Agentic AI is rapidly emerging as the next frontier in marketing technology. The global market is forecast to surge from $7.55 billion in 2025 to a whopping $199.05 billion by 2034—a compound annual growth rate (CAGR) of 43.84%.
While interest and momentum among marketers is building, adoption remains tentative, with only 20% currently deploying AI agents for marketing work.
Understanding what’s changing, what’s coming, and how to prepare for an agentic AI-powered future is essential for marketers looking to navigate these shifts effectively.
Key Takeaways:
Agentic AI represents a fundamental shift for marketers. These autonomous systems differ from the assistive AI many teams use today by handling complete workflows without constant human intervention. This evolution to proactive execution is poised to transform how marketers operate in three major ways: driving significant efficiency and ROI gains, reshaping marketing roles from execution to oversight, and creating an entirely new agentic web where AI systems interact alongside humans.
One of agentic AI’s biggest selling points for marketers is its ability to drive significant efficiency and effectiveness gains. Through capabilities like autonomous campaign optimization across channels, real-time personalization at scale, and intelligent lead qualification, agentic AI can help marketers achieve better results with less manual effort.
Use of the technology across marketing and sales is forecast to fuel over 60% of agentic AI’s overall value across the enterprise. Early deployments for task automation and human assistance can boost company-wide productivity by 3 to 5% annually, with gains potentially reaching 10% or higher as systems evolve to handle more sophisticated workflows.
Today, most marketers primarily use AI as assistive tools—systems that respond to prompts but need human guidance for each task.
Agentic AI is poised to change how marketing teams work due to its ability to autonomously complete multi-stage processes in service of key goals. Rather than simply generating a single ad variant or analyzing one dataset, AI agents will be able to handle entire workflows end to end. For example, within the realm of programmatic advertising, agentic AI will eventually streamline entire campaign processes from start to finish. Beyond media buying, AI agents are expected to take on specialized roles like strategy assistants that generate and test campaign ideas, data analysts that surface actionable insights, and customer engagement coordinators that manage personalized communications across channels.
As agentic AI expands across marketing functions, the marketer’s role will evolve from hands-on execution to managing AI agents that complete tasks autonomously.
As agentic AI transforms how marketers work, it will also alter consumer behavior.
Consumers are expected to increasingly adopt AI agents to handle complex spending decisions such as booking vacations, planning weddings, and comparing financial products. These behavioral shifts will further disrupt the search landscape, with experts saying that many consumers will eventually delegate entire research and decision-making processes to AI agents.
This shift signals a new era for the internet, where the web will be made up not only of the traditional human-facing web, but also an agentic web where AI systems communicate, evaluate, and transact autonomously. Marketers will need to evolve to ensure discoverability across both layers, optimizing for algorithmic systems while maintaining the creative storytelling that resonates with humans.
While agentic AI promises significant transformation, most marketing teams are still in the early stages of adoption. Successfully integrating this technology requires four key steps: identifying high-impact opportunities for AI agents, preparing data infrastructure, managing organizational change effectively, and optimizing for both human and agentic web discovery.
To harness the efficiency and effectiveness benefits of agentic AI, marketing teams must start by identifying the marketing functions where the technology can make the most impact. This involves auditing workflows for repetitive tasks and processes that can be automated by AI agents.
Key opportunity areas include media and performance optimization, creative operations, account management, and strategy and intelligence. More specifically, agentic AI tools can minimize errors and speed up execution across tasks like budget management, creative testing, ad placement verification, and cross-platform data analysis.
Beyond these foundational areas, marketers should explore creative use cases specific to their team’s unique needs.
Agentic AI’s effectiveness hinges on data quality. However, most marketing teams don’t have the data readiness to make the most of the technology: Only 17.9% of marketers say their first-party data is extensive and well-structured, and one-third report that first-party data plays a minimal role in their current AI initiatives.
To get ahead, teams must work to unify their data within centralized platforms and databases and establish clear governance protocols for its usage. Without unified data that AI agents can access and act on, autonomous decision-making proceeds on a fragmented foundation. AI agents may still be able to execute workflows, but their decisions will be based on incomplete datasets that produce generic or flawed outputs rather than unique, differentiated benefits suited to an organization and its specific audience(s). Marketing teams should also invest in measurement tools that provide real-time, cross-channel insights, as this powers AI agents’ ability to learn and optimize continuously.
Thoughtful change management is another critical component of integrating agentic AI effectively. This means earning employee buy-in, providing comprehensive training to build AI fluency across teams, embedding AI tools into standard workflows, and finding ways to measure how successfully teams are using the technology. Leadership should also establish clear governance frameworks that define how AI agents operate and make decisions. These frameworks should clarify the critical role that human employees play in monitoring and managing those processes.
As consumers increasingly delegate research and purchasing decisions to AI agents, brands must ensure they’re discoverable to both autonomous systems and human audiences. This means creating structured data, clean APIs, and metadata-rich content that AI systems can easily ingest and interpret. Marketing teams should audit their websites, product catalogs, and digital assets to verify they’re optimized for both human visitors as well as AI agents.
The rise of agentic AI represents both a challenge and an opportunity for marketing teams. Those who prepare now—by identifying opportunities, building data readiness, proactively managing organizational change, and optimizing for machine discoverability—will be best positioned to capitalize on the technology’s transformative potential.
—
Looking for information on how your peers are approaching and thinking about AI? Our report, AI and the Future of Marketing, synthesizes unique insights from a proprietary survey of marketing and advertising professionals across leading agencies and brands.
