How agentic AI is elevating marketers, not replacing them

written by
Rebecca Corliss

Key Takeaways:

  • Agentic AI is a step beyond generative AI, opening up new potential for marketers to accomplish more, test and iterate campaigns faster, and achieve complex goals more easily.
  • A collaborative approach to agentic AI is essential to help marketers embrace what agents can accomplish for (and with) them.
  • While agentic AI massively increases the output marketers are able to accomplish, it’s not in danger of replacing them. Agents will always need the leadership, vision, and oversight of marketers.

Table of Contents

Will artificial intelligence replace my role? 

This question is at the top of many workers’ minds today. It’s understandable that some might have this fear; several high-profile companies have announced reorganizations or layoffs in favor of delegating to AI’s automation capabilities. 

Make no mistake: AI can and will flip the marketing world on its head. (In some ways, it already has.) But AI won’t take your job, but someone who has a strength for using it might.

AI (in particular, agentic AI) is enhancing marketers’ roles, so they can move faster, execute great ideas sooner, access the full value of their data, and refine every campaign. Agentic AI is elevating marketers, not replacing them. 

Let’s explore what agentic AI helps marketers achieve, how to build a collaborative AI approach, and how agents and marketers can work together to achieve compound growth.  

The era of agentic AI

AI chat tools like ChatGPT, Google Gemini, and Midjourney have taken the news cycle by storm. Users around the world are experimenting with generative AI for both productive and playful purposes. They enter one or more prompts into the tool, which then generates images, text, or other media.

As AI advances, the conversation is shifting again — this time toward agentic AI. OpenAI continues to make headlines with its Operator agent, which promises to buy groceries and book dinner reservations for users, and self-driving tech like Waymo’s shows us what else is possible with agents. 

Unlike the “prompt, then output” flow of generative AI interactions, agentic AI can complete tasks and even operate autonomously without constant human input. A user sets a clear goal, then the agent processes data, creates a multi-step plan, and takes action to reach the goal. 

A single agent on its own can execute tasks. But multiple specially trained AI agents can effectively function as a team that works together to fulfill a complex objective. And when multiple agents join forces with a user with a clear vision, they unlock a form of collaborative intelligence where a multi-agent system and a human solve a problem as one. 

Comparison of generative ai vs agentic ai

AI agents for marketing teams

Now, let’s put this in the context of the marketer’s role. Day to day, marketers combine creative direction with data-driven strategy based on customer behavior and engagement. AI can’t replicate their instincts or experiences, and it certainly can’t replace the empathy, relationships, and humanity of a marketer. But a team of AI agents powered by company and customer data can help surface insights, execute campaigns, enhance decision-making, and apply learnings from previous campaigns. 

Here’s one scenario: A marketer might prompt a team of AI agents with an objective like, “We need to increase repeat purchases by 20%.” A generative AI tool could provide general tips on how one might do that. But agentic AI can actually take steps to help the marketer reach those goals:

  • One AI agent trained on the customers within your data cloud can recommend the ideal audiences to drive more repeat purchases.
  • Another agent might suggest the right steps or campaigns to encourage audience action.
  • A third agent might conduct external research to uncover helpful context to guide timing and execution.

I like to compare this to the dynamic at a focused, action-oriented marketing team meeting. Each team member usually has specialized expertise and their own tasks to complete, like demand generation, content creation, or data analysis. A team of AI agents operates similarly: Each one is trained on a specific type of task and ready to work toward the objective. 

Agentic AI will elevate rather than replace

Does this mean agentic AI is coming for marketers’ roles? Not at all. Agents will take away tasks, not jobs. Marketers (and leadership) should measure their value in both output and value created. In that regard, agents only make marketers more effective. 

The same mindset shift happens when someone becomes a manager for the first time. New marketing leaders are used to having their hands on a keyboard constantly for high individual output. After transitioning into management, they spend most of their time in meetings, shaping the team’s strategy, and guiding their direct reports. While their individual input goes down, the total input they influence (that of their team) increases dramatically.

Whether they’re overseeing a team of human marketing specialists or AI agents, a marketing leader harnesses their interpersonal leadership skills and big-picture company vision to inspire the team to achieve amazing things. No matter how much agentic AI advances, that’s a role only an experienced marketer can play. 

Creating a more collaborative approach to AI

Agentic AI can operate more autonomously than most of the tech that came before it, so many people see it as a “set-it-and-forget-it” tool. Why not, if it can complete tasks on its own, right?

