI assistants are often the easiest starting point. They can help employees summarize meetings, draft proposals and streamline reporting without causing major workflow disruption.

Functional use cases — such as contact center automation, IT support assistance or code generation for small development teams — can also drive fast ROI. Industry-specific use cases, from automated compliance documentation to AI-assisted design work, may provide differentiation in competitive markets.

However, SMB leaders must balance value, cost and risk. Traditional ROI calculations are no longer enough.

“With GenAI, the added dimension is risk — and that covers everything from governance and compliance to the potential for things to go wrong, as we’ve seen in early pilots,” Carter says.

Even when deploying off-the-shelf platforms, safeguards are critical. Smaller organizations may not have dedicated AI governance teams, but they should designate clear ownership across IT, security and business stakeholders.

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Mature organizations — regardless of size — embed governance from the beginning. That means involving decision-makers during use case selection, proof-of-concept planning and rollout.

“There is a clear correlation between AI pioneers and their focus on governance,” Carter explains. “The more mature, the more the levels of governance are well thought-out, documented and practiced.”

For SMBs, this doesn’t require bureaucracy; it requires clarity: Who owns AI? What data can be used? What risks are acceptable? By answering these questions early, smaller businesses can innovate confidently.

By starting with targeted use cases, aligning AI initiatives to measurable business outcomes and embedding governance from day one, SMBs can generate quick wins while building organizational confidence.

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Building a Scalable, AI-Ready Tech Stack for Small Businesses

As GenAI initiatives mature, SMBs must shift from isolated pilots to a repeatable strategy that supports sustainable growth.

Carter describes this future state as an “AI-ready tech stack.” For smaller organizations, that means prioritizing flexibility and scalability over large, capital-intensive infrastructure projects.

Cloud platforms such as Amazon Bedrock, Microsoft Azure OpenAI and solutions powered by NVIDIA enable SMBs to access advanced AI capabilities without building data center–scale environments. Working with a trusted partner such as CDW can help right-size these investments and avoid overprovisioning.

An AI-ready foundation includes:

• Clean, organized and accessible data
• Infrastructure that avoids bottlenecks at the network, server and storage level
• Systems designed to support emerging “agentic” AI capabilities

Rather than building an enterprise “AI factory,” SMBs can focus on creating repeatable frameworks for evaluating, testing and deploying AI use cases. The goal is consistency and acceleration — not complexity.

“You want it to be repeatable, but also to drive acceleration using agentic capabilities,” Carter says. “It’s about mass-producing models, insights and systems.”

Integrating GenAI Into Core SMB Business Systems

For long-term value, GenAI should move beyond productivity tools and connect to core systems such as ERP, CRM and financial platforms.

SMB IT leaders should evaluate whether existing software vendors offer AI-enhanced capabilities or whether AI-first alternatives provide greater efficiency and cost savings.

“You don’t want to be putting together a $100 million ERP transformation and be worried that in three years, you will realize it could have been done in half the time and cost with AI agents,” Carter says.

While SMBs may not face nine-figure transformations, the principle remains: Technology decisions made today should account for AI’s rapid evolution.

Finally, governance must remain central as adoption expands. Even in smaller organizations, AI governance should extend beyond IT to include leadership, HR, legal and operations.

“AI governance should not sit in IT,” Carter says. “It needs to sit under the business — ideally under the CEO — with contributions from legal, compliance, HR, security and IT.”

By investing in scalable infrastructure, integrating GenAI into core processes and treating governance as a shared responsibility, SMB IT leaders can build a strategy that balances innovation with accountability.

“It must be owned by every employee, just like information security became a shared responsibility,” Carter says.