Find the person who owns your AI agents
Companies don't fail at AI agents because of the tech. They fail because nobody owns it. We find, vet, and place the person who does — full-time, fractional, or done-for-you.
Agent leadership is the job of owning a company's AI-agent program end to end — deciding which workflows to automate, what to build versus buy, and who is accountable when an agent acts. Most stalled agent programs are missing this person, not the technology.
Are you ready to run agents in production?
Readiness is not a technology question. It is whether you have owned data, a defined workflow, a named accountable owner, and a measurable outcome. Missing any one of those is why pilots stall before production.
Four gates decide it, and a pilot stalls at whichever one it fails first:
- 1Owned data. The workflow runs on data you control, can grant access to, and can correct when it is wrong. Borrowed or locked data is the most common hard stop, and it is rarely discovered until the build is underway.
- 2A defined workflow. Someone can write down the trigger, the steps, the exceptions, and the handoff. If the process only exists in a person's head, an agent cannot be pointed at it — it has to be documented first, which is work most readiness assessments quietly omit.
- 3A named owner with budget authority. Not a committee and not a champion — one person who decides when the agent ships, when it is paused, and who answers for it acting wrongly. This is the gate most companies fail.
- 4A measurable outcome agreed in advance. Cost per completed task, handling time, accuracy, escalation rate — a number you commit to before the build, so you can tell success from activity afterwards.
Score yourself against the gates that actually predict whether an agent reaches production, then price the seat that would own it.
What does this site actually cover?
Four things, and deliberately not more: what the role is and what it pays, whether you are ready to hire for it, what the hiring market is doing, and what each agent workflow costs to build. Everything else on the site supports one of those four.
Agent leadership
What the role owns and what it explicitly does not, why programs stall without a single accountable owner, what the seat costs once you include search fees and ramp, where it should report, and the practical difference between hiring one person and buying agent software. Start here if you are deciding whether the role exists at your company yet.
AI readiness
Whether your data, workflows, ownership, and success criteria are in a state where an agent can actually reach production — scored against the dimensions the established frameworks agree on, and honest about where they disagree. Start here if a pilot has stalled and you are not sure why.
Agent economics
First-party numbers on the market: open agent-leadership roles counted from public job boards, the salary bands those postings publish, how fast companies are actually deploying agents, and how often those deployments fail. Every figure is dated, sourced, and reported as a floor rather than a census.
Implementation atlas
Workflow by workflow: what it costs to build, how long it takes, who is qualified to build it, and the specific ways that workflow fails. These are the four questions the vendor listicles never answer, because answering them does not sell a product.
What the agent-leadership hiring market looks like right now
Last verified July 2026A floor, not a census — roles filled internally or posted only to LinkedIn are not counted.
See the full Hiring IndexWhere agents earn their keep
View allOr start from your industry
Same workflows, filtered to the operating constraints of your sector.
The stack your Head of Agents runs
Tools are the supporting layer on this site, not the subject. The stack matters because someone has to own it — and picking infrastructure is downstream of deciding who is accountable for the program.
Browse the full directoryWhy is the role the subject here, and not the tools?
Because the tools are not the constraint. Agent frameworks, model providers, and orchestration layers are mature enough to build with today. What stalls programs is that no single person is accountable for deciding what to automate, what to ship, and when to stop.
The pattern repeats: a company runs a promising pilot, the pilot works in a demo, and then it sits. Not because the model was wrong, but because nobody owned the questions that come next — whose data it touches, who signs off when it acts autonomously, what happens when it gets something wrong in front of a customer, and which budget line pays for the next six months. Those are ownership questions. A better framework does not answer any of them.
So this site covers the seat rather than the stack: what the role is called and what it actually owns, where it sits in the org and which reporting lines fail, what it pays, whether it should be full-time or fractional, and how to tell whether your company is ready to hire for it at all. The tool directory is still here, because whoever takes the seat has to pick the infrastructure — but it is the supporting layer, not the point.
How do we source what we publish?
Every number carries an inline link to its source and the date it was published. Where we have no sourced figure, we say so and leave the field empty rather than estimating into it. That is the whole standard, and it is deliberately boring.
- Every statistic is dated and linked in the sentence that makes the claim — not collected in a footnote you have to reconcile yourself.
- Unknown is stated as unknown. We do not publish equity or total-comp figures, for example, because we have no sourced ranges for them. An honest base-salary band beats a padded total-comp number.
- Counts are floors, not censuses. The hiring data is built from public applicant-tracking boards, so roles filled internally or through search firms are invisible to it. Real demand is always higher than what we report, and we say that on the page rather than in the small print.
- Cost and timeline ranges on use-case pages are planning figures for scoping a project. They are not vendor quotes and should not be used as one.
- Revenue is demand-side only — companies pay for audits, matching, and placement. Nobody pays for a ranking, a listing position, or a favourable profile, and any commercial placement is labelled separately from editorial content.
The full collection and dating rules are on our methodology page, and our commercial relationships are listed in disclosures.
What are we not claiming?
We are not claiming a large vetted bench of available executives. The talent network is early and deliberately small, and we would rather say that plainly than imply supply we do not have.
We are also not claiming that hiring a Head of Agents is the right move for every company. For a lot of them it is not — the honest answer is a fractional engagement, a build partner, or waiting until a workflow is actually ready to automate. The readiness work exists precisely to reach that answer before anyone spends money on a search.