The AI Trap: When Outputs Overshadow Outcomes

Stop chasing AI's flashy outputs and start focusing on real business outcomes. Here's why getting caught up in AI's capabilities rather than its business value is a dangerous trap – and how to avoid it.

Author

Eric Brown
February 06, 2025

Aerial view of a complex maze-like pattern made of dark metallic walls on a snowy white background, with a single person in yellow clothing visible in the center, emphasizing the challenge of finding direction amid complexity.

In the maze of AI capabilities, it's easy to get lost chasing outputs. The key is finding your way to meaningful business outcomes. Photo by Dan Asaki on Unsplash

I saw something interesting on LinkedIn recently that really resonated with me. Kudos to Christoper Rathgeb for this nugget. The post highlighted three simple but powerful points about AI:

  • AI isn't the answer to everything

  • Don't get lost in the output

  • Stay focused on the OUTCOME

This got me thinking about a pattern I've been seeing lately with clients and organizations rushing to implement AI.

Everyone’s getting in AI's outputs. "Look at this amazing text it generated!" or "Check out this image it created!" But we're missing something crucial. The actual business outcomes we're trying to achieve.

I've seen this movie before. Back in the early days of big data, everyone was obsessed with collecting massive amounts of data without really thinking about what they'd do with it. Today, we're doing the same thing with AI – implementing solutions just because we can, not because we should.

Let me share a recent example. A friend of mine spent months implementing an AI chat-bot for customer service. The outputs looked great – coherent responses, quick reply times, sophisticated language. But when she looked at the outcomes? Customer satisfaction actually dropped. Why? Because they were so focused on the AI's ability to generate responses that they forgot about what customers really wanted and needed. Their customers (and all customers?) wanted quick solutions to their problems.

Here's what I tell my clients about avoiding the AI output trap:

  1. Start with the end in mind. What specific business outcome are you trying to improve?

  2. Measure what matters. Track business metrics, not just AI performance metrics

  3. Question every AI implementation. Ask "Could we achieve this outcome without AI?"

  4. Keep humans in the loop. AI should augment, not replace, human judgment

AI is a tool, not a strategy.

When you find yourself amazed by what AI can do, take a step back and ask yourself: "Is this actually moving us closer to our desired business outcomes?"

That's the real conversation we should be having about AI. Not what it can do, but what it should do to drive actual business value.

What are your thoughts? Are you seeing organizations get caught up in AI outputs while losing sight of outcomes?

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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