It’s no secret that generative AI tools have transformed the way we do marketing. Now, agentic AI is set to take everything to a whole new level.

AI agents don’t simply produce content on request, but can plan, make decisions, and execute tasks to achieve a defined goal, all with minimal human input. 

This evolution represents a completely new way of working with AI, and with technology itself. For marketing and CRM teams, this shift will be transformative, lightening the load of execution so you can focus on strategy, creativity, and creating better customer experiences. 

In this blog, we’ll break down exactly what agentic AI is, where it’s headed, and how it’s set to change your work as a retail marketer. 

Contents

What is agentic AI?

Agentic AI vs AI agents

Agentic AI vs generative AI

Agentic AI benefits

Agentic AI for marketing

Agentic AI use cases

Architect AI™ by Ometria 

What is agentic AI?

Let’s start with a simple definition. 

In a nutshell, agentic AI is a system which takes actions toward a defined goal. Through a combination of large language models (LLMs), natural language processing (NLP), and machine learning, agentic AI can plan, make decisions, and carry out tasks autonomously, coordinating across systems to achieve a goal.

Going far beyond just writing emails or generating product recommendations, agentic AI can: 

• Build end-to-end campaigns
• Identify impactful audiences
• Suggest and implement ways to optimize campaigns
• Tailor content based on individual behaviors, tastes, and preferences
• Help you extract answers from your data 

Agentic AI vs AI agents 

Though they may sound similar, they’re not quite the same. 

AI agents are the individual actors within an agentic AI system, each responsible for specific tasks or decisions. While agentic AI refers to the overall system, AI agents perform particular roles within that system.

For example, one agent might analyze customer data to build audience segments, another might generate campaign templates, while another handles external integrations like API calls. 

Or, you might embed agents with different ‘jobs’ within an automation campaign, one making the decision on the best channel, one on the timing, one on frequency, and beyond. These agents can work independently or together, with some overseeing and coordinating the work of others.

Agentic AI vs generative AI

With nearly 40% of US adults now having used generative AI, this tech is a familiar concept to many; so what makes agentic AI different?

You can think of Agentic AI as a natural evolution of generative AI. Whilst generative AI only produces content in response to a prompt, agentic AI takes these generative capabilities and rolls them into a wider system which is constantly analyzing and acting on your data.

The key difference is that agentic AI doesn’t require constant human supervision and input to carry out a task. Instead, it works continuously in the background to achieve the goals you set, autonomously adapting to new data, solving problems, and improving its approach as it progresses.

But fear not! Though agentic AI can act autonomously, we’re not on the cusp of an AI free-for-all where bots run around making decisions unsupervised. Human marketers will still call the shots, able to set boundaries and check in on agent activity. 

Agentic AI benefits

We’ve established what agentic AI is; but what can it actually do for you?

Agentic AI removes a lot of the manual work of marketing, whilst also unlocking deeper layers of insight into your customer data. That means less time spent on day-to-day execution, and more time spent on strategic initiatives and crafting exceptional customer experiences. 

Here are a few of the key benefits of agentic AI adoption for retail businesses:

• Greater efficiency and reduced costs by automating repetitive tasks like campaign setup, audience segmentation, and performance reporting.
• Smarter, faster decision-making through real-time analysis of customer behavior and sales trends, enabling more targeted and effective marketing campaigns.
• Accelerated time to market with AI agents handling campaign execution, content generation, and optimization at speed, marketers can respond quicker to trends and seasonal opportunities.
• Improved customer engagement and loyalty by delivering highly personalized offers, recommendations, and content tailored to individual customer preferences.

Agentic AI for marketing

Let’s zoom in on agentic AI in the marketing world specifically, where the arrival of this technology is set to completely transform how we create personalized customer experiences. 

Is time up for workflows?

The arrival of agentic AI could make marketing workflows - the step-by-step processes that marketers have long used to create personalized customer experiences - a thing of the past. 

For the past decade, workflows have been the marketing gold standard. They allow marketers to plan and build a path for their campaigns to follow, defining segments, triggers, rules, and more to craft an engaging journey that runs automatically.

The trouble is, whilst workflows are functional and often effective, they’re also time-consuming for marketers to create. Every segment, every channel, every message, and every detail has to be selected by hand. And ultimately, the flow is static; it can’t learn, predict, or adapt to new information in real-time. 

A turning point for personalization

Agentic AI will flip this personalization paradigm on its head. Because it’s able to constantly assess, analyze, and act on customer behavior in real-time, it can free your marketing from the limitations of a step-by-step workflow. 

Rather than spending hours painstakingly creating campaign workflows by hand, you’ll only need to define your goal - for example, to increase your repeat rate, reactivate lapsed customers, or boost sales for a new product line - and AI agents will handle the rest. 

With an objective in mind, the AI agents will get to work crafting the perfect campaign. One will build the right audience, whilst another drafts the best messaging, all working in harmony to create a pitch-perfect campaign. 

And they don’t stop there. Further agents will ensure everything is tailored to each customer as an individual, from the channel, to the timing, to the perfect product recommendations for them. 

