What is a Practical AI Strategy for Small Business?
The Practical AI Strategy Guide for Small Business
Most small business owners know AI could help their business, but they don't know how to start using AI in a way that produces consistent, measurable results. Many end up wasting money on random AI tools and experiments that never deliver real results. What they need is a practical AI strategy for small business—a focused approach that identifies the most important goals for their implementing AI into their business and a clear, step-by-step AI roadmap for achieving those goals. This guide presents a proven practical AI strategy developed through years of hands-on experience helping organizations implement AI that drive real impact. By following this strategic framework, small business owners, start ups, and solopreneurs will build the essential foundations that guarantees exceptional results from AI for years to come.
My name is Matthew Grote and I've helped numerous federal government agencies, defense contractors, and private businesses develop their AI strategy, first as an AI implementation lab director for federal government agencies and now as a private AI implementation consultant through Generate The Future. I can now bring these same proven strategy development methodologies and best practices to small and medium-sized businesses at a fraction of the traditional cost. The framework I'm sharing here will help you implement AI strategically in your business with minimal investment and maximum impact.
Your Two Essential AI Goals for Small Business Success
The very first step in developing an AI strategy is setting clear goals that align with your business priorities. Through my experience helping the Department of Treasury, Department of Defense, Department of Homeland Security, defense contractors, and numerous private businesses implement AI successfully, I've discovered what actually works for practical AI implementation. Organizations get the best results when they focus on two specific areas: using AI tools to help with critical thinking tasks and automating business processes that impact revenue. The practical AI strategy for small business is built around achieving these two goals:
Goal 1: Transform Your Most Time-Intensive Knowledge Work with AI
Identify one high-value knowledge work process that requires critical thinking and consumes significant time or creates bottlenecks—such as market research, proposal development, customer problem diagnosis, or strategic analysis—and develop a new AI-enhanced process using low cost AI tools that actually work like ChatGPT, Claude, or Gemini. Your team will develop baseline measurements for your chosen process (i.e. how much time it takes without AI) and measure your time savings as you experiment and optimize your new AI-enhanced process over time. Finally, you'll document your new AI-enhanced process and develop training materials so it becomes part of your company's institutional knowledge.
What success looks like (example nine month timeline):
- By Month 3: Cut process time by at least 30% by using your new AI-enhanced business process .
- By Month 6: Refine and improve your AI-enhanced business process to achieve 80% process reduction time.
- By Month 9: Document your new AI-enhanced business process, store it in a knowledge repository, and have your team trained in its use so it becomes institutional knowledge for sustainable AI adoption.
Goal 2: Automate Repetitive Business Processes
Select one high-impact repetitive process that directly impacts customer experience or revenue—such as lead follow-up, customer onboarding, or sales pipeline management—and fully automate it using no-code automation platforms like Make, Zapier, or N8N. These platforms allow you to connect your existing business tools and create automated workflows without requiring technical expertise.
What success looks like (example nine month timeline):
- By Month 3: Have a working prototype automation handling real business tasks and reducing manual work.
- By Month 6: Automation is effective and has a 90% uptime for a full month, delivering measurable results.
- By Month 9: Trained 1-2 team members to build and fix future automations, creating a scalable business automation system.
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Why Small Business AI Implementation Needs Both Approaches
Here's the thing—successful AI implementation for small business requires both approaches. Each one builds different skills your team needs for using AI in your business effectively. The AI-enhanced business process effort teaches your people how to collaborate with AI effectively and build prompts that are reusable. The automation work requires your people to think in terms of systems and learn how to connect tools and data to eliminate repetitive tasks. The two goals support each other as well. Collaborating with AI for complex critical thinking work teaches you and your team effective techniques for using AI that you can apply to other business challenges, and building automations will teach you to think in terms of processes, tools, and data which will improve how you collaborate with AI. They work together to produce the strategic outcomes that set you up for bigger AI wins down the road.
Strategic Outcomes: What This AI Strategy Sets You Up For
Successfully completing both goals gives you two things every business needs for AI success:
Practical AI Skills: Your team learns AI tools and automation platforms by solving real problems, not through abstract training. They develop hands-on experience with the platforms and approaches they'll need for future projects.
Proven Results and Confidence: You have documented wins that show your AI-enhanced business processes and automations work. This builds team confidence and makes it easy to justify expanding your AI efforts to other areas.
Think of this as your AI foundation. Once you prove you can save time consistently on critical thinking tasks and can successfully automate repetitive and costly processes, you're ready to tackle bigger opportunities. But you need both pieces—the AI collaboration skills and the automation capabilities—to build a sustainable and scalable AI advantage in your business.
The businesses that master these basics in their first year are the ones positioned to scale AI across their operations. The ones that skip this foundation or only focus on one area typically struggle to get the full value from any AI implementation investment.
Your Practical AI Implementation Roadmap
Once you've established your AI goals, the next step is developing a roadmap that shows exactly how to achieve them. A roadmap breaks down each goal into specific actions, timelines, and milestones, turning your strategy from an idea into an executable plan for implementing AI into your small business. It identifies what AI and automation tools you'll need, who will be responsible for each task, what order to tackle things in, and how you'll measure progress along the way. Without a roadmap, even the best goals remain wishes—with one, you have a clear path from where you are today to where you want to be.
I've developed another blog post detailing the Practical AI Implementation Roadmap which you can access here:
Matthew T. Grote
Conclusion
Implementing AI in your small business doesn't have to be overwhelming or expensive. By focusing on these two essential goals—AI-enhanced business process optimization and automations—you're building the foundation every successful small business AI adoption effort needs. The key is starting with clear, achievable objectives and executing them systematically over a realistic timeframe.
Remember, this isn't about becoming an AI company. It's about becoming a more efficient, capable business that strategically uses AI for competitive advantage. The businesses that take action on this framework today will have a significant edge over those that continue to experiment without direction.
Matthew T. Grote ran an AI implementation lab for the government that saved agencies millions of dollars. His work focused on identifying strategic outcomes for AI implementations, developing AI solutions, and creating practical frameworks for human-AI collaboration in high-stakes environments.
Business Inquiries: mgrote@generatethefuture.ai
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