THE SPARKLE TRAP

In the rush to adopt AI, many organizations have fallen into what I call the sparkle trap (others call it ‘sparkle sickness’): a scramble to collect and experiment with whatever’s trending, without stopping to ask whether the tool actually serves a business goal.

The result is often shadow AI applications employees quietly bring into their work without oversight or alignment. While intentions are usually good (“this saves me time”), the hidden costs add up: inconsistent workflows, fragmented customer experiences, unvetted data use, and subscriptions that no one’s really tracking.

Even leaders in the AI field remind us that the technology itself is not the point, but a means to an end. The real question is not “Which AI tools are we using?” but “What business problems are we solving?” That distinction has been blurred, in part, by the narrative AI providers have shaped. They’ve sold the story of inevitability — AI everywhere, AI for everything — when in reality, adoption without alignment often leads to waste and risk, not transformation.

If we’ve lost the plot, it’s because the plot was never tools in the first place. The real story is whether AI is improving our products, supporting our employees, and building trust with our customers. Without clarity on those points, we’re not adopting technologywe’re just adding noise.

The organizations that will thrive are the ones that slow down, cut through hype, and treat AI not as a shiny object but as one more tool to be carefully matched to the work that matters.