10 min. read

An AI project manager plans and leads the deployment of AI systems inside an organization, and is accountable for carrying each one from approved pilot to governed, measurable production across every vendor and model involved. The template below defines that role from public sources, including O*NET’s Information Technology Project Manager profile, the NIST AI Risk Management Framework and PMI’s 2026 PMP exam outline, so HR can post it with light editing.

Copy what fits, cut what doesn’t, and keep the accountability lines. They’re what turns a project manager job description into an AI project manager one.

Key facts

$116,580 2025 U.S. median wage in the BLS group that includes IT project managers (Computer Occupations, All Other, SOC 15-1299). Source: O*NET OnLine, BLS data.

7% Projected 2025–35 job growth for project management specialists, which BLS rates “much faster than average.” Source: BLS Occupational Outlook Handbook.

80%+ Share of AI projects that fail by some estimates, about twice the rate of IT projects without AI. The most common root cause RAND found was misunderstanding the problem to be solved. Source: RAND.

62% Average wage premium for workers with AI skills in 2026, up from 57% a year earlier. Source: PwC 2026 Global AI Jobs Barometer.

Why a standard project manager job description isn’t enough

O*NET’s profile for Information Technology Project Managers lists 21 tasks, from managing execution against budget, schedule and scope to selecting vendors and running risk assessments. Every one of them still applies to AI work. PMI is moving in the same direction: its July 2026 update raised Business Environment from 8% to 26% of the PMP exam and added AI to project-based scenarios. The project management foundation is the floor for this role, not the whole of it.

What a standard description doesn’t do is assign the decisions an AI deployment forces. Every AI system in production needs someone who owns four answers:

Unattended authority. What is the system allowed to do without a person reviewing it?
How is its output judged, before launch and every month after?
When must it hand a decision to a human, and which human?
Ownership after the vendor. Who runs it once the vendor’s team rolls off?

If the job description doesn’t name an owner for those four, the organization risks finding out who owns them during the first incident. We cover that handoff in who owns your AI after go-live.

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The other gap is upstream. In RAND’s research the most common root cause of AI project failure was a misunderstanding of what problem the project was meant to solve. So the template makes framing the problem an explicit responsibility, not an assumption.

The AI project manager job description template

Bracketed text is yours to fill in. The responsibilities follow the structure of NIST’s AI Risk Management Framework (Govern, Map, Measure, Manage) on top of the project leadership the PMP certifies; our guide to AI project manager competencies explains each area.

Template: AI Project Manager

Job title

AI Project Manager. Alternates: AI Delivery Manager; AI Program Manager (for a portfolio across vendors); Senior AI Project Manager.

Occupational classification (for HR systems): Information Technology Project Managers, O*NET-SOC 15-1299.09.

About the role

[Company] is deploying AI across [functions]. We’re hiring an AI Project Manager to lead those deployments from approved use case to governed production. You’ll own the delivery plan, the risk decisions and the handoff to operations for each AI system in your portfolio, working with our business teams, data and engineering staff, security, compliance and AI vendors. You won’t build models. You’ll make sure the systems we buy and build work inside our organization, safely, and keep paying off after go-live.

What you’ll do

Lead the project

• Build and maintain the delivery plan for each initiative: scope, milestones, budget, staffing and work breakdown structure.

• Coordinate AI vendors, consultants and vendor-embedded engineers so their work fits our data, systems, security requirements and change control.

• Track data readiness, integration dependencies and access approvals as schedule risks, not afterthoughts.

• Report progress, risks and realized value to sponsors and governance bodies in plain language.

Govern: set authority and accountability

• Set, with risk and compliance partners, what each AI system may do without human review, when it must escalate to a person, and who that person is.

• Maintain each system’s risk register, mapped to our AI governance framework (for example, the NIST AI Risk Management Framework or ISO/IEC 42001) and to the regulations that apply to us.

• Make sure every system has a named internal owner before the vendor or project team rolls off.

Map: frame each use case

• Work with business owners to define the problem each AI use case solves, the decision it supports and the measurable result that will count as success.

• Develop the business case, including cost-benefit and return-on-investment analysis, and revisit it at each stage gate.

Measure: decide how it’s judged

• Make sure evaluation criteria and acceptance tests are agreed before launch.

• Track each system’s performance and risks after go-live against the success measures set at the start.

Manage: launch, run and improve

• Make sure monitoring, incident response and a switch-off path are in place at launch.

• Lead change management and training for the teams whose work each system changes.

• Plan and run the handoff from vendor or project team to the internal owner, with documentation and runbooks in place.

• Recommend whether to scale, fix or retire each system based on results.

What you’ll bring

Required

• [3–5] years leading IT, digital or data projects with cross-functional teams and external vendors.

• Working knowledge of how AI systems are built, evaluated and monitored: enough to ask engineers and vendors the right questions. Coding isn’t required.

• Experience managing scope, schedule, budget and risk under real security or compliance constraints.

• Clear writing and speaking for both executives and technical staff.

Preferred

• PMP® certification, or CAPM® for earlier-career candidates.

• Experience taking an AI or automation system into production, including post-launch monitoring.

• Familiarity with an AI risk framework (NIST AI RMF, ISO/IEC 42001) and with [sector] regulations.

