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The Trojan Horse of AI and Data

I’ve spent the last few weeks meeting with business leaders, managers, and operations leads to discuss their data goals.

The conversations were insightful. Enthusiastic, even.

There was a genuine eagerness to adopt AI, automate reporting, and modernise decision-making. However, in meeting after meeting, a familiar theme kept emerging:

It is not the first time I have heard that. And it will not be the last time either. The issue is not a lack of innovation. Too many data and AI projects stop at the idea stage. 

POCs are built. Dashboards are shared. A buzz is created. But when we try to go live, everything falls apart.

Why?

 Because we’re celebrating the Trojan Horse—without knowing what’s inside.


The Illusion of Progress

POCs are valuable.

They’re the sketches before the final painting.

The drafts before the launch.

The tests before the flight.

They give teams a chance to experiment. To test ideas. To “see what’s possible”.

They’re short. Exciting. Visually stunning. And often… completely misleading

Because what you see in the demo isn’t always what you get in reality. Too many POCs are built with no real plan to scale. They win applause in internal demos, get featured in strategy slides, and then… quietly fade away.

They become the Trojan Horses of modern data and AI initiatives — elegant on the outside, hiding complexity, chaos, and confusion within. They are grandly wheeled into organisations with great fanfare, only to sit idle in the courtyard of innovation, never quite marching into battle. They give the illusion of progress without delivering lasting value. 

Why?


Why It Happens?

From my experience, here are six warning signs that your POC might not cross the finish line:

  1. No Clear Path to ProductionIf “what happens after the demo” isn’t defined, you’re rehearsing, not piloting.
  2. Lack of Business OwnershipWhen POCs are seen as “IT projects”, they struggle to get adoption from the people they’re meant to help.
  3. Data ChaosEven the smartest algorithms crumble without well-governed, contextual, accessible data.
  4. Over-engineering or OverpromisingTrying to showcase everything in one go leads to fragile, bloated prototypes.
  5. No Clear Business ProblemToo many POCs start with “let’s try” instead of “let’s solve this”. Cool tech doesn’t win. Solving real, pressing business pain does.
  6. IT and Business Speak Different LanguageWithout a translation layer, technical teams build what business teams can’t understand—and don’t use.


The Cure: Think Deployment-First, Not POC-First

If you’re committed to success, take a different approach:

  • Start with a real, painful business problem
  • Design the solution backward from how it will be used
  • Build with production in mind—scale, security, and sustainability
  • Don’t just demo value—deliver it


And above all, stop treating the journey like an R&D exercise. It’s a change initiative. A business transformation. A culture shift.


What Should the Horse Carry?

Instead of hiding complexity, our POCs should carry:

  • Trustable data
  • Reusable logic
  • Governed models
  • Cross-functional alignment
  • A clear path to production

That’s when the horse becomes a vehicle—not a trap.


Rethinking the Horse: Symbol of Strategy or Symbol of Surprise?

In business decks and keynote presentations, the horse head often appears as a clean, minimalist icon for strategy. It has become a visual metaphor for focus, planning, and disciplined execution.

But here’s the twist: the original Trojan Horse wasn’t just a tactic. It was the strategy. It was designed to look harmless. To gain access. To deceive.
And in many ways, that’s what happens today—not out of malice, but out of misalignment. We celebrate the horse—clean dashboards, beautiful POCs, confident AI pilots—as symbols of strategic maturity. But without governance, alignment, or a deployment plan, these become optics, not outcomes

Real strategy is about seeing the horse not as the victory — but as the vehicle.

So let’s elevate the metaphor. Let the horse head remain a symbol of strategy—but only when what’s inside is built to scale, governed, and usable.

One More Thought

When the Greeks wheeled in the original Trojan Horse, it wasn’t because they lacked imagination—it was because they had a plan. Unfortunately, many AI and data initiatives today skip the second part.

So next time someone says, “Let’s build a quick POC,” ask them: And what happens after that?

Because without an answer, you may just be building another wooden horse.

Final Thought

The goal isn’t to stop experimentation.
It’s to make experimentation meaningful, sustainable, and aligned with outcomes.

Because the only thing worse than no innovation… is the kind that looks like progress but leads nowhere.

We’ve all seen it:
A shiny proof-of-concept. A slick demo. Applause in the boardroom.

Then… silence.
No adoption. No impact. No rollout.

POCs are often touted as success stories in pitch decks, boardroom updates, and tech conference panels. But let’s call it what it is: theatre. A POC, in isolation, is rarely a measure of transformation. At best, it’s a lab experiment. At worst, it’s a distraction—soaking up time, talent, and attention with no path to production.

Like the original Trojan Horse, these showcases often come bearing promises—only to reveal, too late, their true nature: a misalignment of purpose, process, and practicality.

When POCs are built with no real plan to scale, they become the Trojan Horses of modern data and AI initiatives – elegant on the outside, anything but on the inside.

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