A technology company recently reported a 73% increase in campaign ROI within six months, all thanks to an AI agent that made 2,847 optimization decisions their marketing team would’ve needed years to complete manually.

This isn’t science fiction. It’s the new reality of marketing leadership.

As more CMOs explore the potential of generative AI, a new wave of innovators is already stepping further – into the agentic AI era, where intelligent systems can analyze data, optimize workflows, and even collaborate on decision-making.

But what does this really mean for marketing leaders? How do you get started? And which tools or team structures actually work?

To get real answers, we hosted another Mavuus Coffee Chat with two experts shaping the future of AI in marketing:

• Jonathan M Kvarfordt – Head of GTM Growth at Momentum.io and founder of GTM AI Academy. With experience training teams at AWS, Google, and Seismic, Jonathan brings a deep understanding of how AI can power go-to-market strategies.
  
  
• Justin Parnell – Head of Marketing at GrubMarket and founder of JustinGPT, a boutique consulting firm specializing in production-ready agentic AI for GTM teams. Justin blends hands-on marketing leadership with practical AI implementation experience.

We discussed what it takes to move from experimentation to execution with AI agents and how CMOs can start seeing real ROI in months, not years.

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Table of Contents

1. From Generative to Agentic AI: How Far Should You Go?
2. Where to Begin: Identifying High-Impact Use Cases
3. How Other C-Level Executives Are Leveraging AI Agents
4. Choosing Tools and Structuring Your AI Workflows
5. Resources and Experts to Follow

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From Generative to Agentic AI: How Far Should You Go

Generative AI tools like ChatGPT or Midjourney changed how marketing teams create and analyze content. But Agentic AI takes things a step further. Instead of waiting for human prompts, agentic systems can act on their own, making decisions and completing tasks in the background.

Think of it as moving from “AI that helps you” → to “AI that works for you.”

Still, most companies are somewhere in the middle of that spectrum. According to Deloitte, around 80% of senior marketers feel they’re behind in understanding how far to let AI take control, and that’s exactly where Agentic AI becomes both exciting and confusing.

As Jonathan explained during our coffee chat:

“To me, agents come down to how much agency or control you’re giving them. ChatGPT, for example, needs a human to prompt it. A full-on agent can act without you being involved. Most companies still keep a human in the loop.”

He gave the Deep Research example – a process where hundreds of AI agents work in the background to analyze data and return summarized insights. You never see the steps, only the final, refined result.

👉 Watch the short snippet below to hear Jonathan explain what Agentic AI really is and how Deep Research works in practice.

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Where to Begin: Identifying High-Impact Use Cases

The easiest way to get started with agentic AI is to avoid the shiny-object trap and focus on your most critical KPI – the one that directly moves business results.

Ask yourself: What’s the one area where faster decisions or better automation could move the needle the most?

Once you know that, you can design an agentic workflow around it. For example, if your main goal is lead conversion, your first agent might monitor and analyze sales calls, update battle cards, and flag key objections for your team.

During the session, the speakers shared several real-world use cases CMOs are already experimenting with:

• Sales call intelligence – agents listen to sales calls and automatically revise battle cards based on real-time objections and customer pain points.
• Competitor monitoring – agents scan industry news, analyze competitors’ messaging, and send summarized updates directly to your inbox.
• Inbox management – agents sort, summarize, and prioritize daily emails to keep executives focused on strategic tasks.
• Content curation – agents read your favorite newsletters and summarize the most relevant insights for your team.

For practical guidance, Justin Parnell shared a simple approach to get started:

“Think about whatever KPI you’re trying to influence, and then go into your LLM of choice and ask: ‘Hey, I want to influence this KPI with AI. What are some potential workflows or agents or ideas that you have for me?’”

👉 Watch the short snippet below to hear Justin explain how to brainstorm agentic AI workflows starting from your KPI.

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The key takeaway: start small, stay specific, and measure results early. Agentic AI becomes powerful not through scale, but through well-defined problems it can solve consistently.

