AI strategy: Gain value without hiring a data science team

Generative AI (Gen AI) may feel like a buzzword, but it represents a genuine opportunity for small and mid-sized enterprises (SMEs) if approached strategically. You don’t need a dedicated data science team; you need a practical, intentional path forward.

Many platforms SMEs already use, like Google Workspace, Slack, Zoom, and HubSpot, now include generative AI features. These capabilities can streamline workflows around meetings, emails, and document drafting without any technical setup.

Additionally, AI-driven audio and video note-taking tools are transforming how SMEs manage meetings. By recording, summarizing, and analyzing unstructured meeting notes, these tools help uncover valuable insights and save significant time. It’s a quick win for improving productivity with minimal overhead.

A 2025 McKinsey report reveals that 78% of organizations now use AI in at least one business function, while 71% leverage Gen AI in specific areas like marketing, service ops, and development.

AI shouldn’t be adopted for its own sake. Begin by mapping workflows and identifying friction points.

Ask yourself: What tasks are repetitive? What customer issues recur most frequently?

Assess different functional areas and identify where you need support with productivity and efficiency. Whether it’s marketing, sales, operations, or customer service, pinpointing areas of greatest need will help prioritize where AI adoption will deliver the most value.

While enterprise AI solutions can seem tempting, they often require complex data structuring and advanced technical expertise, resources that most SMEs don’t have.

Public generative AI tools, like GPT models and other widely available platforms, offer a more straightforward and effective entry point. These tools are ready to use, require little to no technical setup, and can scale with your business needs.

Moreover, SME data is often poorly structured, making it difficult to run large language models (LLMs) effectively. Using public AI tools today sets the stage for more sophisticated enterprise AI solutions down the line, as you work toward meaningful business transformation, and data becomes more organized.

Read: The ROI of business transformation: How to measure success

It’s time to start viewing AI as a capacity multiplier. 

Sales teams can use AI to prioritize leads; support teams can resolve tickets faster; operations can automate routine reporting. You can accelerate adoption without adding headcount by incorporating AI training modules into your ongoing professional development programs.

This approach empowers your employees and fosters a culture of continuous learning and adaptability.

AI literacy doesn’t need to be reserved for technical roles. Cross-functional teams, including sales, marketing, and customer service, can all benefit from understanding how to use AI tools to improve efficiency and decision-making.

This investment in upskilling also pays long-term dividends by enhancing employee engagement and retention. As your business evolves, a well-trained team will be better equipped to leverage new tools, ensuring your company remains competitive in a rapidly changing landscape.

Read: How to hire in the age of AI overload

Too many AI pilots die on the vine. According to the same McKinsey report, fewer than 20% of companies track KPIs for Gen AI, yet those that do report stronger cost and revenue outcomes.

Start by setting simple metrics, like response times, output volume, and cost savings. And monitor them closely.

With these valuable data points, you can justify further investments, scale cautiously, and reduce risk.

None of this AI “magic” happens by accident. It works when tools are chosen deliberately, use cases are clearly defined, teams are trained, and results are tracked.

It’s about amplifying what you do, not reinventing your organization.

If you’re ready for AI to have an impact in your organization, consider these next steps:

Want help getting started? Talk to one of our advisors today.