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Artificial intelligence (AI) is the most disruptive technology of our time. However, as more organizations capitalize on this technology, managed service providers (MSPs) could experience substantial growth.

Small and medium businesses (SMBs) may lack the internal resources and skills to develop and implement their own AI solutions. Consequently, you could secure loyal, long-term customers by serving this need. However, crafting AI strategies for small businesses can be challenging. Here’s how you can approach it effectively.

Find a niche that AI serves

While 39 percent of small businesses plan to implement artificial intelligence, 77 percent say they don’t know enough about it or its benefits. In light of this gap, you should start by identifying a specific use case for an AI solution relevant to your market.

Automating time-consuming tasks

Process automation is one of the most common AI use cases. It’s easy to see why, as employees spend an average of 60 percent of their time on non-value-adding tasks.

To fill these gaps, you could create a solution that automates data entry, scheduling, or basic customer outreach. Chatbots are a popular specific option under this umbrella, as many SMBs don’t have enough staff for 24/7 human customer service.

Data analytics

AI solutions that can pull actionable insights from data also benefit many small businesses. SMB analytics solutions must be specific, purpose-built systems since more general, versatile models may be too expensive or require too much technical expertise.

Inventory management artificial intelligence is a good fit for retailers or logistics businesses. Customer management artificial intelligence is another excellent option for many small businesses.

Security and compliance

Small businesses can also benefit from AI in security and compliance workflows. These are rising concerns for SMBs, but many lack the staff or technical skills to manage them manually.

AI can automatically identify and flag suspicious discrepancies, monitor network activity, and contain breaches. These solutions are particularly valuable for businesses in tightly regulated industries like health care and finance.

Focus on AI affordability

Once you’ve identified a clear use case for your AI solution, consider your market’s limitations. Costs are among the biggest for small businesses, especially as many SMBs plan to cut tech spending amid economic headwinds.

While Artificial intelligence enables long-term cost savings, the high initial expenses give many SMBs pause. You can address this barrier by stripping AI models back, sacrificing multifunctionality for cost-efficiency. Don’t build an expensive AI solution that can do it all. Develop a small, lightweight one that does one thing very well.

Open-source AI tools and pre-trained models are a huge help. Tailoring an existing AI model to a specific use case will save significant time and money in development, justifying a lower cost for your customers.

Consider data limitations

Data availability is another common barrier for small businesses trying to capitalize on artificial intelligence. Many machine learning models need a lot of information to work well, so smaller companies may not have enough on hand to see a meaningful return with these technologies.

One possible solution is to focus on building an artificial intelligence system that doesn’t require as much data. Pretrained models and narrow AI may not need as much information to deliver results. Alternatively, you could help SMB customers by supplying synthetic data to train and refine AI solutions.

Synthetic data has the added benefit of not reflecting real-world information while matching its performance. Security-minded businesses or those worried about privacy and ethical issues will benefit the most from this method.

Educate customers

After constructing a focused, affordable, and non-data-heavy artificial intelligence model, you should focus on customer education. SMBs will only invest in AI if they see its value for their company. Demonstrating its efficacy in areas where small businesses face challenges is crucial.

Small businesses are less likely to be familiar with AI, so be specific about its benefits and capabilities. Avoid using technical jargon in your marketing materials to make the solution more approachable to non-experts.

This is also a good opportunity to address common questions and concerns. Go over why your AI solution is secure, ethical, and reliable. Explain how businesses can use it to improve their employees’ work instead of replacing them.

Provide ongoing support

Similarly, MSPs must offer ongoing technical support to their customers. Roughly 40 percent of small businesses have trouble filling labor shortages, and digital skills are some of the most in-demand. Consequently, SMBs are less likely to have enough in-house data and AI knowledge and experience to implement it effectively on their own.

Don’t just sell SMBs an AI solution. Help them integrate it into their current workflow. Offer troubleshooting and ongoing optimization services. This ongoing support will help clients see more significant returns and build customer loyalty.

Adopting an as-a-service business model can help you maximize this opportunity. It may also make AI services more accessible to small businesses that can’t afford a larger upfront expense.

Small businesses need the right-sized AI solutions

Artificial intelligence is a potential game-changer for any organization, but small businesses won’t see equal benefits from the same solutions as larger ones. They need options that fit their unique needs. This presents both a challenge and an opportunity for MSPs.

You can craft a more relevant solution for this market when you recognize small businesses’ barriers to AI adoption and implementation. Doing so will let you bring the power of AI to companies who need it most.

Did you enjoy this edition of Tip Tuesday? Check out the others here.

Photo: / Shutterstock

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Devin Partida

Posted by Devin Partida

Devin Partida is the Editor-in-Chief of, and is especially interested in writing about finance and FinTech. Devin's work has been featured on AT&T Cybersecurity, Hackernoon and Security Boulevard.

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