Last month, Marcel Digital partnered with B2B Marketing to host a roundtable in Chicago focused on a question that's top of mind for nearly every organization today:
How do you move from AI experimentation to enterprise value?
The conversation brought together marketing and business leaders from a variety of industries, all at different stages of their AI journey. Some organizations are just beginning to establish governance. Others are building AI into their daily operations. Many are somewhere in between.
While everyone came to the table with different experiences, the discussion revealed a surprising amount of common ground.
Here are a few of the biggest takeaways.
AI Isn't the Challenge. Strategy Is.
One of the strongest themes throughout the discussion was that most organizations don't have an AI problem.
They have a strategy problem.
Across the room, we heard similar stories. Teams are being encouraged to adopt AI, leadership wants to move quickly, and new tools are constantly entering the market. But many organizations haven't taken a step back to answer a more important question:
What are we actually trying to accomplish?
Without a clear strategy, AI initiatives become disconnected experiments rather than scalable business capabilities.
"The possibilities with AI are absolutely endless. That's exciting, but can also be intimidating. If the possibilities are endless, it can be difficult to decide where to start "
Kyle Brigham, Chief Strategy Officer at Marcel Digital
The organizations making the most progress aren't necessarily adopting more AI tools. They're aligning those tools with clearly defined business objectives.
Better Data Leads to Better AI
Another recurring theme was data.
AI is only as effective as the information it's given.
Disconnected systems, inconsistent reporting, and siloed data continue to prevent organizations from realizing the full value of AI. In many cases, instead of solving those problems, AI exposes them.
Before investing in another AI platform, many organizations may benefit more from improving how data is collected, connected, and shared across the business.
The Goal Isn't Just Efficiency
It's easy to measure productivity gains.
How much faster can AI create content?
How many hours can it save?
Those metrics matter.
But during the roundtable, many leaders challenged the idea that efficiency alone should define AI success.
The bigger opportunity is using AI to improve customer experiences, support sales teams, accelerate decision-making, and uncover new opportunities for growth.
Efficiency creates capacity.
What organizations do with that capacity is what ultimately drives business value.
Start With the Business Problem
One of the most practical insights from the discussion was also one of the simplest.
Instead of asking:
"How should we use AI?"
Organizations should first ask:
"What problem are we trying to solve?"
Whether it's improving lead quality, streamlining sales enablement, personalizing customer experiences, or connecting fragmented data, starting with the business challenge creates a much clearer path to identifying the right AI solution.
Human Expertise Is Still the Differentiator
Perhaps the biggest misconception surrounding AI is that it replaces expertise.
The discussion suggested the opposite.
The organizations seeing meaningful results are using AI to augment experienced marketers, analysts, developers, and strategists, not replace them.
AI can automate repetitive work, summarize information, and accelerate research.
People still provide the judgment, creativity, context, and strategic thinking that drive meaningful business outcomes.
Where Organizations Go From Here
Hosting this conversation reinforced something we see every day working with our clients: organizations aren't looking for more AI tools. They're looking for direction.
The companies creating lasting value with AI aren't necessarily the ones adopting every new platform or experimenting with the latest technology. They're the ones building a strong foundation that connects their data, aligns AI initiatives with business goals, and gives their teams the strategy and governance needed to scale AI effectively.
Every organization is at a different stage of its AI journey. Some are establishing governance. Others are scaling successful use cases. Wherever you are, the next step shouldn't be adopting another tool. It should be building a strategy that aligns AI with your business goals.
At Marcel Digital, we help organizations do exactly that. Get in touch to learn how we can help you build the data, strategy, and marketing foundation needed to create lasting business value with AI.
