Crafting Your AI Strategy: A Practical Guide for SMB Executives

With AI technologies rapidly evolving and new tools like DeepSeek, Capilot, and ChatGPT emerging almost every few months, it's no surprise that many business leaders feel overwhelmed when thinking about how to develop an AI strategy for their companies.

When technology changes at such a fast pace and lacks clear, actionable roadmaps for real-world implementation, SMB executives can easily get caught up in a flood of tech hype and disconnected discussions. These conversations, often heavy on buzzwords but light on practical use cases, can add to the confusion. This is where many businesses find themselves today.

This article aims to provide SMB leaders with straightforward guidelines for cutting through the noise and adopting AI strategies that make sense. We’ll focus on two practical approaches to get you started on your AI journey.

Two Approaches to Explore Your AI Strategy

1. Adopt Ready-to-Use AI Tools with Minimal Risk and Investment

This approach involves implementing pre-built AI tools or AI-powered business solutions created by tech vendors. Examples include HR software with AI-based CV screening, online meeting software with AI assistants, and marketing platforms that help with AI-assisted content generation. The process for integrating these tools is similar to implementing an ERP or CRM system—essentially focusing on the right configuration for your specific needs.

From a workflow perspective, this approach begins with identifying an AI-powered solution that enhances employee productivity within a specific task. When evaluating the work optimization with AI, explaining how the AI implementation will improve employees’ work and performance is critical for gaining buy-in and building trust with future users.

If your company is curious about AI but doesn’t have a dedicated budget for tech initiatives, starting with AI-powered tools can be a great way to mitigate risks and test the waters.

How to Choose Your First AI Tool:

• Identify repetitive and manual tasks: Focus on tasks that are time-consuming and can easily be automated. For example, if employees spend a lot of time manually transferring information from forms, images, or PDFs into other software systems, this is a prime candidate for automation. AI tools like Extacta.ai can read information from images and match it to specific fields in your software.

  
  

• Match the right AI tool to the task: Once you’ve identified the task, research AI solutions that can address it and reach out to vendors for demos. Verify whether the tool integrates seamlessly into your current workflows.

  
  

• Ensure compatibility: Make sure the AI tool is compatible with your existing software systems and won’t cause disruptions across interrelated workflows.

  
  

• Estimate costs: Consider how many people will use the AI tool and how often. Vendors can provide cost projections, but keep in mind that costs can grow as usage increases, especially if your employee base expands.

  
  

2. Build In-House AI Technology

For businesses focused on service or product innovation, developing in-house AI technology can be a more fitting approach. This strategy is ideal if you have unique business processes or need a specialized solution that doesn’t exist in the market. Additionally, building AI in-house means you retain ownership of the intellectual property (IP), which can be leveraged for commercialization.

Building an in-house AI solution is fundamentally different from adopting ready-made tools. It involves a dedicated Research & Development (R&D) phase, with a focus on creating custom AI models tailored to your business needs. This strategy requires careful evaluation of use cases, technical feasibility assessments, and sufficient budget allocation to navigate each stage of development.

While in-house AI solutions start with a higher initial investment, they offer long-term strategic benefits and sustainable advantages, such as positioning your products or services uniquely in the market, improving the customer experience, and solving problems that traditional technologies can’t. With proprietary AI models, your company gains the flexibility to evolve and diversify the use of AI over time.

How to Start Building Your In-House AI Strategy:

• Evaluate innovation opportunities: Assess all potential use cases and their long-term impact on the business. Start with one specific use case to focus your efforts.

  
  

• Develop a data strategy: Identify the data required to train your AI models. Ensure that you have sufficient, high-quality data, and create a strategy to collect and organize it to maximize the success of your AI initiatives.

  
  

• Assemble the right team: Form a team that combines technical experts with business leaders. Business team members should validate the AI model’s results in real-world scenarios and provide valuable feedback to the technical team.

  
  

• Set clear milestones: Use lean agile methodology to define measurable milestones for the project. This allows you to make course corrections and ensure progress with regular iterations.

  
  

Conclusion

Developing the right AI strategy for your company should never be a one-size-fits-all approach. Depending on your business goals for the next 3-5 years, your AI strategy will likely combine both of the approaches discussed above. By gaining a holistic understanding of AI, you’ll be in a better position to evaluate your options and make informed decisions that align with your company’s vision and needs.