For many marketing teams, the conversation around AI still starts with tools. Which platforms to invest in. Which models to test. Which use cases to prioritise.
But as organisations move beyond early experimentation, it becomes clear that tools are not the limiting factor. The real challenge is how marketing teams work.
AI doesn’t simply accelerate existing processes; it changes how work is designed, delivered and managed. Without evolving ways of working, even the most promising AI initiatives struggle to scale. This is why the organisations making real progress aren’t just adopting AI tools — they are reshaping how marketing operates day-to-day.
AI isn’t a tool problem – it’s a workflow problem
Most marketing teams today are experimenting with AI. Far fewer, however, have embedded it into the workflows that underpin delivery.
This creates a gap between activity and impact. AI is often used in isolated tasks rather than integrated into how marketing actually runs. As a result, teams may move faster in pockets, but not across the end-to-end system.
To deliver meaningful value, AI needs to be built into the flow of work itself. High-performing organisations are therefore shifting their focus away from individual use cases and towards redesigning the workflows that drive marketing performance.
From tasks to systems: redesigning how marketing operates
AI introduces a fundamental shift in how marketing work is structured.
Traditionally, workflows have been built around manual execution. AI accelerates these activities, but it also changes the role of the marketer. Increasingly, marketers are responsible for shaping inputs, guiding outputs and making decisions based on AI-enabled insight rather than executing every task themselves.
This shift requires more than inserting AI into individual steps. It requires a rethink of how work connects end-to-end.
Organisations that are successfully scaling AI are moving towards more structured and repeatable ways of delivering marketing. They are connecting ideation, execution and optimisation into a more cohesive system, ensuring that AI is embedded into the flow of delivery rather than sitting alongside it.
Where workflows typically break down
Across organisations, a consistent pattern emerges. The challenge is rarely a lack of tools or intent. It is how workflows are structured.
One common issue is applying AI to broken or unclear processes. When workflows are inefficient or poorly defined, AI does not resolve the problem. Instead, it accelerates it and often exposes underlying weaknesses in how teams already operate.
A second challenge is disconnected experimentation. Many teams run pilots that sit outside of core delivery. While these generate insight, they rarely translate into sustained impact because they are not integrated into day-to-day workflows. This is why so many organisations remain stuck in experimentation without making the leap to scale.
Finally, there is the issue of repeatability. Even when a use case is successful, it is often dependent on individuals rather than systems. Without clear processes, ownership and consistency, success becomes difficult to scale across teams.
What AI-enabled ways of working look like
Organisations that are successfully embedding AI tend to share a common shift: they integrate it into the way work happens rather than treating it as a separate activity.
In practice, this means AI becomes part of core workflows such as campaign planning, content creation and performance analysis. It supports decision-making and execution throughout the lifecycle, rather than being applied in isolation.
These organisations also prioritise structure and consistency in how work is delivered. Workflows are clearly defined, making it easier to scale activity, onboard teams and maintain quality across outputs.
At the same time, they treat ways of working as evolving systems. Teams continuously test, learn and refine how they operate, using feedback and performance data to improve both processes and outcomes.
Another defining characteristic is collaboration. AI-enabled marketing doesn’t sit within a single function. It connects marketing with data, technology and governance teams, ensuring that workflows are aligned and can scale effectively across the organisation.
Ways of working drive commercial impact
Redesigning ways of working is not just an operational exercise. It is what unlocks value.
When AI is embedded into structured workflows, organisations begin to see improvements across the metrics that matter. Campaigns are delivered faster and more consistently, targeting becomes more precise, and decision-making improves. Over time, this translates into stronger pipeline performance and measurable commercial outcomes.
These results are not driven by isolated use cases. They come from building a system that consistently turns activity into impact.
From experimentation to embedded capability
Most organisations today are somewhere between experimentation and early scaling. AI is being used, but it is not yet fully integrated into how marketing operates. Moving forward requires a shift away from isolated tools and pilots, towards integrated workflows and repeatable systems.
This is what allows AI to move from an innovation initiative to a core organisational capability.
The next step for marketing leaders
AI is already changing what’s possible in marketing. But the organisations that are realising its full potential are those that are rethinking how their teams work.
Ways of working sit at the centre of this transformation. They connect strategy to execution, enable scale, and turn AI into something repeatable, measurable and commercially impactful.
The challenge for marketing leaders is not just the technology, it’s how the marketing organisation needs to evolve around it.
By Zoe Merchant, Partner – Growth, Marketing and Sales Consulting