AI FOMO Drives Wasteful Tech Spend as Returns Falter

Context Companies across Nigeria and beyond are racing to showcase AI initiatives, often at the expense of proven, simpler solutions. The pressure to appear cutting‑edge fuels investments that rarely match business needs, leading to costly mis‑allocations.

Key Facts - Between 15% and 25% of technology spend in most enterprises funds duplicate systems that add no measurable value. - In 2025, 85% of organizations increased AI budgets, yet the average time to recoup those costs has stretched to about four years, far beyond the traditional 7‑12 month horizon for new tech. - A Boston Consulting Group survey shows 88% of firms have launched AI pilots, but only 5% have realized substantial financial returns; the remaining 60% report no material value despite significant outlays.

What It Means The data points to a capital allocation problem rather than a technology flaw. Fear of missing out on AI—often called AI FOMO—pushes leaders to favor sophisticated, non‑deterministic models even when a deterministic fix would be cheaper and faster. When AI solutions cannot meet required accuracy levels, additional human oversight erodes any cost advantage, turning a promised efficiency gain into a hidden expense.

Enterprises must adopt a disciplined pre‑build diagnostic: verify that the problem is truly AI‑solvable, confirm that model performance meets business thresholds, and calculate total inference costs, including required human review. Early termination criteria should be built into project plans to stop spending before sunk‑cost fallacy takes hold.

Looking ahead, firms that tighten governance around AI investment decisions and prioritize fit‑for‑purpose solutions are likely to shorten payback periods and avoid the wasteful spend that now plagues the sector.