3 essential change management steps for agentic AI success

Agentic AI is more than a cutting-edge technology; it’s quickly becoming a competitive essential and catalyst that will forever change how organizations operate — and we’ve only just begun to see its full potential. 

Most teams are still learning how to adapt their infrastructure and workflows to effectively integrate AI. However, the window of opportunity is quickly closing, according to the 2025 AI and Marketing Performance Index:

• Organizations achieving the greatest revenue growth are also more likely to use AI in their marketing processes.

• Using real-time data to adjust campaigns is proving vital for high-growth organizations to stay ahead.

• Two-thirds of marketers describe their campaign cycle as either “unacceptably slow,” “somewhat slow,” or simply “manageable.

Early AI adopters have revealed some of the best use cases in marketing — as well as the common hurdles teams will face in hitting their stride. We shared learnings from these organizations and offer one blueprint for how you can transform your marketing team in the age of agentic AI in our agentic marketing organization eBook.

To further discuss the future of marketing and strategies for success, we connected with two technology innovators to hear their thoughts. Let’s explore takeaways from our conversation on building a foundation for your AI future with Murat Genc, The McClane Co. president and chief information and digital officer, and Suresh Susarla, director of engineering martech at AT&T.

3 change management essentials for agentic AI

Despite decades of technological advancements, marketers still grapple with the same challenges: 

• Collecting, unifying, and standardizing customer data

• Gleaning insights to build segments and inform outreach strategies

• Learning from campaigns to iterate and improve results

Agentic AI can now greatly accelerate and improve these workflows, but it isn’t a plug-and-play solution. 

“Agentic AI is forcing marketers to know more about their data [and] the power of their first-party data,” Suresh said. “There are a lot of areas to bring in efficiency. Tools are popping up to accelerate [any task], whether it is ideation or testing, prototyping a strategy, or doing a test; and feedback cycles are getting shorter and shorter.”

The challenge is that many organizations aren’t designed to effectively leverage agentic AI. Tools, processes, and team structures built for past realities are no longer fit to integrate AI effectively. 

Activating the power of AI requires marketing leaders to lead change management across three key areas in particular: Technology, people, and ongoing transformation. 

Technology: Centralize and democratize data access

Marketing’s success with AI rides on first-party data, because AI is only as powerful as the data it can access. 

Technology stacks must preserve the single source of truth for customer data and ensure data flows seamlessly across each system. Transitioning to a composable marketing architecture is the essential first step for establishing a flexible toolset that maintains data integrity, including:

• A cloud data warehouse, which is the sole data storage location.

• A composable activation layer, which uses an audience or orchestration tool like a Compound Marketing Engine to pull data from the warehouse and activate it across different channel tools.

• An agentic AI-powered toolset that helps marketers surface ideas for audiences, journeys, and campaign optimization — all powered by the first-party data and customer 360 in the enterprise cloud.

“A very strong cloud-based data foundation is critical. It’s almost like the nerve center of your AI activation and it’s also [critical] for security and flexibility,” explained Suresh. “The second layer is the composable layer of activation where you can bring in the best-in-class tools connected to your data cloud. The last is bringing in those agentic AI-powered toolsets and identifying the use cases where it could be most appropriately leveraged, very quickly.”

Teams used to have limited options on which tools they could consider, however, there is now a proliferation of technology options — meaning teams can purchase composable solutions and get up to speed rapidly, instead of building a proprietary, in-house solution or getting locked in to a monolithic marketing suite. 

“With AI, building things is already a lot easier. But the fact that you can build it doesn’t mean you should,” Murat said. “Tools like GrowthLoop provide an off-the-shelf solution to build audiences in an algorithmic way with AI. Since there’s already a tool built, you can probably get a lot of speed to value and speed to scale.”

Team structure: A new org chart for agentic AI

The right technology foundation unlocks new workflow efficiencies, and it also requires a new team structure so everyone can provide their greatest value. We anticipate organizations will move toward a three-layer organization:

• Leadership

• Marketing intelligence

• Business pods

The agentic marketing organization eBook provides a framework to build this model, with greater detail on key roles and functions across each level.

Suresh and Murat agree with this vision, and they emphasized that every team must embrace experimentation and testing to find the best blend of human and AI expertise. 

“There is a cultural shift of testing. We don’t know what perfect looks like, so as you’re selecting tools and writing the workflows, the team culture should encourage risk-taking and strategy testing to learn from the mistakes and pivot quickly,” said Suresh.

Humans must stay in the loop for all processes, especially customer-facing messages and activities. Organizations will perform best when team members are empowered to use AI to surface critical insights that inform ongoing testing and improvements. Replacing humans without a strategic reason is likely to hurt campaign performance. 

“Sometimes people quickly jump to ‘the machine is going to replace the human.’ I’m looking for how the machine can power humans and free them up so they can focus on even more creative and emotional tasks to be done, which is the higher order of value,” said Murat. “How can I train humans and move them up in the chain? If you can combine people with great customer obsession and understanding with their technical ability and hands-on AI experience, they are going to be the next-gen unicorn talent. They can actually both execute great campaigns and do them really fast and at scale.” 

Transformation: Ongoing testing and learning 

The new technology foundation and team structure in an agentic marketing organization provide a scalable foundation for integrating AI across functions. The focus then becomes: 

• Empowering the team in its new ecosystem

• Finding the highest-value starting points for AI

• Ensuring your learnings scale

“You need to dream big with AI, but at the same time, you can only execute at the speed of your people. So start with a few priorities first.” Murat said. “But eventually, you have to escape what I call ‘pilot gravity’. Whatever you are seeing work [with AI], scale it to fit your company.” 

Identify time-intensive tasks where AI can provide immediate value, such as audience segmentation, journey orchestration, or campaign analysis. Assess the workflow with and without AI to understand where AI provides value, and what training your team may need to effectively partner with AI for the workflow. 

Repeat this process and implement AI in steps to give team members space to work through challenges and consider better, more effective ways to use AI. Tackling one use case at a time also ensures humans stay in the loop for all critical functions. 

“This doesn’t happen overnight. Some organizations are paying very keen attention to upskilling their existing talent with AI,” said Suresh. “Human in the loop is going to be very critical. As much as we want to give the agents [data] to be more autonomous, we have to establish a very strict governance around the usage of data and how decisions are made.”

Reap the early adopter advantages of agentic AI

Agentic AI is a great equalizer for marketing teams. Enterprise organizations and startups can achieve speed and scale never before possible, so even small teams can compete with large, established companies.

First-party data is the true differentiator in this new era. By prioritizing a first-party data strategy, teams can kickstart a flywheel of innovation where every audience insight informs more personalized campaigns across every channel. An AI-ready toolset allows marketers to turn insights into new campaign ideas with confidence. 

Suresh and Murat share additional insights and lessons learned in our full discussion. Access the webinar replay here and start building your version of the agentic marketing organization today.