Not so fast. As marketers start to lean more on agentic AI, the path forward is collaborative

Remember, marketers bring essential insights, experiences, and firsthand knowledge to the table. A collaborative AI approach lets them contribute their unique expertise while working with agentic AI to reach a shared outcome. With that, a team of AI agents should collaborate with each other, with the data, and with a marketer at the helm, asking for additional input and making proactive suggestions for the marketer to accept or reject. This back-and-forth unlocks the efficiency and speed that agentic AI promises, and promises greater outcome by leveraging the expertise and greater strategic context that marketers have.

How can AI help me with this? 

To embrace and adapt to the new normal of agentic AI, marketers will need to form new habits and a new, collaborative AI mindset.

Nine out of 10 marketers use AI in their roles, from idea generation to editing copy to research. But in many cases where AI could be incredibly useful, their instinct is still to recruit a human’s help. 

A more collaborative approach to AI starts with building it into as many workflows as possible, starting with generative AI tools. Throughout the day, marketers should pause to ask themselves, “How might AI assist me with this?” As they ask themselves this question and experiment with prompts, workflows, and use cases, they’ll learn to recruit AI’s help with creating text or graphics by default. 

AI is all about the art of the possible. Whether marketers are creating a flyer for a personal passion project or need to get unstuck during a marketing sprint, they should stop and consider where generative AI could be useful and experiment. That’s the first step to thriving with more advanced agentic AI use cases.

What direction does AI need from me?

There’s an important parallel to be made between the management of people and the management of agents. The better direction leaders provide, the greater their total output will be and the better the results. A roster (or “team”) of AI agents needs guidance, just like that team of human marketing specialists you lead. 

Marketing managers need to give agentic AI precise marching orders to reach the ultimate goal and produce the right output. This includes providing detailed context and direction to ensure agents take the right steps. Instead of asking an agent to create an audience as a one-off task, they should share more about the big-picture objective they want to achieve that the audience fits into. This invites more back-and-forth engagement between the marketer and agent, so both can lean on their strengths.

With thoughtful human intervention, agentic AI can improve the speed, depth, and results everyone can achieve within the same number of hours in a day. That means every marketer, from the newest hire to the most senior exec, can achieve more.

But a human marketer will always be most advantaged to set a goal, provide strategic context, and offer direction, and confirm the output will drive the required outcome. Even with a team of AI agents, someone always needs to be in the driver’s seat to provide an initial prompt and supervision.

The three ingredients for agentic AI success

The 3 ingredients for agentic AI success

AI agents can solve complex problems more simply by taking time-consuming tasks off marketers’ plates and out of their project workflow. But agents don’t operate in isolation. They need three foundational elements to succeed. 

  1. Marketers’ prompting skills. We’ve said it before, and we’ll say it again: A human marketer needs to be in the loop for AI success. No matter how advanced your AI agents, they won’t help your organization grow if you have the wrong goals and strategy from the outset. Marketers need to bring the right objectives relative to their audience. They also need to develop the prompting skills to get the best out of AI agents and achieve the ideal outcome.
  2. Data as a differentiator. You don’t have an AI strategy if you don’t have a data strategy. If every other marketer on the planet has advanced AI prompting skills, how are you going to win next? Your ability to give AI agents access to your data is what will set you apart. AI agents need as much context as possible: information about your business objectives, your customers and their product usage, your marketing, sales, and more. Give them the most comprehensive possible view of your company’s world to set up your agents for success. 
  3. The agents themselves. As agentic AI advances and becomes more sophisticated, so will marketers’ ability to use it and accelerate their results. Technology companies are responsible for providing and enhancing this piece of the agentic AI puzzle, which has to happen before marketers can go deeper with agentic AI.

Even with advanced analytical and execution skills, agentic AI still needs a human to oversee its output and check its instincts, along with robust data to inform its decision-making. Marketers will see the best results when they know how to leverage all three together. 

The future of marketing is bright

AI in its many forms is an advisor to the human marketers it supports. Like any advisor, AI needs real people to listen to its suggestions and insights and decide whether to move forward.

AI outputs might inspire a better idea, clash with historical knowledge the marketer has, or go against a gut instinct based on years of experience. Someone needs to stay in the driver’s seat, offering oversight, judgment, and creative vision. 