In short, agentic AI is finally making the marketing dream come true: enabling teams to send the right message, on the right channel, at the right time, at scale - effortlessly.

It marks the beginning of a new era of marketing. One which is truly dynamic and flexible, with fewer one-size-fits-all workflows, and more fluid, personalized 1:1 interactions that happen continuously in the background.

A new way of working with technology

So, what will working alongside AI agents actually look like?

Much like how many of us use ChatGPT today, you can expect to work with agentic AI through a conversational interface, prompting, receiving information in response, and prompting again to achieve whatever your strategy calls for. 

In fact, looking much further down the line, it’s possible marketers won’t even need to use software in the way they do now to build campaigns or monitor results. You’ll simply communicate requests to an AI agent, which will then devise, execute, and continuously monitor a truly data-driven solution tailored to your business.

Want more detail on how agentic AI is set to revolutionize retail marketing? Check out our official deep dive: The Retail Marketer's Guide to Agentic AI.

Agentic AI use cases

Now we’ve covered the theory, let’s talk about agentic AI in practice.

Below, we’ve outlined 4 powerful use cases where AI agents could help you better understand your data, optimize campaigns, and ultimately unlock the kind of customer experiences that make everything else feel outdated.

A Customer Data Platform (CDP) is the foundation of a successful AI implementation as it provides the clean, complete data that AI needs to make accurate decisions. AI that is trained on or that operates with only part of your customer data, for example in an ESP or other point solution, won’t have the full picture it needs to be truly effective. 

Use case 1: Data exploration and strategic planning

Marketers depend on customer data to make informed strategic decisions, yet gathering and analyzing that data is often time-consuming. 

AI agents can make this process easy by allowing you to directly query your data, asking iterative questions and getting the answers you need, all without opening a single spreadsheet. 

Not only is this quicker, but it’s also more effective. The agent can surface trends and insights from within your data that humans simply wouldn’t be able to detect, allowing you to act with confidence. 

In practice: You ask the agent, ‘How many customers lapsed in Q1 compared to the same period last year?’ The agent analyzes your data and delivers an answer in seconds, not days, surfacing key insights proactively as well as on demand.

Overall impact: Faster answers from your data, deeper customer insight, and the confidence you need to make strategic adjustments when you need to.

Use case 2: Audience generation and predictive insights

Traditionally, audience segmentation has been a very manual process based on basic attributes like gender. But with AI-powered predictive insights, you’ll gain insight into how customers are forecasted to behave, allowing you to be more proactive in your segmentation and campaign planning.

In a nutshell, predictive insights are data-driven predictions about future outcomes. They use inbound customer data, statistical algorithms, and machine learning to identify patterns and relationships that can forecast what might happen next.

Say you’re planning the launch of your new summer handbag collection. Instead of spending hours creating a broad audience from basic attributes (e.g. past handbag buyers or recent site visitors) you could simply ask an AI agent to “Build an audience most likely to purchase our new summer handbags.” It would go beyond surface-level data to find those most likely to convert.

In practice: Sephora UK used Ometria’s predictive segmentation to send personalized newsletters based on each subscriber’s brand preferences, as identified by machine learning. The result: a 95% uplift in revenue per email.

Overall impact: Smarter targeting, higher engagement, and increased ROIs from every campaign you send.

Use case 3: Building campaigns and templates

Modern marketing campaigns span multiple channels and touchpoints, but planning and execution are often time-consuming. Teams must decide channels, coordinate content creation, and manually build templates, often relying on assumptions or past experiences to make decisions.

AI agents can make this quicker and more accurate, suggesting optimized campaign flows, generating branded templates, and even auto-populating content with personalized product recommendations. They handle the heavy lifting, so teams can focus on strategy and fine-tuning.

In practice: You’re launching a new summer dress collection. Your AI agent reviews your data to predict the strongest channel mix for this audience, builds the flow, creates the templates, and writes the copy. You simply review and hit launch.

Overall impact: Cross-channel campaigns get to market faster with greater accuracy and relevance, giving you more time to focus on strategy.

Use case 4: Campaign optimization

As marketers, we know that to maximize the ROI from any campaign, it’s not enough to simply launch and hope for the best. You need to respond quickly to customer signals and make adjustments on the fly, or risk leaving money on the table. 

AI agents shift this process from reactive to proactive. They continuously monitor campaigns across channels, flagging performance trends and anomalies the moment they appear. Instead of just reporting, agents explain what’s driving results, suggest the next best action, and even implement optimizations like pausing underperforming variants or targeting high-value segments.

In practice: Your AI agent alerts you that your summer sale email had a 20% higher open rate among past swimwear buyers, and recommends you target them with early access to the new collection. 

Overall impact: Relevant insights and recommendations are raised in real-time, maximizing campaign ROI and allowing you to respond faster to customer behavior. 

A new era for marketing

Agentic AI is far from just another tool. It’s tech that will unlock a whole new world of possibilities for delivering exceptional customer experiences, change how we use technology, and ultimately reshape how we think about work itself.

Interested in what this game-changing technology could do for your business? Why not get in touch with one of our expert team here.