Agentic AI is reshaping the role of the marketer and redefining how marketing organizations operate. Past innovations—from customer relationship management software to marketing automation—helped streamline and optimize discrete steps in the marketing process. Agentic AI goes further. These systems introduce autonomy: they make decisions, trigger actions, and learn across cycles. That shift delivers more than efficiency. It enables marketers to identify what works and what doesn’t and to forecast how consumers will respond, even before launch.
CMOs are aware of the shift underway. More than 80% report having growing confidence, optimism, and curiosity about AI’s potential, even as they acknowledge the disruptive pressures it creates. Nearly one in three CMOs has piloted AI for content creation, with video generation emerging as the next wave. But agentic AI, still at its frontier, has the potential to reconfigure the entire marketing workflow.
Agentic AI, still at its frontier, has the potential to reconfigure the entire marketing workflow.
Specifically, agentic AI can triple marketing ROI, speed, and volume (see Exhibit 1). In practice, these outcomes often translate to 5% to 10% incremental top-line growth and 15% to 20% cost efficiencies across internal and agency spending, creating a self-funding transformation that fuels further change. In our work with leading global brands, we’ve seen these results help teams move faster and reinvest in AI. In fact, 43% of the CMOs we surveyed say they already invest $10 million to $15 million annually in scaling AI adoption. This is not an incremental shift. It’s a reset of the marketing operating model, and those who move first will define the next era of growth.
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The Forces Driving Change
Marketing leaders are simultaneously facing internal and external pressures: collapsing funnels, fragmented consumer attention, rising growth expectations, and intensifying cost constraints. AI is accelerating those disruptions even as it opens new ways to counter them.
Externally, both discovery and media are being reshaped. Large language model-driven search is disrupting how consumers encounter brands in the earliest stages of the journey. At the same time, nearly 60% of CMOs expect AI to run the majority of media workflows within the next two to three years, fundamentally changing how marketing spending is planned and optimized. Internally, the mandate is just as stark: deliver more with less. CMOs rank cost efficiency (76%) and speed to insights (71%) as the top benefits of AI adoption, and new tooling is pushing organizations to become leaner and more efficient.
These forces are converging faster than most organizations can adapt. Placing agentic AI as central within the marketing model offers a path to stay aligned with shifting customer behavior and industry dynamics.
Placing agentic AI at the center of the marketing model offers a path to stay aligned with shifting customer behavior and industry dynamics.
The New Marketing Workflow Powered by Agents
The pace of disruption requires new capacity in marketing organizations. This is where AI agents can serve as an important release valve for teams. Whether built or bought, agents are designed to reduce toil, scale repetitive but critical tasks, and unlock production capacity across the value chain. Agents can automate nearly any marketing activity, from generating tags for measurement to building email variants, analyzing market trends, or generating insights.
Agents’ impact now spans the full marketing workflow. There are six areas where agentic AI creates advantage—from insight and innovation to creative content, personalized activation, and measurable outcomes. (See Exhibit 2.) Brands are already beginning to apply these capabilities, with encouraging results.
A global retailer, for instance, used synthetic consumers to test messaging and refine brand positioning across personas and markets. And a leading media and entertainment company captured real-time signals from viral content to amplify stories that resonated with specific geographic and consumer microsegments across channels. These are tasks that once demanded large teams and long lead times.
Other organizations are scaling even further. One consumer packaged goods leader introduced agentic copilots across its process—from campaign brief generators to dynamic email builders—creating a marketing operating system that empowers its teams and operates with greater speed, precision, and adaptability.
Our experience in building and advising on agentic capabilities with leading global companies underscores the scale and velocity of change already underway. Marketing organizations are now using multiagent platforms that connect vast datasets, running on many petabytes of data and processing terabytes each day to deliver insights and actions in real time. At one global company, hundreds of marketers are already engaging daily with these systems, through custom and commercial interfaces that coordinate dozens of specialized agents across markets and data sources. What began as an isolated pilot is rapidly evolving into an enterprise capability embedded in how marketing gets done.
Efforts that once depended on multiple handoffs across teams and agencies is beginning to move through integrated, responsive systems, offering a level of speed and precision that was impossible before.
Together, these advances show how quickly the marketing workflow is shifting. Efforts that once depended on multiple handoffs across teams and agencies is beginning to move through integrated, responsive systems, giving CMOs the ability to respond to both markets and customers with a level of speed and precision that was impossible before.
Agents Are Transforming the Marketer’s Role
For CMOs, the greater challenge is not adopting new tools but reshaping the teams, partners, and structures around them, ensuring that agentic AI becomes a source of scale, not fragmentation.
The marketer’s role is shifting from specialist in a silo to orchestrator in chief of intelligent agents across the full cycle of insight, creation, activation, and measurement. This evolution is driving demand for new skills—from prompt writing to analytics fluency—with roughly 75% of CMOs already investing in GenAI upskilling across levels.