• Agile or iterative delivery experience.

• Completion of a Registered Apprenticeship in information technology project management.

How we’ll measure success

• First 90 days: an inventory of the AI initiatives in your portfolio, each with a named owner, a stage and a success measure.

• First 6 months: at least one AI system moved from pilot to production with agreed evaluation criteria, monitoring and an operational owner.

• First year: a rising share of approved AI use cases reaching production, and realized value reported against the original business cases.

Compensation

$[minimum]–$[maximum] per year. [General description of benefits.] [Other compensation: bonus, equity.]

Some jurisdictions require all three in the posting. Maryland, for example, requires a good-faith pay range, a general description of benefits and any other compensation for roles performed at least partly in the state, including remote roles open to Maryland-based workers (Maryland Department of Labor). Our AI project manager salary guide shows how to set the range.

Reporting

Reports to [Head of PMO / CIO / Chief Data or AI Officer]. Works with [AI governance committee, business sponsors, vendor partners].

How to adapt the template

One vendor or many? If the role covers a single vendor’s rollout on a fixed date, cut the portfolio language and scope it as a project role. If it spans vendors, model types and years, keep the governance and handoff responsibilities and title it AI Program Manager.
Regulated or not? In banking, healthcare, government contracting and other regulated settings, move the Govern and Measure responsibilities to the top and name the framework or regulation the role answers to.
Earlier-career version. For an associate or coordinator role, keep Lead the project and Map, make Govern, Measure and Manage supporting responsibilities, and ask for CAPM rather than PMP.
Our guide to AI project manager competencies gives one evidence question for each area of the template.
Keep tools out of the required list. Tools change every quarter. Accountabilities don’t.

Five mistakes to avoid in an AI project manager job description

Writing a data-scientist job and calling it a PM job. If the required list asks for model building or Python, you’ll filter out people who deliver and attract people who want to build.
Listing tools instead of accountabilities. A candidate can learn a platform in weeks. The four decisions above take judgment.
Giving responsibility without authority. If the role owns outcomes but can’t direct vendor work, say so now, or fix it before you post.
Stopping at go-live. Success measures that end at launch produce launches, not results. That’s one of the five places AI pilots stall.
Pricing it like a coordinator. The role carries risk decisions. See the salary guide for benchmarks.

Before you post: one diagnostic

Pull your last three AI initiatives that stalled or were shelved. For each one, can you name the person whose job description made them accountable for getting it into production?

If you can’t, the role you’re about to post doesn’t exist in your organization yet. That’s the gap this job description is meant to close.

If you can’t hire one, you can build one

The market isn’t producing AI project managers at volume yet. Federal statistics don’t track the title at all, and the closest vendor-side role, the forward deployed engineer, posts $300,000–$550,000 in total compensation for mid-to-senior roles, according to Perspective AI’s analysis of roughly 1,000 2026 postings. Many employers will grow the role from their own staff instead.

Master of Project Academy sponsors the nation’s first registered apprenticeship dedicated to AI Project Management, registered by the Maryland Apprenticeship and Training Council (MATC #2575, September 8, 2026) under the registered occupation Information Technology Project Manager. The registration was announced via Business Wire.

The apprentice is your employee from day one, learning on your projects. The AI Project Management apprenticeship explains how the program works.

Frequently asked questions

What does an AI project manager do?

An AI project manager plans and leads the deployment of AI systems inside an organization. The role owns the delivery plan, the risk decisions (what the system may do unattended, how its output is evaluated, when it escalates to a person), vendor coordination, the handoff to an internal owner and post-launch value tracking. It doesn’t build models.

What qualifications should an AI project manager have?

Look for several years leading cross-functional IT or data projects with vendors, working knowledge of how AI systems are evaluated and monitored, and familiarity with an AI risk framework such as the NIST AI RMF. PMP certification is a strong signal for experienced candidates and CAPM for earlier-career ones. Coding usually isn’t required.

How is an AI project manager different from an AI product manager?

An AI product manager decides what an AI product should do and for whom. An AI project manager gets AI systems deployed and governed inside an organization, often across several vendors’ products. Many organizations need both.

What occupation code should HR use for an AI project manager?

O*NET classifies IT project managers as 15-1299.09, and BLS reports their wages within SOC 15-1299, Computer Occupations, All Other. Project manager roles centered outside IT are usually coded 13-1082, Project Management Specialists.

Can’t find this person? Build them.

The AI Project Management apprenticeship, registered under the Information Technology Project Manager occupation (MATC #2575), develops one of your own employees into the role, on your projects, as a full-time employee from day one.

See how employers join the apprenticeship →

P.S. Looking for an AI project manager role yourself? Our guide to how to become an AI project manager covers both ways in.

About Master of Project Academy

Founded in 2012, Master of Project Academy has served 500,000+ enrollments across 180+ countries in project management training. It sponsors the AI Project Management apprenticeship, registered under the Information Technology Project Manager occupation (MATC #2575). Learn more at masterofproject.com/p/aipmapprenticeship.

Sources

Business Wire — Maryland Registers Nation’s First AI Project Management Apprenticeship, Sponsored by Master of Project Academy (Sept 16, 2026)

AI Project Manager Salary Guide 2026: What Employers Pay for the Role