How to Get the Whole Marketing Team to Embrace AI

Much of the talk around artificial intelligence in marketing has centered on content creation: how it helps produce copy, imagery, and creative faster and more efficiently. That's real, but it's only one part of the bigger picture. Today's marketing teams aren't just made up of writers and designers. More often than not, they include demand generation leads, growth marketers, analysts, and operationss folks all focused on pipeline, performance, and proving returns on investments.

In that context, the real promise of AI lies in its ability to act as a force multiplier across the full team. To realize that potential, AI can't be something in which just a few individuals dabble; it needs to be adopted across the board, embedded into daily workflows, and used to drive smarter, faster decisions.

The most immediate value AI brings to marketing teams is its ability to synthesize information, analyze data, and surface actionable insights quickly and at scale. These capabilities address a set of pain points with which we all wrestle: fragmented systems, slow feedback loops, and inconsistent visibility into what's working and what's not.

When used intentionally, AI can help us spot trends across campaigns, identify conversion gaps, and even test new growth ideas faster. In a world where most of your ideal buyers aren't in-market (hello, 95/5 rule), AI can help teams keep up with shifting signals, better understand customer pain points, and reposition faster than the competition.

For demand gen and growth marketers, AI helps maximize your budget by telling you where to place your bets. Think faster competitor research, sharper campaign messaging, quicker testing of use cases, and clearer performance signals.

The challenge today is that data lives everywhere—LinkedIn here, CRM reports there, website performance, customer signals tucked away in a sales deck. AI helps stitch those signals together and answer key questions. Which channels are driving real engagement? Which messaging is converting for which segments? Where should we double down, and what’s not worth the spend? That's the kind of clarity that helps marketers move from just generating marketing-qualified leads to actually influencing revenue.

Marketing Accountability Has Shifted

Ten years ago, marketers could report on MQLs and pat themselves on the back for driving awareness. Today, it's a different story. Leadership expects marketing to show its impact on pipeline and revenue that's already closed and that's forecasted to close. It's no longer about what you generated; it's about what you converted.

To meet that demand, teams need to know exactly which efforts are working and why. And conventional dashboards and static reports just don't cut it. AI changes the game by allowing marketers to ask open-ended questions using natural language and get answers instantly. No more waiting on analysts to build a deck. No more working from last quarter's insights.

Right now, most AI use in marketing is fragmented. Content folks use ChatGPT. Designers explore AI tools in their creative suites. Data teams run queries through Chat or Copilot. Everyone’s doing something, but often in isolation.

To truly benefit, marketing teams need a shared approach. That means doing the following:

• Identifying common problems where AI can help.
• Choosing tools that serve the whole team, not just individual roles.
• Sharing learnings, wins, and even failures.
• Documenting usage to build internal best practices.

If we treat AI as a team sport, not a personal hobby, we unlock scale. It's not about replacing anyone's creativity or judgment. It's about freeing up time so people can focus on what they do best.

Make It Work With What You Already Have

Most of us are already using Salesforce, HubSpot, Marketo, or other platforms that power how we work. You don't need to rip those out. Instead, look for opportunities where AI can enhance those tools, filling in gaps, enriching data, cleaning lists, or surfacing better insights.

And as AI helps generate clearer reports and dashboards, don't keep that value contained to marketing. Share those learnings with sales, ops, and the C-suite. Translate what's happening into terms everyone can understand.

Just don't skip over governance. Make sure security, compliance, and privacy are built into the process, especially if your organization is regulated or data-sensitive. Work with your internal teams up front to avoid surprises later.

The biggest blocker I hear is, "We don't know where to start." And that's fair. The key is to pick a small, defined task that’s slowing you down—something repetitive, manual, or time-consuming—and test an AI solution there. Document what works. Show value. Then scale it from there.

Create space for the team to learn. Hold brown bags. Bring in experts. Normalize experimentation. And just as important, normalize imperfection. It's OK if everything doesn't work right away.

Address any fear or resistance head-on. People want to know that AI isn't here to take away their jobs but to give them back time to do their best work.

The future of marketing isn't just about better tools. It's about building better systems where insights flow faster, teams move with confidence, and work gets done smarter.

The most effective marketing teams will embrace AI as a teamwide effort. Not siloed experiments. Not isolated wins. But a shared practice that brings the whole team forward.

Those are the teams that will move faster, execute smarter, and ultimately win in this next chapter of modern marketing.