As a company that provides ERP solutions, we began trying to demonstrate to small and medium-sized businesses that artificial intelligence (AI) had the potential to be a transformative technology back as far as 2016.
For years, many struggled to grasp the benefits that AI could provide. A strong tech stack can give businesses the edge they need to compete with larger rivals. Large and small businesses struggled to envision the capabilities that AI could add to existing applications such as analytics, forecasting and cybersecurity.
AI seemed too new and unproven to many of them because AI at the time seemed more like technology that required a data scientist rather than a typical IT worker. When it came to talent, the obstacles were even more stark. Even businesses with nine-digit revenues often struggle to hire AI professionals.
That situation has changed over the past several years. Services like OpenAI’s ChatGPT, IBM’s watsonx and Google’s Gemini have not only opened the eyes of businesses and consumers eyes to new use cases for AI but also convinced organizational leaders that these tools can be user-friendly.
Midmarket companies don’t have endless resources to experiment with AI. They need the best bang for their buck. The most immediate and extensive opportunities exist at the intersection of e-commerce and AI. That’s because e-commerce can touch nearly every aspect of an organization’s supply chain — from ordering to marketing to delivery.
Here are a couple of examples from my own experiences that show how AI and e-commerce can work together.
* Streamlining shipping. We worked with Mariani Packing Company — a well-established, decades-old dried fruits provider — to help it develop new processes to handle unique customer requirements. These sorts of processes can become cumbersome to manage and more difficult to maintain during upgrades, but they also generate a lot of data and represent patterns that AI can use to recognize these customers’ unique requirements — leading to streamlined processes and reduced customized code. Advanced analytics helped the company reduce human touch and eliminate errors in supply processes, achieving an efficiency rate of 99.8%.
* Improved site search functionality. Kinnunen Sales & Rental, serving everyone from heavy industrial contractors to DIY homeowners, had over 42,000 SKUs across multiple locations and was growing quickly. We worked with Kinnunen to help the company turn to a single, centralized database that synched its website and app — providing customers with accurate inventory and pricing information in real time. This, coupled with AI enabling predicted purchasing based on data analytics, allows customers to buy and get the tools they need without issue to quickly get back to work.
Midmarket companies now have access to significantly more AI capabilities such as intelligent chatbots to automate responses to complex queries. One advantage AI chatbots have over traditional chatbots is that they can keep users more engaged on product pages, ensuring that the product is front of mind as the buyer gathers information. AI chatbots can also be trained to understand industry-specific terminology using retrieval-augmented generation (RAG) to more effectively learn from past interactions.
Small and midmarket businesses appear to be on a buying spree when it comes to AI. A May 2024 survey from tax and advisory firm RSM found that 89% of midmarket executives planned to boost budgets for AI technology — with nearly three-quarters of that spend focused on generative AI. A 2023 report from the National Center for the Middle Market (NCMM) found that 80% of midmarket firms planned to use AI in the future but only 34% were doing so.
The surveys also hint at companies’ main challenges and concerns when adopting AI — governance and data security as well as integration with the existing technology stack. Companies also want a clear use case for AI deployment. AI is a tool, but it’s only useful if it solves a problem.
These are two surveys with two different methodologies, so their results may not be directly comparable. However, I think they have the direction of the trend right, which underscores the importance of another finding from NCMM: Early adopters of AI have grown faster.
That’s a sign that these challenges can likely be overcome.
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