The World Doesn't Need More Echoes

I published this earlier this week on my LinkedIn newsletter and wanted to share it here as well, as I thought the message was worth getting out to as many people as possible.

Every executive I know is talking about AI strategy. They've read the McKinsey reports, attended the conferences and collected the playbooks.

They all sound remarkably similar.

And that's a problem.

AI isn't a checklist to be completed. It's not a framework you copy from someone else. Companies that are getting real value from AI are creating their own approaches.

The Echo Chamber Effect

Most AI strategies are echoes.

People see what big companies are doing and copy them. They implement the same tools everyone else is buying and follow the same "transformation roadmap" that worked for a completely different business.

Three forces push us toward copying others’ approaches:

• Fear of falling behind: When everyone's moving fast toward AI, following the crowd feels safest.

• Validation from familiar approaches: Boards approve strategies that sound like proven winners from other companies.

• Self-doubt about doing something different: "Who are we to think we can approach this differently?" sounds reasonable until different works better.

What Happens When Everyone Sounds the Same

I watched this play out at a recent AI meetup. There were twenty presentations. All had basically the same slides and buzzwords. They all had the same promises about "transforming operations" and "data-driven insights."

But ask any of those leaders about their specific challenges, their unique constraints, and/or their particular opportunities, and you get very different answers. Yet their AI strategies all looked identical.

The companies winning with AI have AI that works specifically for them. They are not copying others.

Finding Your Voice in AI Strategy

Your competitive advantage comes from having AI that fits your business, your customers, and your constraints.

This requires asking different questions:

• What problems do we see that our competitors miss?

• How do our specific constraints create opportunities?

• What would we build if we stopped worrying about looking different?

A manufacturing client taught me this lesson. They spent eighteen months building an AI system that looked exactly like what their biggest competitor was doing. They had the same features, same architecture and the same promises.

And it failed miserably.

The technology was fine. But it didn't fit how their people actually worked, and it didn't solve problems their customers actually had. It was a beautiful echo of someone else's voice.

When they rebuilt from scratch, starting with their unique manufacturing constraints, specific customer relationships, and their particular data advantages, the AI became transformative because it was authentically theirs.

Beyond Best Practices

Best practices have their place. They help you avoid obvious mistakes. But best practices are starting points, not destinations.

Your AI strategy should sound different from everyone else's because your business is different from everyone else's. Your constraints are unique, and your opportunities are specific to your business. Additionally, your culture has particular strengths.

The world has enough companies implementing generic AI strategies. It has enough leaders giving presentations that could be delivered by anyone in their industry.

What it needs is your perspective on how AI can serve your specific mission. Your take on what your customers actually need. Your voice in the conversation about what's possible.

Stop copying. Start creating.

If you found this post helpful, consider sharing it with another executive grappling with AI, technology, and data. If you want to explore AI and other Technology strategies, grab some time on my calendar, and let's chat.

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