That’s why AI agents are such an exciting proposition. They’re here to help marketing teams accomplish more and achieve better results with every campaign. And with a collaborative AI approach, marketers and agents will achieve it all together. 

Published On:
May 20, 2025
Updated On:
May 20, 2025
Read Time:
5 min
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AI

How agentic AI is elevating marketers, not replacing them

Agentic AI is shaping a new world in marketing. What does that mean for the humans behind it?

Rebecca Corliss

Rebecca Corliss

Will artificial intelligence replace my role? 

This question is at the top of many workers’ minds today. It’s understandable that some might have this fear; several high-profile companies have announced reorganizations or layoffs in favor of delegating to AI’s automation capabilities. 

Make no mistake: AI can and will flip the marketing world on its head. (In some ways, it already has.) But AI won’t take your job, but someone who has a strength for using it might.

AI (in particular, agentic AI) is enhancing marketers’ roles, so they can move faster, execute great ideas sooner, access the full value of their data, and refine every campaign. Agentic AI is elevating marketers, not replacing them. 

Let’s explore what agentic AI helps marketers achieve, how to build a collaborative AI approach, and how agents and marketers can work together to achieve compound growth.  

The era of agentic AI

AI chat tools like ChatGPT, Google Gemini, and Midjourney have taken the news cycle by storm. Users around the world are experimenting with generative AI for both productive and playful purposes. They enter one or more prompts into the tool, which then generates images, text, or other media.

As AI advances, the conversation is shifting again — this time toward agentic AI. OpenAI continues to make headlines with its Operator agent, which promises to buy groceries and book dinner reservations for users, and self-driving tech like Waymo’s shows us what else is possible with agents. 

Unlike the “prompt, then output” flow of generative AI interactions, agentic AI can complete tasks and even operate autonomously without constant human input. A user sets a clear goal, then the agent processes data, creates a multi-step plan, and takes action to reach the goal. 

A single agent on its own can execute tasks. But multiple specially trained AI agents can effectively function as a team that works together to fulfill a complex objective. And when multiple agents join forces with a user with a clear vision, they unlock a form of collaborative intelligence where a multi-agent system and a human solve a problem as one. 

Comparison of generative ai vs agentic ai

AI agents for marketing teams

Now, let’s put this in the context of the marketer’s role. Day to day, marketers combine creative direction with data-driven strategy based on customer behavior and engagement. AI can’t replicate their instincts or experiences, and it certainly can’t replace the empathy, relationships, and humanity of a marketer. But a team of AI agents powered by company and customer data can help surface insights, execute campaigns, enhance decision-making, and apply learnings from previous campaigns. 

Here’s one scenario: A marketer might prompt a team of AI agents with an objective like, “We need to increase repeat purchases by 20%.” A generative AI tool could provide general tips on how one might do that. But agentic AI can actually take steps to help the marketer reach those goals:

  • One AI agent trained on the customers within your data cloud can recommend the ideal audiences to drive more repeat purchases.
  • Another agent might suggest the right steps or campaigns to encourage audience action.
  • A third agent might conduct external research to uncover helpful context to guide timing and execution.

I like to compare this to the dynamic at a focused, action-oriented marketing team meeting. Each team member usually has specialized expertise and their own tasks to complete, like demand generation, content creation, or data analysis. A team of AI agents operates similarly: Each one is trained on a specific type of task and ready to work toward the objective. 

Agentic AI will elevate rather than replace

Does this mean agentic AI is coming for marketers’ roles? Not at all. Agents will take away tasks, not jobs. Marketers (and leadership) should measure their value in both output and value created. In that regard, agents only make marketers more effective. 

The same mindset shift happens when someone becomes a manager for the first time. New marketing leaders are used to having their hands on a keyboard constantly for high individual output. After transitioning into management, they spend most of their time in meetings, shaping the team’s strategy, and guiding their direct reports. While their individual input goes down, the total input they influence (that of their team) increases dramatically.

Whether they’re overseeing a team of human marketing specialists or AI agents, a marketing leader harnesses their interpersonal leadership skills and big-picture company vision to inspire the team to achieve amazing things. No matter how much agentic AI advances, that’s a role only an experienced marketer can play. 

Creating a more collaborative approach to AI

Agentic AI can operate more autonomously than most of the tech that came before it, so many people see it as a “set-it-and-forget-it” tool. Why not, if it can complete tasks on its own, right?

