The Two Biggest AI Pitfalls for Small and Medium-Sized Businesses
If you’ve been paying any attention to the tech space recently, you’ve heard about AI. From OpenAI’s ChatGPT to Google’s Gemini, and my personal favorite, Anthropic’s Claude, AI has dominated the conversation—often accompanied by CEOs making a wide range of outrageous promises.
What Is AI, Really?
Those of us entrenched in the tech industry often take for granted how the general public perceives AI and its limitations. When I talk to fellow developers about database solutions, we’re discussing whether to stick with MS SQL Server, cut costs with Postgres, or consider a document database like Firebase or MongoDB. But to most people, a database is just a really, really big Excel file.
Why does this matter?
Because when the average person hears “Artificial Intelligence,” they think Terminator. Combine this limited understanding with the exaggerated claims of tech executives, and you have a recipe for misinformation.
This isn’t to say that AI tools aren’t useful—they absolutely are—but we need to step off the hype train for a moment.
Tools like ChatGPT and Claude are, at their core, Large Language Models (LLMs)—sophisticated programs trained on vast amounts of data to generate responses based on patterns.
They don’t think.
They don’t have a personality.
They don’t learn or act independently of human input.
There’s ongoing debate about whether LLMs are a stepping stone toward true Artificial General Intelligence (AGI), but that’s a discussion for another time.
AI and Small to Medium-Sized Businesses
The internet is flooded with articles touting AI as the next big thing, offering solutions in search of problems. I won’t rehash all of that here.
From what I’ve seen, small and medium-sized businesses (SMBs) primarily use AI tools as digital assistants—drafting emails, writing proposals, summarizing documents, and more. And while these tools are useful, there are two major pitfalls SMBs need to watch out for.
1. Overdependence
Emerging research suggests that excessive reliance on AI can lead to skill degradation across multiple domains. This isn’t just a business risk—it’s a personal one. The more we outsource critical thinking and expertise to AI, the harder it becomes to function without it.
For businesses, this risk extends to vendor lock-in. Many companies already depend on cloud providers like Microsoft Azure or AWS, but switching away from them—while difficult—is at least possible. AI, on the other hand, poses a bigger challenge.
Right now, most AI companies aren’t profitable. Their focus is on acquiring users, which often means lower costs and generous free tiers. But history has shown that once dominance is achieved, the focus shifts to profit. We’ve seen this with Uber, Airbnb, and even Google Search to some extent.
So what happens when your AI tool of choice:
- Raises its prices to unsustainable levels?
- Fails unexpectedly?
- Alters its policies in a way that doesn’t align with your business needs?
If AI becomes deeply embedded in your core operations, switching away may be next to impossible.
2. Lack of Oversight
Many of my clients come to me with a similar story:
- They’re a product manager or entrepreneur with a great idea.
- They hire a developer or try using AI to build their product.
- It doesn’t work the way they want.
- They have no idea why.
AI-generated code is impressive, but it’s far from perfect. Getting AI to fix its own mistakes can be frustrating, and debugging AI-generated code often takes longer than writing it from scratch. Skilled developers are still necessary—especially for SMBs that may lack the capital to course-correct when things go wrong.
Final Thoughts
AI is a powerful tool, but like any tool, it comes with risks. For SMBs, the key is strategic adoption—leveraging AI where it makes sense while ensuring that your business remains adaptable, resilient, and not overly dependent on any single technology.
If you’re considering integrating AI into your business and want to do it the right way, let’s talk.