AI agents for marketing are no longer a future state — they have arrived. Eighty-three percent of B2C marketing decision makers report actively implementing agentic AI into their workflows, and 85% agree that it’s delivering meaningful business value in their marketing efforts. With the rise of AI platforms like Claude and ChatGPT, and the majority of martech vendors launching proprietary AI agents, access to agentic functionality for marketing is pervasive.

The opportunities for using AI agents in marketing are nearly boundless, spanning customer insights, content creation, operations, and campaign execution. The potential is undeniable, but it’s unrealistic to expect marketers to run an infinite number of agents for all marketing tasks. AI agents promise speed and efficiency, but they still require resources to implement, maintain, utilize, and monitor. And AI is taking a bigger bite out of budgets as usage grows and becomes more costly. There are practical limits to how much AI an organization can deploy. To stay within their resource thresholds while also providing a return to the business, marketers must take a disciplined approach to evaluating their AI agent investments.

In 2025, we published The B2C Marketer’s Guide To Agentic AI to help marketers assess organizational readiness for AI agents in marketing. Our latest research, AI Agent Use Case Readiness Tool For Marketing, goes further. Marketers can evaluate specific AI agents by categories and use cases and then determine which use cases their organizations are ready to implement by using a standard priority, people, process, and technology framework to output a marketer readiness score.

First, Organize AI Agents Across Seven Marketing Categories And 52 Use Cases

The tool distributes agents across seven core marketing functions according to their respective purpose:

  1. Data. Transform, structure, unify, and enrich data inputs for downstream systems.
  2. Analytics. Produce insights, predictions, recommendations, and decision support for marketers.
  3. Measurement. Evaluate marketing performance and optimize based on outcomes.
  4. Content. Produce and manage creative assets for effective utilization.
  5. Operations. Coordinate resources and optimize marketing processes.
  6. Orchestration. Execute marketing programs and campaigns for customer engagement.
  7. Experience Delivery. Automate and optimize customer-facing interactions.

Across these seven categories, the tool includes 52 potential use cases, ranging from “assemble customer profiles” and “define retention-risk scoring models” to “assemble and structure content assets” and “arbitrate contextually relevant cross-channel interactions.”

Then, Evaluate Readiness Across Four Practical Dimensions

For each use case, the tool asks marketers to assess:

  • Priority: Is this use case important enough to pursue?
  • People: Have the necessary stakeholders been identified, assigned, and prepared?
  • Process: Is the supporting process merely diagnosed, or is it designed, implemented, and optimized?
  • Technology: Has the relevant technology been scoped, piloted, or put into live production?

The tool automatically calculates a readiness score, which marketers can use alongside self-selected priority indicators to plan their marketing roadmap for AI agents.

Ready to chat about your results? Schedule a guidance session or inquiry with us.

Special thanks to coauthors Katie Linford, Rusty Warner, Zeid Khater, Brad Haag, Jordan Brodeur, and Emily Collins.

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