Not so fast. As marketers start to lean more on agentic AI, the path forward is collaborative

Remember, marketers bring essential insights, experiences, and firsthand knowledge to the table. A collaborative AI approach lets them contribute their unique expertise while working with agentic AI to reach a shared outcome. With that, a team of AI agents should collaborate with each other, with the data, and with a marketer at the helm, asking for additional input and making proactive suggestions for the marketer to accept or reject. This back-and-forth unlocks the efficiency and speed that agentic AI promises, and promises greater outcome by leveraging the expertise and greater strategic context that marketers have.

How can AI help me with this? 

To embrace and adapt to the new normal of agentic AI, marketers will need to form new habits and a new, collaborative AI mindset.

Nine out of 10 marketers use AI in their roles, from idea generation to editing copy to research. But in many cases where AI could be incredibly useful, their instinct is still to recruit a human’s help. 

A more collaborative approach to AI starts with building it into as many workflows as possible, starting with generative AI tools. Throughout the day, marketers should pause to ask themselves, “How might AI assist me with this?” As they ask themselves this question and experiment with prompts, workflows, and use cases, they’ll learn to recruit AI’s help with creating text or graphics by default. 

AI is all about the art of the possible. Whether marketers are creating a flyer for a personal passion project or need to get unstuck during a marketing sprint, they should stop and consider where generative AI could be useful and experiment. That’s the first step to thriving with more advanced agentic AI use cases.

What direction does AI need from me?

There’s an important parallel to be made between the management of people and the management of agents. The better direction leaders provide, the greater their total output will be and the better the results. A roster (or “team”) of AI agents needs guidance, just like that team of human marketing specialists you lead. 

Marketing managers need to give agentic AI precise marching orders to reach the ultimate goal and produce the right output. This includes providing detailed context and direction to ensure agents take the right steps. Instead of asking an agent to create an audience as a one-off task, they should share more about the big-picture objective they want to achieve that the audience fits into. This invites more back-and-forth engagement between the marketer and agent, so both can lean on their strengths.

With thoughtful human intervention, agentic AI can improve the speed, depth, and results everyone can achieve within the same number of hours in a day. That means every marketer, from the newest hire to the most senior exec, can achieve more.

But a human marketer will always be most advantaged to set a goal, provide strategic context, and offer direction, and confirm the output will drive the required outcome. Even with a team of AI agents, someone always needs to be in the driver’s seat to provide an initial prompt and supervision.

The three ingredients for agentic AI success

The 3 ingredients for agentic AI success

AI agents can solve complex problems more simply by taking time-consuming tasks off marketers’ plates and out of their project workflow. But agents don’t operate in isolation. They need three foundational elements to succeed. 

  1. Marketers’ prompting skills. We’ve said it before, and we’ll say it again: A human marketer needs to be in the loop for AI success. No matter how advanced your AI agents, they won’t help your organization grow if you have the wrong goals and strategy from the outset. Marketers need to bring the right objectives relative to their audience. They also need to develop the prompting skills to get the best out of AI agents and achieve the ideal outcome.
  2. Data as a differentiator. You don’t have an AI strategy if you don’t have a data strategy. If every other marketer on the planet has advanced AI prompting skills, how are you going to win next? Your ability to give AI agents access to your data is what will set you apart. AI agents need as much context as possible: information about your business objectives, your customers and their product usage, your marketing, sales, and more. Give them the most comprehensive possible view of your company’s world to set up your agents for success. 
  3. The agents themselves. As agentic AI advances and becomes more sophisticated, so will marketers’ ability to use it and accelerate their results. Technology companies are responsible for providing and enhancing this piece of the agentic AI puzzle, which has to happen before marketers can go deeper with agentic AI.

Even with advanced analytical and execution skills, agentic AI still needs a human to oversee its output and check its instincts, along with robust data to inform its decision-making. Marketers will see the best results when they know how to leverage all three together. 

The future of marketing is bright

AI in its many forms is an advisor to the human marketers it supports. Like any advisor, AI needs real people to listen to its suggestions and insights and decide whether to move forward.

AI outputs might inspire a better idea, clash with historical knowledge the marketer has, or go against a gut instinct based on years of experience. Someone needs to stay in the driver’s seat, offering oversight, judgment, and creative vision. 

That’s why AI agents are such an exciting proposition. They’re here to help marketing teams accomplish more and achieve better results with every campaign. And with a collaborative AI approach, marketers and agents will achieve it all together. 

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