How Other C-Level Executives Are Leveraging AI Agents

AI agents are becoming everyday partners for executives across departments, transforming the way teams work. Many leaders now rely on them to manage repetitive tasks, analyze data, and even support decision-making.

Here are some of the ways C-level executives are already using agentic workflows:

1️⃣ Organizing communication – AI agents review and categorize daily emails, summarize long threads, and highlight messages that require immediate attention. This helps executives stay focused on strategic decisions instead of getting lost in their inbox.

2️⃣ Writing social content – executives use agents to draft, schedule, and optimize social media posts. Agents can suggest variations, track engagement metrics, and ensure posts align with broader brand messaging, saving hours each week.

3️⃣ Thought partnership – many leaders treat AI as a sounding board for new ideas. Agents can run simulations, test messaging, and provide alternative perspectives, giving executives a safe space to explore strategies before taking action.

4️⃣ Digital twins for teams – some leaders build digital counterparts of their teams to simulate projects, predict outcomes, or test different business scenarios. This helps identify bottlenecks, forecast results, and make better-informed decisions.

5️⃣ Technology evaluation – AI agents help research and assess new tools, summarizing features, pros, cons, and integration options. This allows executives to quickly compare solutions and decide which technologies to adopt without spending hours on manual research.

The shift is clear – AI is no longer a sidekick for marketers; it’s becoming a trusted partner for leadership. By observing how executives across roles are integrating these systems, CMOs can better understand where agentic AI can deliver the most impact within their own teams.

Choosing Tools and Structuring Your AI Workflows

Once you’ve identified the high-impact KPIs to focus on, the next step is building a strategy that combines the right tools with the right team structure.

Choosing the Right Tools

Starting simple is key. For marketers just getting started with agentic AI, Zapier is a great place to begin. It lets you experiment with automations and workflows without any coding, making it easy to see results quickly and learn the basics.

If you’re looking for something more powerful, n8n offers greater capabilities. This open-source platform can handle complex workflows and integrations, though it does require more setup and technical know-how.

For teams ready to build chat-based agents, OpenAI Agent Builder is a strong option. It allows you to deploy conversational agents that can interact directly with users or other systems, making it ideal for practical, real-world applications.

Structuring Your Team

Even the best tools won’t reach their potential without a clear human-AI workflow. Most companies today use a hybrid model, where humans stay in the loop for decision-making, oversight, and strategy, while AI agents handle repetitive, time-consuming tasks. This approach ensures both efficiency and accuracy while allowing teams to scale their capabilities quickly.

Starting small, experimenting with a few workflows, and gradually expanding to more complex integrations is the recommended approach. Over time, this hybrid model becomes a foundation for scaling agentic AI across marketing, operations, and beyond.

Resources and Experts to Follow

Learning from others is one of the fastest ways to get up to speed with agentic AI. The speakers shared several resources and experts who regularly discuss AI workflows, strategies, and practical applications for marketers and executives.

• MATG Podcast – Hosted by Kipp Bodnar and Kieran Flanagan, this YouTube channel dives into marketing, AI, and growth strategies.
• How I AI Podcast – Hosted by Claire Vo, this podcast explores AI in marketing and business with practical insights.
• Kyle Poyar – A LinkedIn thought leader focused on AI, SaaS, and go-to-market strategies.
• Emilia Moller – Shares insights on marketing technology, AI, and innovation for business leaders.
• Liza Adams – Covers AI, marketing strategy, and practical applications of emerging technology.

Following these experts and channels is a great way to stay informed, discover new AI use cases, and learn best practices directly from professionals experimenting with agentic workflows.

Want to Learn More About AI in Marketing?

At Mavuus, we’re all about helping marketing leaders stay ahead of the curve with AI, growth strategies, and industry insights. Our community shares best practices, hosts interactive sessions, and connects professionals who are exploring the future of marketing together.

If you want to learn and collaborate with other forward-thinking marketers, consider joining Mavuus. Be part of a network where ideas turn into action and conversations lead to results.

👉 Join Mavuus today and start exploring the world of AI-driven marketing with peers and experts.