Notes from the field.

Short pieces on FinOps, cloud, AI cost, and the hiring side of all of it.

The “AI cost owner” is quietly becoming a real role.

Six months ago, AI spend was someone’s side responsibility—usually a platform engineer or a finance analyst who inherited it. Now we are starting to see dedicated mandates: someone whose actual job is to own how AI workloads are governed, attributed, and optimised. The problem is that most of these roles are being scoped by taking a cloud FinOps job description and pasting “AI” in front of it. The skills overlap, but they are not the same. Owning AI cost means understanding inference economics, model-selection trade-offs, and how agentic workflows scale with business volume—alongside the usual governance and stakeholder work. If you are about to open one of these roles, define it from the workload up, not from the old template down.

Cost and carbon are starting to be the same conversation.

For years, cloud cost and cloud sustainability lived in separate meetings—one owned by finance, the other by an ESG team that rarely touched infrastructure. That is changing. The same levers that reduce spend—right-sizing, scheduling, region choice, efficient model selection—also reduce emissions, and boards are increasingly asking about both in the same breath. For FinOps, this means GreenOps is less a separate discipline than a second lens on the same data. For hiring, it means the profile is broadening: the strongest candidates can speak to cost and carbon without treating them as competing priorities. We think that convergence is permanent, and worth designing roles around now rather than later.

FinOps X 2026 in San Diego: three things worth watching.

FinOps X returns to San Diego in June. Beyond the usual rate-and-discount sessions, three storylines deserve attention this year. First, how mature practitioners are absorbing AI workloads into their FinOps practice rather than handling them on a parallel track. Second, the slow shift from cost-reporting roles toward decision-support ones, which is quietly rewriting the job description. Third, what “FinOps Certified for AI” is doing to the senior talent profile. We’ll be watching, with hiring notes to follow.

The bill for AI is starting to look like a strategy problem.

Token costs that were rounding errors twelve months ago are now showing up in P&L reviews. Inference scales with usage; training scales with ambition. Both are starting to need governance, not just dashboards. The question for hiring teams is whether your current FinOps lead has the mandate—and the technical depth—to own AI workloads, or whether you need a different shape of person at the table. The role profile is broadening, and many existing mandates were written before that was true.

When the FinOps search isn’t working, the brief is the problem.

We hear this often: “we’ve been searching for six months and can’t find the right person.” Most of the time, that is not a candidate-pool problem. The brief was written before anyone clarified what the role actually needs to deliver, and now every shortlist looks plausible without any of them being a fit. The fix is not a wider search; it is a sharper mandate. The companies that get the right hire on the second attempt usually go back and rewrite the role first.

Who actually owns FinOps in your organisation?

Cloud spend is a finance issue and an engineering issue and an executive issue, which is exactly why it ends up being nobody’s issue. The most durable FinOps practices we see have one thing in common: a single role with explicit authority to make calls across both sides. Whether that sits under the CFO, the CTO, or a Cloud Centre of Excellence matters less than whether the role has been defined with real decision rights—before the first hire is made.