The €7.5B Bet That Came Up Empty
In 2012, Europe's Large Hadron Collider confirmed the Higgs boson existed. Good news: the physics worked exactly as predicted. Bad news: that's all it did.
Thirteen years later, the 27-kilometre supercollider has detected precisely zero particles beyond the Standard Model—the 1970s framework that explains the 25 known elementary particles. No dark matter candidates. No explanation for matter-antimatter imbalance. No solution to the "hierarchy problem" that has puzzled physicists since 1981.
Particle physicist Adam Falkowski predicted in 2012 what would follow: "The number of jobs in particle physics will steadily decrease, and particle physicists will die out naturally." He wasn't wrong. Major physics publications have declined. Research funding is stagnant. The crisis is real.
The AI Pivot (Sound Familiar?)
With no new particles to find, the LHC turned to AI pattern recognition to measure existing particle interactions more precisely. The logic: maybe novel particles are hiding in statistical noise at lower energy levels, detectable only through indirect evidence.
So far, better measurement has only confirmed the existing model more accurately. Each precision improvement narrows the space where new physics could hide.
Matt Strassler, a Harvard-affiliated physicist, remains optimistic about "hidden valleys" in the data. "There's a huge amount of unexplored territory," he told Quanta. But that's hope, not evidence.
What This Means for Technology Investment
The parallels to enterprise technology are uncomfortable:
The big infrastructure bet. Massive capital deployed on the promise of breakthrough capabilities. Quantum computing, anyone?
Incremental improvements mask the core problem. AI makes existing processes more efficient, but doesn't solve the fundamental limitations. This is table stakes, not transformation.
The pivot to lower expectations. When the moonshot fails, reframe success as "unexplored territory" and "opportunities at lower levels." Watch for this language in vendor roadmaps.
The slow decay. Falkowski's prediction—declining jobs, natural attrition—describes many enterprise technology functions today. Legacy modernisation teams. On-premise infrastructure groups. Roles tied to architectures that didn't deliver promised breakthroughs.
The Pattern Recognition
Particle physics spent decades theorising about particles that should exist to make the mathematics elegant. When experiments disagreed, the field faced a choice: accept nature is less elegant than hoped, or keep searching in increasingly unlikely places.
Enterprise technology makes similar bets on elegant architectures—microservices, zero trust, composable infrastructure—that should solve problems in theory.
The question physics forces us to ask: when does persistence become sunk cost fallacy?
Particle physics will continue. The LHC runs until 2035 at minimum. But the field has fundamentally changed from discovery-driven to measurement-focused. From breakthrough to optimisation.
Worth noting: they're still spending billions. The technology itself works perfectly. It's just not delivering the transformation everyone expected.
We'll see.