How to Balance AI Fluency With Human Insight in Marketing Teams

AI can generate dozens of campaign ideas in seconds. But knowing which are worth pursuing—and investing in—takes more than machine speed. With AI use in marketing at U.S. companies more than doubling in just two years, the distinction between using the technology and using it well is becoming increasingly important.

That shift may also change who on a marketing team is best positioned to contribute. Marketers who lack AI fluency risk falling behind, while those who rely too heavily on the technology may never develop the customer insight, creative instincts and critical thinking needed to judge what it produces. The 2025 AMA Marketing Skills Report, based on a survey of more than 1,200 marketers, reflects this balance: Respondents ranked generative AI as the top future skill, yet the report emphasizes that human skills such as communication, innovation and adaptability remain essential. 

The consequences of falling behind on AI—or failing to focus on fundamental human skills—can extend beyond individual skill gaps and lead to ineffective campaigns, misguided investments and messaging that erodes customer trust. Below, members of the Senior Executive CMO Think Tank draw on their marketing expertise and leadership experience to share practical strategies for developing AI-fluent marketers who can think independently, exercise sound judgment and uphold the standards that protect their brands.

“The goal is not maximum AI adoption but marketers who use it deliberately, challenge its output and remain accountable for the consequences.”

– Oleksandr Osmichenko, CEO of IT Monks

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Decide When AI Should—and Shouldn’t—Be Involved

Oleksandr Osmichenko, CEO of IT Monks, advises marketing leaders to teach teams three AI skills: when to delegate, when to collaborate and when to refuse its involvement.

“Map workflows by risk: AI can support low-risk tasks such as summarizing research, while customer-facing content and strategic decisions require human review,” he suggests. “Ask marketers to explain what they accepted, rejected and verified and where their judgment changed the result.”

He also emphasizes the importance of preserving opportunities for independent thinking, including engaging in customer conversations, AI-free brainstorming and team critiques.

“The goal is not maximum AI adoption but marketers who use it deliberately, challenge its output and remain accountable for the consequences.”

Make Real Work the Training Ground

Rather than treating AI education as a separate activity, Vinny La Barbera, Founder and CEO of imFORZA, favors a hands-on approach.

“Marketing leaders should stop sending people to AI training and put it inside their team’s real work,” he says. “Have everyone bring the AI draft and their edited version to a team review, side by side.”

The exercise gives teams a chance to examine not only the finished product but also the thinking behind the revisions. For La Barbera, that distinction is essential to building genuine expertise.

“Judgment gets built by fixing bad output, not by watching a course, and it makes the real skill more visible,” he says. “The most valuable person isn’t the fastest prompter; it’s the one who can tell you why the draft was wrong.”

Make AI Fluency a Core Marketing Competency

Kurt Allen, Vice President of Enrollment, Marketing and Communications at Notre Dame de Namur University, believes marketing leaders should treat AI fluency as a core competency, not a technical specialty.

“Give teams opportunities to use AI on real work—research, personalization, analytics, content development and workflow automation—while teaching them to question outputs, validate insights and recognize bias,” he says. “The goal isn’t to create better prompt writers; it’s to develop better marketers who know when and how to use AI.” 

Allen adds that leaders should also establish clear ethical guardrails around data, transparency and brand integrity. And while he acknowledges that AI strategy and proficiency are essential focuses for modern CMOs, Allen says that the technology doesn’t diminish what only humans can bring to the table.

“As AI makes execution faster and more accessible, strategic judgment, creativity, empathy and critical thinking become even more valuable,” he says. “The strongest teams will combine AI’s speed and scale with the distinctly human ability to understand context, customers and consequences.”

Look Beyond the Numbers

Data analysis is one of AI’s primary strengths. But Jessica Hawthorne, CEO of Hawthorne Advertising, highlights the importance of human expertise in evaluating marketing performance.

“AI can significantly accelerate reporting, data analysis and the identification of marketing insights, but human expertise remains essential to interpreting those findings accurately,” she says.

Hawthorne emphasizes that marketers must apply strategic judgment to automated findings to ensure important nuances—such as customer lifetime value, brand considerations, market conditions and organizational objectives—aren’t overlooked. 

“Without that human perspective, AI-generated reporting can miss critical context, leading to conclusions that are incomplete or do not accurately reflect true marketing performance.”

“Nobody builds judgment in a training program; you build it writing the bad draft, getting it marked up, and sitting in the room when a good idea dies for a reason you never saw coming.”

– Kathleen Lucente, Founder and CEO of Red Fan Communications

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Protect the Experiences That Build Judgment

For Kathleen Lucente, Founder and CEO of Red Fan Communications, the importance of learning through experience was, fittingly, learned through experience.

“I learned a lesson at EDN early in my career as a journalist, watching an editor take my copy apart in front of me,” she recalls. “It stung. It also worked.”

As AI handles more of the work traditionally performed by developing professionals, Lucente warns that younger marketers may miss the formative experiences that prepare them for leadership.

“Nobody builds judgment in a training program; you build it writing the bad draft, getting it marked up, and sitting in the room when a good idea dies for a reason you never saw coming,” she says. “Those are reps, and AI is absorbing every one of them. You will not feel it this year. You will feel it in three when the person who should be running the account cannot tell you why the draft is wrong.”

Lucente shares her recommendation for how to “put the reps back”—both for building AI skills and distinctly human ones.

