AI strategy: Gain value without hiring a data science team

If Generative AI (Gen AI) sounds like something reserved for large enterprise companies, think again. Organizations of all sizes are now leveraging these tools to help accelerate and automate tasks such as repetitive work and internal communications. A 2025 McKinsey report reveals that 78% of organizations now utilize AI in at least one business function, while 71% leverage Gen AI in specific areas, such as marketing, service operations, and development.

Whether you’re running a small or medium-sized enterprise (SME), there are many ways to begin building your Gen AI strategy. Before we dig in, let’s start with some good news: you don’t need a dedicated data science team, just a practical, intentional path forward.

Did you know that you might already be using platforms that have some elements of generative AI features built in? Google, Slack, Zoom, and HubSpot all offer their generative AI features. These capabilities can streamline workflows related to meetings, emails, and document drafting, eliminating the need for technical setup. It doesn’t stop there; 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 a significant amount of time. It’s a quick win for improving productivity with minimal overhead.

Like any successful business investment, AI shouldn’t be adopted for its own sake. If you’re adding specific tools to stay on top of the latest trends or get ahead of the competition without first researching whether those tools are a good fit, it’s time to take a step back. Begin by mapping workflows and identifying areas of friction. Consider the most repetitive tasks; the things that take key employees away from more important work. Can these be safely automated?

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 you prioritize where AI adoption will deliver the most value for your business.

While enterprise AI solutions can seem tempting, they often require complex data structuring and advanced technical expertise, resources that most SMEs lack (and are costly to acquire). Meanwhile, 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. However, if you choose to experiment with public models, be aware that many lack the same level of privacy and security as their enterprise-level counterparts and should never be fed confidential company data, IP, PII, or any other sensitive information. With the proper protocols in place, experimenting with public AI tools can lay the groundwork for more sophisticated enterprise AI solutions in the future, as you work toward achieving meaningful business transformation and data becomes more organized.

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

It’s time for business leaders to start viewing AI as a capacity multiplier, not a people-replacer.  Sales teams can utilize AI to prioritize leads, support teams can resolve tickets more efficiently, and 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 utilize AI tools to enhance efficiency and informed decision-making. Such an investment in upskilling also pays long-term dividends by enhancing employee engagement and removing the fear of AI tools. As your business evolves, an AI-fueled team will be better equipped to leverage new technologies, 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 previously mentioned McKinsey report, fewer than 20% of companies track KPIs for Gen AI, yet those that do report stronger cost and revenue outcomes. Begin by establishing straightforward metrics, such as response times, output volume, and cost savings. And monitor them closely. With these valuable data points, you can justify further AI investments, scale cautiously, and reduce risk.

None of this is magic. Successful AI implementation doesn’t happen by accident. It works when tools are chosen deliberately, use cases are clearly defined, teams are trained, and results are tracked. Remember, it’s about amplifying what you do, not reinventing your organization.

Here’s a quick checklist to help you get started in your AI adoption:

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