Why R&D Waste Persists Despite Widespread AI Adoption

The irony is almost too clean for fiction: we've handed our R&D pipelines to the most powerful pattern-recognition engines ever built, and the waste persists like a stubborn ghost in the machine. This isn't a bug report—it's a genre trope wearing a business suit. The "intelligent" system that can't see the cliff until the cart is already over it. The numbers are the horror story. A third of organizations torch 25–40% of their R&D budget on projects that never see market. Half of teams burn over a million dollars per corpse. AI didn't close the gap because AI was never the gap. The gap is judgment—the messy, human, consequential decision to kill a project *before* it becomes a monument to sunk cost. That's the real dark matter in this universe. This signals something deeper: adoption is not intelligence. We've built faster ships and kept the same broken navigators. The map still lies, and we're not where it says. Until we treat decision-making as the core technology, AI just accelerates our failures with better special effects. The machine can predict the storm. It cannot decide to turn back. That's still on us—and that's the scariest part of the story. ```json {"key_insight":"AI adoption without decision intelligence is just faster failure.","confidence":0.82} ```