Your AI Strategy is Backwards (And Everyone Knows It)

You wouldn't renovate your kitchen just because granite countertops are popular. 

You'd renovate because your current setup doesn't work for how you cook, entertain, or live.

Yet I keep seeing brilliant executives approach AI exactly like interior design trends - adopting it because it's what successful companies are supposed to have, rather than because it solves a fundamental operational challenge.

I was brought in to assess a company's AI strategy. They had 12 use cases, all with compelling business value calculations from a major management consulting firm. 

After asking a series of questions about their organizational maturity and capabilities, I had to deliver uncomfortable news: 9 of those 12 projects were impossible to implement with their current resources (data, infrastructure, and talent).

That's when I realized we were treating AI like a luxury purchase instead of a strategic tool.

After falling into the trap of countless deployments myself,  I've seen first hand how organizations rush into AI for all the wrong reasons. Here are the warning signs that suggest your organization might be heading down the wrong path:

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Warning Sign #1: "Everyone Else is Doing It"

When your primary motivation is keeping up with competitors rather than solving actual business problems, you're setting yourself up for failure. 

You wouldn't buy a hammer just because your neighbor has one; you buy it because you have wood to connect and nails to drive.

Warning Sign #2: Confusing AI with Basic Math

I can't tell you how many times I've heard, "We're AI powered” when they're really just running SQL scripts with massive business rules behind the scenes. 

If your "AI" is simply automating calculations you're not leveraging artificial intelligence - you're doing math with fancy marketing.

Warning Sign #3: Technology First, Problem Second

The biggest red flag? When someone asks, "How can we use AI?" instead of "What business problem are we trying to solve?"

Here's the reality: AI should never be the starting point of your conversation. 

The conversation should always begin with identifying genuine business problems that have resisted traditional solutions for years - problems where conventional approaches have been tried, tested, and proven insufficient.

Before considering AI, ask yourself:

• Have we tried proven, traditional methods to solve this problem?
• Why haven't those methods worked?
• Is this problem significant enough to warrant the complexity and investment that AI requires?
• Do we have the organizational maturity to deploy and maintain an AI solution?

Remember: AI isn't magic. It's not a silver bullet. It's a sophisticated capability that works best when applied to the right problems by organizations that understand both its capabilities and limitations.

What's your take? Have you seen organizations rush into AI for the wrong reasons? I'd love to hear your experiences in the comments.

Until next time,

Sol

Every Friday morning, I deliver 1 actionable insight to help you navigate the post-AI landscape, simplifying complex transitions into a clear path for business impact. You can click here to subscribe.