AI Strategy

Who Should Lead AI Transformation in Your Agency? (Hint: Not Who You Think)

By Alyssa Caridi, VP, Strategy & Innovation · Last updated July 3, 2026

• AI Leadership
• Chief AI Officer
• AI Transformation
• Agency

The person who should lead AI transformation at your agency is whoever has authority over how work actually gets done: budgets, workflows, and the people whose jobs will change. In most agencies that is a senior business or operations leader, and increasingly a dedicated or fractional Chief AI Officer, rather than the CTO by default. In BCG's AI Radar 2026, 72% of CEOs now name themselves the main decision maker on AI, double the share a year earlier (BCG, 2026). AI transformation succeeds or stalls on change management and workflow redesign. Choose a leader who can move an organization and has the standing to redesign how it operates.

Who should lead AI transformation at an agency?

Lead AI transformation with the person who controls the operating model, meaning the budgets, the workflows, and the staffing decisions that AI will change. That authority is the scarce ingredient. Most agencies already have someone who can evaluate a tool. Far fewer have named a single leader who can redesign a service line, retrain a team, and hold other executives accountable to a shared plan. The title matters less than the mandate. Whoever leads needs a real budget, a direct line to the CEO, and the standing to change how client work gets produced.

Why isn't the CTO or CIO the obvious choice to lead AI transformation?

The instinct is to hand AI to the most technical executive, because AI looks like a technology problem. Adoption is where most transformations break, and that is a change management problem. A CTO or CIO can select, integrate, and secure the tools. Scaling those tools across an agency depends on redesigned workflows, retrained staff, and buy-in from creative and account teams that a technology leader rarely controls. Deloitte's research on C-suite AI leadership found that returns depend on the right mix of executives working together, not on a single technical owner (Deloitte, 2026). The technical role stays essential. It is one seat at the table rather than the head of it.

What does the rise of the Chief AI Officer tell CMOs?

Companies are answering the ownership question by creating a dedicated seat. In IBM's 2026 CEO study of 2,000 chief executives across 33 countries, 76% of organizations now have a Chief AI Officer, up from 26% a year earlier (IBM, 2026). The same study found that 77% of CEOs say talent and technology leadership roles are converging, and that organizations with an AI-first approach to C-suite design scaled 10% more AI initiatives than their peers. The lesson for a CMO is that AI benefits from one accountable owner who sits above any single function, with authority to align technology, talent, and process.

When is a CMO or business leader the right person to lead?

A CMO or business leader is the right choice when the largest AI gains run through customer-facing work. In an agency, that describes most of the value: content production, campaign execution, personalization, media, and client service. A marketing leader already owns those workflows and the client relationships they feed. When that leader also has AI fluency and a budget mandate, they can move faster than a technical executive who would need to learn the creative and account side first. The test is authority. If the CMO can redirect spend, rewrite a process, and change who does what, they can lead. If they can only advise, the mandate belongs elsewhere.

Why does a dedicated or fractional AI leader do the best job?

The strongest AI transformation leaders almost always come out of operations, and that background is the reason they outperform. They have run the processes they are now being asked to improve, and in many cases they have done the frontline work themselves. That history gives them something no tool can supply: the judgment to tell a workflow that is genuinely broken from one that only looks inefficient from the outside. A leader who has sat in the seat can watch a team work and know within minutes whether the bottleneck is the process, the handoff, or the tool. That accuracy is what protects an agency from spending six figures automating a step that should have been removed.

A dedicated leader brings that judgment full time. A fractional leader brings the same profile at a fraction of a full executive salary, plus pattern recognition from other engagements, which is useful when an agency is standing up its first AI function and does not yet need a permanent seat. Interest in the fractional model is rising as boards weigh whether a full-time Chief AI Officer is warranted (CNBC, 2026). Either way, the value comes from the same source: an operator who has done the work, backed by real command of the tools, with the relationships to make change stick.

What qualities should an AI transformation leader have?

Screen for the qualities below before you screen for engineering depth. Deep technical skill is useful and rarely the deciding factor. The person who can align finance, talent, and delivery around a plan will outperform the most technical candidate who cannot.

• An operations background and hands-on experience with the work. The best AI leaders have done some or all of what the teams do, so they understand the work from the inside and earn the trust that makes a team open up. That credibility is what turns a diagnosis into a change people actually adopt.
• Diagnostic patience. A strong leader sits with a team and says, show me how you actually work, then does it again with the next team, and the next, before proposing a single change. The failure mode to avoid is diagnosing too quickly, solving a problem that does not exist, or automating a process that should be redesigned first. Watching the real workflow, more than once, is how you avoid it.
• Plain-language communication. The role lives at the boundary between technical possibility and the people who have to use it. A good leader can take a complex model or automation and explain it in direct, digestible terms that a creative director or account lead can act on without a translator.
• Detail orientation. Workflow problems hide in the small steps: the manual export, the duplicate approval, the handoff where work sits for a day. A leader who reads the process at that level of detail finds the gains that a high-level map misses.
• Working fluency in AI, automation, and development. They do not need to be a full-time engineer. They do need strong working knowledge of AI tools, automation platforms, and ideally some development ability, so they can tell a real capability from a vendor promise and judge what is feasible before the agency commits budget. This matters more as buying accelerates, with CEOs committing more than 30% of AI investment to agentic tools this year (BCG, 2026).
• Strong relationships across the organization. Change lands through trust. A leader who already has credibility with both technical and creative teams can move a redesign through the parts of the agency that would resist an outsider.

Combine an operator who has done the work with real command of the tools and strong relationships, and you have the profile that consistently delivers. It is a rare mix, which is exactly why agencies often meet it through a dedicated hire or a fractional engagement rather than by reassigning an existing executive.

Should an agency hire a fractional AI leader?

Bring in a fractional AI leader when no internal executive holds both the AI fluency and the organizational authority to drive change, or when the agency needs momentum faster than it can grow that person. A fractional leader can set strategy, stand up governance, and run the first wave of workflow redesign for a defined period, then step back. Structure the engagement so knowledge transfers to a named internal owner, so the agency keeps the capability once the foundation is built and is not left dependent on an outside party. The goal of the engagement is to make itself unnecessary.

How do you set your AI leader up to succeed?

Give the leader a clear mandate, a real budget, and a direct reporting line to the CEO, then hold the rest of the executive team accountable to the same plan. Name the outcomes you expect in the first two quarters, fund the workflow changes that support them, and make governance part of the role from day one. Agencies that decide ownership early move from pilots to production while their competitors are still debating who is in charge. If you are weighing that decision now, start by naming the person with the authority to change how the work gets done, give them the qualities above as your checklist, and give them the room to do it.