Do you use generative AI to help you complete specific tasks, like writing a blog, summarising a transcript or generating a headline? So do I; AI has become my team mate, assisting with research at lightning speed, organising idea dumps and quickly playing out different scenarios.

It has been a game changer for productivity. I’ve recently also started testing agents to manage my inbox, summarise campaign performance and save even more time. For this reason I find the new wave of autonomous software that is emerging with agentic AI incredibly exciting. Instead of waiting for a prompt, agents take a goal, work in the background and figure out how to get to the final output. It is reshaping how many of us work, especially in marketing.

So what happens when AI isn’t just something we use, but something that works for us?

Moving from task-based help to goal-oriented operations

Unlike a one-off AI prompt, agents are autonomous systems that can:

• perceive (read data, scan websites, interpret reports),
• decide (choose which action to take next),
• act (complete steps like filling forms, sending emails, booking meetings) and learn over time.

You don’t tell them what to do, you tell them what outcome you want. For example, instead of downloading reports, cleaning up metrics and writing a performance summary, an agent autonomously retrieves the data, spots trends, flags anomalies and drafts the weekly marketing update.

In many ways, agents will become our interns, assistants and operations managers rolled into one.

Why AI agents change everything for marketing leaders

Here’s what I’m paying attention to as a CMO.

Resource and time allocation 

Together with strategy and execution, we’re adding strategic AI orchestration to our job descriptions.

Tasks like reporting, campaign tagging, segmentation, writing internal updates and building briefs take up a considerable amount of time for marketing teams. 

With agent-led workflows able to complete these tasks, the work for marketing teams shifts to designing, supervising and optimising agent behaviours. This represents a big opportunity particularly for lean teams, enabling marketers to repurpose their attention to anything from testing and learning faster from campaigns, to entering new markets at an increased speed.

New capabilities

Most SaaS tools today rely on APIs (Application Programming Interfaces). These let systems talk to each other in a structured way. In marketing, APIs define interactions between tools to:

• push data from forms into CRMs,
• sync performance data into dashboards,
• connect platforms like HubSpot, Google Ads, Slack and Segment.

AI agents on the other hand simulate clicks, interpret visual interfaces and fill in fields like a human would. They can do this without needing pre-defined API access, and when APIs are available, agents reason, adapt and act based on context instead of just push or pull data. 

For marketing teams this means they’re no longer just asking “Can these tools integrate?”, but “What goals do I want the system to achieve and what guardrails, such as access and context, should be in place?”

Training marketing teams to use AI

In a world where content is increasingly AI-generated, originality, relevance and credibility become your differentiators. We’ve already seen posts online that feel like they were written by the same LLM with no point of view.

The risk is that when everyone starts sounding the same, the audience tunes out and agents, which will soon be filtering content for users, will do the same.

Aside from training your agents to represent your brand, tone and values, the human layer becomes essential to produce strategic marketing initiatives that get nuance and apply a combination of learned experience and insights.

Tooling up for the AI transformation

Here’s what I’m exploring next. I’m watching platforms like Crew AI, Lindy and emerging marketplaces like Agent.ai and I’m curious about how large players such as Hubspot are building out their agentic ecosystems.

As AI agents redefine the marketing stack, as marketers we need to know how to train them. I’m therefore also asking myself:

• How many of our current marketing workflows can be agent-led?
• Where do humans still need to stay in the loop?
• What happens when agents start talking to each other instead of waiting on us?

How are you preparing for the AI shift?