The Pain Customers Pay to Solve
AI and observability cost is the runaway line item of 2026.
The test is simple: what are companies actually struggling with that they will spend real money to fix? In 2026 there is a clear answer — the cost of AI and observability is exploding, and almost no one has it under control.
The wave (recent industry data)
Nearly everyone now manages AI spend
Up from roughly a third two years ago to almost universal today. "Control AI bill" went from niche to mainstream in a couple of years.
Trillions in AI spend
Global AI spend is now measured in the trillions, and organizations routinely overspend AI workloads by several times their original budget.
Optimization overtook expansion
For the first time, more enterprises name optimizing AI and cloud workloads their top priority than name growth. Efficiency is the new mandate.
A boardroom problem
Cost control has become an executive agenda item, not a back-office chore — FinOps is now a boardroom strategy for AI spending.
Industry forecasters warn that within a couple of years, large organizations face a meaningful rise in underestimated AI infrastructure costs from under-forecasting. The bill is not just big — it's surprising people.
Why this is VisiCore's pain to own
The generic FinOps wave is about AI spend. VisiCore's edge is the adjacent, equally painful, and far more familiar problem: Splunk and Cribl cost. It is the same buyer (the executive watching the bill), the same motion (find waste, cut it, keep it down), and it is work we already do better than anyone. We really are the best.
The buyer is already panicking
The executive who has to explain AI bill is the same one watching Splunk and Cribl spend climb. One conversation, two budgets.
We have the expertise they lack
"Use AI to cut your costs" is what every vendor says. We can actually do it — with expert, master Splunk and Cribl engineers. Moreover, in many places AI is now more expensive than the engineers it replaced. By focusing on true optimization, we reverse that trend and deliver real margin.
The honest caveat
The same research that proves the demand also proves most attempts fail: across thousands of organizations surveyed, the large majority have adopted AI but only a small fraction achieve working ROI. The money is real — but it goes to the few who embed AI into work they already do well. That is precisely VisiCore's posture. See the full evidence, both ways.
Next
Proof in dollars
Quest and HEB — customers paying for this outcome today.
For and against the thesis
The honest evidence on both sides, and why our framing survives it.
Sources
The figures above are drawn from recent, well-vetted industry research on AI and observability spend:
- FinOps Foundation — State of FinOps (AI-spend management; workload overspend)
- NVIDIA — State of AI (optimization as the top priority)
- SiliconANGLE — FinOps as a boardroom strategy
- IDC — the FinOps mandate for AI (under-forecasting risk)
- Deloitte UPMA briefing to VisiCore (adoption-vs-ROI gap)