Monks and M&C Saatchi rethink roles as AI agents spread
Monks is revisiting junior tasks while M&C Saatchi reserves weekly learning time, showing how agency roles are adapting to AI agents.
At Monks and M&C Saatchi North America, the conversation about artificial intelligence is shifting from which tools agencies use to how their people work. Executives from both agencies described changes to training and early-career responsibilities at an October media-buying summit in California.
The development is less dramatic than a wholesale redesign of the agency workforce, but it may be more revealing. AI agents can assist with planning and activation before an organization has settled who should supervise them, what junior staff should learn or how time saved by automation should be reinvested.
Table of contents
Jump to each section:
- The gap between AI adoption and agency design
- Monks revisits junior work without cutting roles
- Why weekly AI training matters to agency operations
- What marketers should know about AI-led agency teams
The gap between AI adoption and agency design
Marketing agencies have embraced AI agents for tasks such as campaign planning and media activation. The organizational consequences have been slower to emerge. An employee may be able to assemble a plan more quickly without the agency having changed its hiring criteria, review processes or training expectations.
That creates a tension between individual efficiency and institutional capability. Faster output is not necessarily better work if staff use automation to bypass evaluation, especially when recommendations or creative choices need human judgment.
The distinction matters to brands buying agency services. A supplier's AI toolkit reveals comparatively little about the quality of its processes for checking the outputs. The more useful question is who remains accountable when an automated workflow produces something plausible but unsuitable.
The gap is not simply technical. It concerns how agencies transfer expertise between experienced practitioners and people entering the industry, particularly when routine tasks that once provided a route into media buying are easier to automate.
Monks revisits junior work without cutting roles
Gila Wilensky, Monks' executive vice president and head of data and media in North America, said the company was revisiting the tasks assigned to junior employees. She specifically rejected the idea that this meant hiring fewer junior people.
Instead, the agency is reconsidering what new hires should spend their time doing. Preparing spreadsheets is one example of activity that could be reduced as AI takes on more of the routine work.
That changes the apprenticeship question. Repetitive production tasks are not necessarily a good use of human time, but removing them also means junior workers need other ways to develop judgment about campaign decisions and the assumptions behind automated plans.
Monks' AI-focused marketing offering provides context for this shift. Tools built around AI-assisted marketing workflows can change the sequence of work, but the agency's reported staffing discussion is about the people who must interpret and improve that work.
Wilensky also suggested that a future role might involve checking AI outputs and guarding against agent errors. That was a prediction, not an announcement of an established role or recruitment program.
Why weekly AI training matters to agency operations
M&C Saatchi North America described a more immediately measurable response: making staff development part of the working week rather than an optional activity outside it.
One hour each week is reserved on employee timesheets for learning at M&C Saatchi North America, according to CEO Nadja Bellan-White's remarks at the media-buying summit.
"A learning agenda has to be operationalized throughout your organization," Bellan-White said. Her point was about creating time for learning inside an operating model, not simply encouraging workers to familiarize themselves with a new product.
A scheduled hour does not establish that the training is effective or that an agency has achieved a measurable return on AI investment. No such performance result was disclosed. It does, however, make learning a recognized work responsibility.
Monks and M&C Saatchi are addressing different sides of the same problem. Monks' discussion concerns what junior staff do as automation spreads; M&C Saatchi's concerns how to create capacity for people to develop the skills needed to supervise changing workflows. Both imply that the adoption of agents is only one part of organizational change.
What marketers should know about AI-led agency teams
For marketing leaders evaluating their own teams or external agencies, these developments offer a way to examine the human structure behind AI-assisted execution.
Ask who checks the work. Automated media plans still require people capable of questioning assumptions, interpreting a brand brief and deciding when an output should not be used.
Treat training time as operational capacity. M&C Saatchi's weekly allocation provides a concrete example of how learning can be accounted for in a working schedule rather than left to individual initiative.
Revisit early-career development. Monks' discussion suggests that removing repetitive tasks should prompt an equally deliberate rethink of how junior talent gains campaign judgment and experience.
Separate predictions from proven changes. Possible future AI-checking positions and broad productivity gains should not be confused with demonstrated staffing changes, client outcomes or commercial results.
The broader question is whether agencies will redesign work around their strongest human capabilities, or simply use AI to accelerate the same chain of deliverables. Those are different operating choices, even if both begin with the same agentic tools.
Brand teams face a parallel decision. When evaluating an agency's AI capabilities, the credentials of its people, their capacity to challenge automated recommendations and its learning processes may become as relevant as the software itself.
The outcome will not be settled by tool adoption alone. It will depend on whether faster execution creates more room for strategic judgment, or merely raises expectations for producing more material with the same organizational habits.
