Global trade is complex. Even if you do not ship internationally, you likely rely on foreign suppliers, so events that happen halfway around the world can trickle down to you. What are you supposed to do when disruptions can happen anytime, anywhere? The answer is artificial intelligence. This technology can help you identify gaps, predict changes and find solutions. 

Common Supply Chain Problems Businesses Face

Though the supply chain is integral to business operations worldwide, it has periods of instability. If that makes you feel vulnerable, you are not alone. According to KPMG’s Future of Supply Chain Report, 47% of companies believe they are susceptible to disruptions. Even the largest, best-funded enterprises cannot predict the future.  

Causes of Small Business Supply Chain Disruption

Extreme weather events, fluctuating consumer demand, natural disasters, raw material shortages and factory fires are generally unpredictable, so they can have considerable impacts regardless of frequency or severity. 

New upheaval has emerged in recent years. For example, no one knew how to respond when COVID-19 shut down cities and forced workers home. Around 20% of logistics professionals reported pandemic-related setbacks.

After global trade took a hit due to the pandemic, it took years for some companies to find alternative suppliers and trade routes. In 2024, many economists and logistics industry leaders were optimistic about the supply chain’s future. However, they have had to temper their expectations in 2025 with trade wars on the horizon. 

Now, tariffs and trade restrictions are ramping up. Like many business owners, you may be concerned about what this means for you. According to The Economist, 69% of companies believe they can use neutral countries to fill the supply gaps created by trade conflicts between world powers. However, 63% worry regulatory changes could undermine this strategy. 

Small Businesses Are Using AI to Solve This Issue

Whether you are dealing with the aftermath of a factory fire or the fallout from a global trade war, making contingency plans can feel impossible. After all, how are you supposed to have the answers when natural disasters, workplace accidents and policy changes are so capricious? Fortunately, you do not need to handle things on your own. 

Recent technological advances put AI-driven solutions at your fingertips. An advanced model can analyze thousands of images, documents, news articles or emails in seconds, giving you in-depth insights faster than any human or software. 

A machine learning model can automatically monitor trade policies, analyze customer demand or manage your inventory. It essentially thinks for itself, so the process is mostly hands-off. Once it finishes, you can request summaries, predictions, recommendations or insights. Since it is purpose-built, it can do whatever you need it to. 

You do not need to be exceptionally technology savvy to use AI tools. Their user-friendly, no-code interfaces let you ask questions and make requests in plain language. Instead of learning how to code or figuring out settings, you type or talk as you would when speaking to another person. 

Since AI is effective and easy to use, its popularity has skyrocketed. According to Forbes Advisor, 30% of business owners already use it in their supply chains. If you are considering joining their ranks, you must first understand how to implement this technology. While the process is relatively straightforward, it can be confusing if you lack technical knowledge. 

How Small Businesses Can Adopt Supply Chain AI 

These tips can help you implement AI to avoid supply chain disruptions and improve your return on investment.  

1. Identify a Use Case Before Integration

AI is most effective when you have a specific purpose in mind. Would you use it to develop contingency plans? Do you need to translate messages from suppliers? Could your customer service team benefit from help answering frequently asked questions? Clarify its purpose before proceeding with implementation. 

2. Hire an AI Engineer or Choose a Vendor 

Hiring an AI engineer to build a model from the ground up costs around $120,000 to $200,000 yearly. Though this investment is pricey, you benefit from having full creative control and retaining ownership of the final product. Vendors charge $30,000 to $300,000, depending on project scope. A cheaper third option is a subscription-based software-as-a-service solution.

3. Establish a Baseline With Metrics

How can you tell how effective your machine learning model is unless you establish a pre-implementation baseline? Track metrics like on-time delivery rate, freight invoice accuracy, return rate and inventory-to-sales ratio. 

4. Assign Auditing Responsibilities 

An algorithm is only as good as the data you feed it. You could skew its output by giving it outdated, irrelevant or inaccurate information. The best way to avoid this issue is by auditing data sources and model performance. 

Since most small businesses have fewer than four employees, you may have to hire someone or do the work yourself. If you get access to the AI through a third-party vendor, they generally take on that responsibility for you. 

Solving Supply Chain Pain Points With AI Tools

If events like the pandemic and tariff announcements have taught small business owners anything, it’s that a “normal” supply chain is a myth. However, that does not mean you have to deal with disruption-related losses. AI lets you quickly pivot when the unexpected occurs to maintain communication with your suppliers and keep your customers happy.