Mike Biwer is the CEO at Cavallo.
I talk to business leaders who are feeling pressure from their boards and peers to “do something with AI.” The problem is that “implement AI” isn’t a business objective. Before you invest in anything, you still need to know what you’re trying to improve.
That’s where some healthy skepticism around AI is warranted. AI is a tool, not a strategy or an identity. Buying a product because it carries an “AI” label may generate some initial excitement, but that label tells you very little about whether the technology will improve the business. Without a clear problem worth solving and the operational structure to support it, AI can easily become an expensive investment with little to show for it.
First Things First
I’ve made the same argument about ERP migrations. When someone tells you that you need to move to a new platform, it’s worth asking who benefits from that decision. You still need your own business case.
AI deserves the same scrutiny. A vendor’s enthusiasm for AI isn’t a reason for you to invest in it. Being AI-first offers no inherent advantage. I saw that challenge firsthand at an industry AI conference last year. Distributors arrived already trying to figure out what AI meant for their businesses. Then they walked into a room with 40 technology providers with booths offering AI solutions. Some of the more candid executives asked a reasonable question: Where do I even start?
You don’t start by choosing among 40 AI solutions. Instead, you need to decide what problem is worth solving. Maybe you need to reduce the manual work required to process orders or your sales team needs better information when making pricing decisions. Maybe customers are waiting too long for answers because your team has to pull information from multiple systems. Define the operational problem and the outcome you want first. Then evaluate the technology.
If AI is the right tool, use it. If not, ignore the hype.
The Widening Gap
The divide between strong and weak operators is already there. Some companies have spent years building the discipline to use data and technology to improve the business. They know what they’re trying to accomplish, measure performance and adjust when something isn’t working. My expectation is they’ll use AI intelligently for the same reasons they’ve been able to use other technology intelligently.
Think about two companies using the same AI tool. Company A has clean data, understands its processes and knows where it wants to improve. It can tell whether the technology is helping them. Company B is working with disconnected data, inconsistent processes and no clear measure of what success looks like for them.
The technology is available to both of them. But if Company B keeps doing the same old thing, AI isn’t going to change much.
AI doesn’t manufacture operational discipline; it amplifies the discipline a company already possesses. Put simply: AI doesn’t tell you what smart things to do, it allows high-performing teams to do smart things massively faster. If your processes are already sound, AI accelerates that success. If your operations are chaotic, it just executes bad habits at a higher speed.
Most companies will eventually have access to many of the same AI capabilities. What they do with them is another story.
Skepticism, Not Resistance
Before long, the AI label itself will probably lose much of its power. I’ve joked about seeing products like an “AI putter” (a real thing). When everything starts carrying an AI label, you start wondering how much the label really tells you.
I expect AI will eventually become part of the fabric of technology in much the same way internet connectivity did. We won’t need to call everything AI-powered. We’ll care about what the product does and whether it makes the business better. Until then, skepticism is essential, and it needs to work in both directions.
I’ve seen plenty of headlines suggesting AI and agents are going to kill traditional software. A business leader could read enough of that and conclude, “Why would I invest in core software right now?” But freezing tech investments is reacting to AI hype in the opposite direction.
The reality is that an AI agent is only as good as the underlying systems it interacts with. AI may sit on top of existing systems, operate within them, connect information across them or fundamentally change workflows. Without reliable platforms managing your inventory, order flow or financials, an agent lacks the clean data and operational context required to be useful.
Healthy skepticism means resisting both extremes. AI will change how businesses operate, but every prediction about what it will replace or make obsolete doesn’t deserve to drive an investment decision. Technology will keep changing. New capabilities will emerge, some of today’s tools will disappear, and AI itself will become less of a category companies talk about and more of something embedded in the technology they already use.
Don’t aim to build an “AI company.” Build an exceptional business with clean data and reliable processes. Then let AI earn its place by doing what it does best: taking your smartest operational moves and scaling them at speed.
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