The more profound implications, though, are organizational. Lean, automation-powered teams are breaking down silos and moving faster. Internal creative studios are rising as content scales, while traditional channel specialist roles decline. Agency relationships are under pressure: 86% of CMOs say creative agencies are not yet using AI at scale, and 67% say the same of media agencies. And marketing technology ownership is shifting closer to the CMO, requiring tighter collaboration with IT to balance speed with safety.
Resilient organizations are anchoring these shifts in five capabilities:
Pod-Based Design. They are embedding AI talent within core business teams to enhance agility, accountability, and collaboration.
Continuous Capability Development. They are investing in ongoing AI training and fluency building so that teams can adapt quickly as technologies evolve.
Clear Measurement. They are tracking AI’s impact through defined KPIs, usage dashboards, and behavioral insights that guide adoption and performance.
Integrated Tooling. They are creating a unified set of approved AI tools that connect across workflows, streamline operations, and enable safe experimentation.
Strong Governance. They are establishing guardrails and ethical guidelines to ensure AI is deployed securely, transparently, and responsibly.
Together, these capabilities allow CMOs to scale agentic AI responsibly while positioning marketing as a driver of enterprise growth.
Building a Foundation of Flexible Data and Technology
Scaling agentic AI requires more than new tools. It depends on a strong foundation that connects data, integration, and interface layers. Companies must link business context, enterprise knowledge, and marketer action through cohesive systems and clear governance. Without that backbone, pilots remain stuck in silos and fail to scale. (See Exhibit 3.)
Bridging that foundation now falls to CMOs, who must determine how to scale it: moving quickly with vendor partners, building proprietary capabilities for differentiation, or pursuing a hybrid path that blends both speed and control?
Yet technology choices alone won’t determine outcomes. Leading organizations are coupling architecture with practices that instill trust and adaptability, rolling out governance guardrails early and making iteration a core discipline. Nearly 80% of CMOs are already introducing governance plans, and the most advanced teams continuously tune prompts, workflows, and retraining cycles to stay aligned with business goals.
The decisive factor remains first-party data. Data fragmentation is the top barrier CMOs cite to scaling GenAI and the strongest predictor of whether agentic AI delivers the speed, personalization, and measurable outcomes it promises.
A Roadmap for Leaders
CMOs who are preparing now for Agentic AI’s acceleration are beginning to build compounding advantages, capturing speed, scale, and efficiency gains that will be hard for others to match. The challenge is no longer whether adoption will happen but how to scale responsibly and quickly as adoption accelerates.
The challenge is no longer whether adoption will happen but how to scale responsibly and quickly as adoption accelerates.
Rather than taking a slow, multiyear approach or running narrow pilots, leading organizations are committing to a focused 9- to 12-month roadmap to reimagine marketing for the agentic era. The playbook follows four accelerating steps that move from experimentation to enterprise scale, with early adopters already seeing that returns, speed, and content volume can all triple when agents are fully embedded in daily operations.
Step one: prove the power. Begin with a use case that delivers visible ROI within weeks. Early pilots, such as a brief generator agent that can cut campaign-briefing cycles by weeks, help create internal champions and a quantified case for change. The focus is on proof, not scale: on validating the potential and building momentum.
Step two: build the foundation. Expand from pilot to practice. Train teams, introduce additional prototypes, and shape the supporting data and technology road map. At this stage, many brands launch content copilots or orchestration engines that optimize spend in real time, moving from isolated wins to a repeatable operating rhythm.
Step three: scale what works. Redesign full workflows with agents embedded end to end, from creative briefing to activation to measurement. One global retailer, for instance, rebuilt its content supply chain, cutting cycle times from 25 weeks to under 8. By this point, operating models evolve, teams restructure, and agency partnerships shift.
Step four: embed and evolve. Make agentic marketing the new normal. Governance, upskilling, and tech upgrades hardwire new behaviors into the organization. The payoff becomes more visible in the profit and loss: faster cycles, higher returns, and declining external spending. Marketing is no longer experimenting with AI—it’s operating on an agentic model.
Entry Points for Early Wins
While every organization will chart its own path, three entry points are proving to be most effective:
- Reimagine a process. Use agents to shorten campaign briefing cycles or to automate reporting.
- Reinvent a channel or category. Improve efficiency and targeting of social or performance campaigns.
- Transform a customer moment. Pilot conversational commerce or agentic discovery to reshape how customers engage.
The coming year will be decisive. CMOs who accelerate through quick wins, redesign core processes, and build the foundations for enterprise scaling will define the next era of growth. Those who delay will still adopt agentic AI, but they’ll miss the momentum, scale, and hands-on learning that come only from leading the change.
