Top use cases of agentic AI in marketing automation

Great marketing is much more than just telling the world about your products and services. A simple brochure can do that. Marketing is about creating value, relationships, and trust with your customers.

Agentic AI in marketing can help marketers achieve these goals much more effectively. Imagine you’re a marketer and you just deploy a set of AI agents to create customer profiles, optimize customer journeys, and set data-based goals within seconds. This would take entire teams weeks or months to do otherwise.

However, some marketers feel that AI will replace their roles. But the truth is quite the opposite; agentic AI solutions are here to elevate marketers, not replace them.

In this article, we’ll discuss the transformative role of Agentic AI in marketing and its four major use cases. In the end, it will share some advice for marketers and CMOs on how to prepare for this change.

Brush up your AI literacy: What is agentic AI?

You’ll probably have been hearing about agentic AI a lot these days. AI is the zeitgeist of our times, so you should know what these terms, agentic AI and generative AI, really mean.

Agentic AI is the third wave of artificial intelligence. It embodies AI systems that can perceive their environments in real-time and make independent decisions with little or no human supervision. AI agents autonomously take strategic actions to accomplish their tasks.

Moreover, they learn and improve with every interaction. So, let’s say an AI agent encounters a problem its system doesn’t have the preset rules to solve. The agent will simply process the data from its environment to improvise and find a way to solve the bottleneck.

Agentic AI doesn’t just tell you what you should do, like generative AI. Instead, it does it for you.

Agentic AI in marketing: Start of a new era

So how does agentic AI make sense in the context of a marketer’s role? The best way to explain that is through the role of a scout in professional sports. You probably know that major sports teams have a network of scouts to find young, raw talent that they can nurture in the future.

These scouts relied on firsthand observations and their prudence to sniff out exceptional talent like Ronaldo from the rest. However, modern scouts now use data analytics to analyze a player’s every move from thousands of points.

Agentic AI in marketing augments the role of marketers in the same sense. AI agents can perceive their environment and make decisions to spot cues about customer behavior and market trends that the human eye can overlook. Such Agentic AI use cases in marketing operations help find the most promising prospects and nurture them into long-term customers.

Marketing teams can use AI agents to continuously improve ways to connect with their customers. And the best part? They don’t have to be around all the time since agentic AI is goal-driven. It will perform tasks on its own to achieve the set goals in a powerful way.

Four ways agentic AI in marketing is a godsend

“How can agentic AI be used in marketing?” The potential agentic AI use cases in marketing are quite vast. Some of them are still in the pipeline, while others have already shown their value to businesses. Moreover, agentic AI is still a developing technology, so the complete range of its applications is yet to be seen.

For CMOs who want to best capitalize on the benefits of agentic AI in marketing, these four core agentic AI applications in marketing can meet their expectations.

Lead identification and outreach
Sales optimization and customer engagement
Full-funnel automation
Impact measurement

1. Lead identification and outreach

Leads, leads, and more leads. These are the first, second, and third priorities of every marketing head. However, many CMOs don’t realize or bother to ask whether their marketing team has the capacity to churn out that many leads regularly. Particularly, identifying and finalizing B2B leads is a rigmarole.

Agentic AI in marketing is a relief for marketers under constant pressure to generate leads. AI-powered assistants can handle early-stage outreach on their own. An AI agent can analyze data to score leads and find which prospects are most likely to convert. For those leads, you can write personalized emails using details like past purchases and inferred interests, or instruct the agent to do it autonomously.

Furthermore, AI agents constantly learn to understand what makes a qualified lead. For example, an AI agent might notice that leads from generative AI companies that interact with specific types of content are more likely to convert. It will then adjust its model to look for more prospects like those.

2. Sales optimization and customer engagement

Sales and marketing go together in most enterprise settings. Agentic AI in marketing makes sales operations smoother by speeding up complex tasks. During the sales process, AI agents can expedite tasks that usually take hours, such as creating proposals.

