Why We Should Stop Talking About "AI" (Seriously)
Article | June 2025
"AI" has become the ultimate buzzword, a catch-all term that means everything and nothing. We throw it around to describe chatbots, self-driving cars, and complex data analysis, as if they're all the same. This vague language isn't just lazy; it's actively sabotaging our understanding, our investments, and our future.
Think of it like this: AI is as broad and deep as Chemistry. When you say "chemistry," are you talking about simple elements like water (H2O) or silver (Ag)? Or are we diving into organic chemistry, biochemistry, quantum chemistry, or advanced chemical engineering? All are "chemistry," but they solve wildly different problems with distinct properties and incredibly complex applications.
Lumping all AI together is just as absurd and unhelpful.
The Real Problem with "AI"
This massive oversimplification leads to:
Wasted Money: Companies invest in the wrong "AI" because they don't understand the specific tool needed for their specific problem.
Failed Expectations: Hype builds for "AI," then crashes when a general tool can't solve every complex business challenge it was never designed for.
Bad Decisions: Leaders can't make smart choices about strategy or regulation when they don't differentiate between a simple algorithm and a powerful, autonomous system.
Unnecessary Fear: Treating AI as one big, mysterious entity fuels general anxiety instead of allowing for targeted, informed discussions about its specific uses and implications.
From Buzzword to Breakthrough: How to Talk About AI
To truly unlock AI's potential, we need to get specific. The starting point isn't "Let's get AI!" It's:
Understand Your Problem or Opportunity: What precisely are you trying to achieve? Is it to streamline a bottleneck, reduce costs, improve customer experience, or uncover new market insights? This fundamental "why" must be clear to all your humans first.
Then, Explore the Tools: Only once the problem is crystal clear can you explore if a specific type of "AI" – or any other technology – can be part of the solution.
Get Specific About the "AI": If AI is indeed part of the answer, then specify: Is it a Large Language Model (LLM) for content generation? A computer vision system for quality control? A predictive analytics algorithm for forecasting sales?
Connect to Human Understanding: Crucially, ensure your teams understand how this specific AI tool will address their identified problem or opportunity, making their work better or delivering a clearer benefit.
AI isn't a single solution. It's a vast, intricate toolkit, with specialized branches just like chemistry. Only by understanding its diverse "chemistry" – by using precise language, focusing on specific applications, and grounding it in human-understood problems and opportunities – can we move beyond the hype and truly build a smarter future.