The Case For Healthy Skepticism In The Age Of AI

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.