This is really beneficial in two situations:

You are a large enterprise with hundreds of leads
You offer complex products or services with complicated pipelines

AI agents also help move deals forward faster by scheduling meetings and automatically logging interactions in CRMS like Salesforce.

Additionally, agentic AI in marketing makes decisions in real time based on each customer’s responses and data. They design unique programs for every prospect and pinpoint them at the best moment to engage.

3. Full-funnel automation

The marketing funnel encompasses the entire customer journey. With AI transforming the future of content management, marketers need to optimize their content for each stage of the funnel differently. Regular automation does that to some extent, but it’s entirely rules-based and limited in its capacity.

On the other hand, agentic AI in marketing automation takes a customer from the first moment of awareness and retains them through post-purchase engagement without manual intervention at every step of the funnel.

Agentic AI in marketing doesn’t treat the top, middle, and bottom of the funnel as separate processes. Instead, it connects them into a single, data-driven flow through full-funnel automation.

At the top of the funnel, AI agents can use behavioral and intent data to identify high-fit prospects across channels. Then, the middle of the funnel is about building trust, which AI agents can do through personalized communication.

And finally, when a lead reaches a certain score or shows buying intent, it’s routed directly to a sales rep with context-rich data.

4. Impact measurement

Understanding the impact of a marketing campaign is crucial for any marketing team. However, it is very difficult to accurately measure how well your marketing efforts are paying off because interactions are fragmented and multi-channel. Especially, measuring the ROI of agentic AI in B2B marketing automation can take years.

AI agents make it much easier to see which prospecting activities actually lead to sales. They track things, such as the best-performing marketing content, channels that deliver the most value, and the ideal timing for closing deals.

Additionally, agentic AI in marketing continuously monitors what works and what doesn’t. This also unites sales and marketing teams around a shared understanding of what drives growth.

Rethinking marketing roles and responsibilities with agentic AI

Early on, we said that AI agents will only augment the work of marketers, not replace them. But that doesn’t mean that agentic AI in marketing will not change the roles and responsibilities of marketers.

There will be some reshuffling of the marketing workforce. And preparing yourself for this coming overhaul is necessary for your continuous professional development.

So, how can you, as a marketing professional, adapt to the AI age? Well, we recommend that you start using AI agents in your smaller daily tasks as soon as possible. Don’t be a Luddite, if you’re an early adopter of agentic AI in your marketing workflows, it will give you valuable experience through trial and error.

Here are some great starting points to begin implementing agentic AI in marketing:

Content research and ideation
Social media scheduling
Email personalization
Automating simple repetitive tasks

Once you get the hang of it, you’ll learn how to manage multiple specialized AI agents. You can target different functions with designated agents. And depending on how much control you want, these agents can be more autonomous, capable of breaking big tasks into smaller ones and designing their own intelligent workflows.

A word for CMOs

For C-level executives, implementing agentic AI in marketing also means redesigning their enterprises. And no, it doesn’t just mean cutting down jobs and handing everything over to AI. Many Agentic AI projects are failing due to this flawed implementation strategy.

Rather, train your staff for AI oversight, strategy, and orchestration. It would also be great if you introduced new hybrid roles, such as Agent Supervisor, Prompt Engineer, or AI Workflow Architect.

Conclusion

Marketing is all about communication. And technology has shaped how we communicate in each era. The Romans had town criers who, in many ways, were the original social media. Fortunately, with AI, marketers don’t have to shout their lungs out to get their message across.

Agentic AI in marketing will change marketing operations as we know them. It goes beyond mere automation. AI agents are digital members of marketing teams that perform tasks faster and more effectively than humans.

However, that doesn’t mean humans have no part to play in the future of marketing. They will remain integral in the planning, execution, and analysis of marketing efforts. Only their methods and roles will change, which is something both marketers and CMOs need to prepare for.

Do you want to ensure that your business is ready for this shift? Partner with Xavor’s agentic AI development services to implement agentic solutions in your workflows effectively. Our AI experts evaluate your needs in specific domains like marketing and develop AI agents that deliver tangible business value.

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