“Make people commit to a recommendation before they see the model’s version, then argue about the gap,” she advises. “Get young professionals in front of clients years earlier than we did. Speed is easy to buy now. Judgment still has to be earned in the room.”

Encourage Experimentation—With Clear Guardrails

Erin Lentz, Executive Director of Design at ArtVersion, advocates letting teams become familiar with AI by making it part of everyday workflows.

“Start by giving teams low-risk opportunities to use AI for research, ideation and analysis, then require them to verify claims, identify assumptions and explain the judgment behind their decisions,” she says.

Lentz stresses that leaders must provide a framework that protects both the organization and its customers.

“Establish clear standards for privacy, bias, intellectual property and disclosure, with human accountability for every final output,” she says. “Most importantly, reward curiosity without rewarding blind adoption.”

For Lentz, the ultimate goal is balance.

“The strongest marketers will be those who know when AI can accelerate the work—and when customer insight, creative touch and human judgment should overrule it.”

Teach Teams to Make Decisions, Not Just Use Tools

Hastimal Jangid, Co-Founder of Coozmoo Digital Solutions, argues that marketing leaders should build skills that will remain relevant even as platforms change.

“Stop treating AI fluency as a software-training exercise,” he says. “It is fundamentally a judgment skill. Tools will evolve every quarter, but knowing when to trust, challenge or override an AI’s output remains essential.”

Jangid recommends structuring training around actual marketing decisions rather than platforms. 

“Have teams generate AI-assisted options for real briefs, then explain why they would select, reject or revise each one before it reaches the market. That process builds discernment faster than any certification,” he says. “Ethical checkpoints are equally important. Teams should ask, ‘Does this reflect a deliberate strategic choice or merely the model’s default pattern?’”

Without that scrutiny, Jangid says, creativity and originality disappear; maybe not overnight, but quietly, campaign by campaign. With it, marketing teams are ready for a future where AI powers—but doesn’t overpower—campaigns. 

“The marketers who remain indispensable will not be those who use AI fastest. They will be the ones who can explain why human judgment mattered at every stage,” he concludes.

Hire and Promote for Curiosity

Jayashree Rajan, CMO of Nexla, sees AI as increasingly important not only to marketing professionals’ day-to-day performance but also to their career prospects.

“AI is not replacing the need for marketing expertise,” she says. “What it is doing is exposing junior marketers who cannot embrace AI and use it to move faster, whether for research, analysis, content ideation or simple tasks.”

That AI fluency, Rajan believes, is also essential for future leaders—with key added ingredients.

“Naturally, AI is also changing who is best positioned to lead. But tools alone will not build that readiness,” she says. “Marketers need genuine curiosity and an appetite for learning.”

Rajan advises marketing leaders to adopt strategies centered on the future—both of AI and their teams.

“What good marketing leaders should actually do is build structured AI fluency programs that define clear boundaries for data sharing and set AI best practices,” she says. “More importantly, they should change how they hire and promote, focusing on curiosity and the ability to work with AI while still giving latitude to humans to apply judgment and creativity.”

Measure Better Decisions, Not Level of AI Use

For Jeff Chancellor, CMO of Oversight, Inc., the measure of AI proficiency that matters isn’t how quickly employees learn to leverage LLMs.

“AI fluency is not prompt fluency,” he says. “Leaders should teach teams to separate the work that machines can accelerate from the work that humans must continue to own: context, judgment, originality, ethics and accountability.”

To develop both AI skills and marketing savvy, Chancellor recommends on-the-job learning with guardrails, productivity metrics and a clear North Star. 

“Give teams governed environments and real workflows where they can test, critique and improve AI output,” he says. “Measure whether AI improves decisions and frees people for higher-value work, not how many tools they use. The goal is not AI-first marketing. It is better marketers, equipped with AI.”

“Wise marketers understand that the most probable answer is not always the most human or the most strategically sound answer.”

– Paul L. Gunn Jr., Founder of Signal & Anomaly

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Center Human Experience and Empathy

Paul L. Gunn Jr., Founder of Signal & Anomaly, says that building AI fluency—without confusing what data outputs suggest with lived judgment—can be meaningful for marketing leaders. He acknowledges AI’s usefulness while also clarifying its limitations. 

“AI can model scenarios, accelerate analysis and reveal patterns, but markets ultimately operate in the theater of real life, where trust, culture, emotion and consequence can challenge even well-modeled outcomes,” Gunn says.

He stresses that teams should understand where AI strengthens their thinking and where human experience must interrogate AI.

“The advantage may belong to marketers who can combine machine intelligence with cognitive empathy, creativity and ethical judgment,” Gunn says. “Wise marketers understand that the most probable answer is not always the most human or the most strategically sound answer.”

Turning AI Fluency Into a Competitive Advantage

• Match AI involvement to the risks of each task. Allow greater autonomy for routine work while requiring human oversight for customer-facing content and strategic decisions.
• Use side-by-side reviews to strengthen editing skills. Compare AI-generated drafts with employees’ revisions and ask team members to explain what they changed and why.
• Make practical AI fluency a teamwide expectation. Give marketers hands-on experience with AI in research, personalization, analytics, content development and workflow automation.
• Evaluate AI-generated insights against business realities. Consider customer lifetime value, market conditions and organizational goals before acting on automated reports or recommendations.
• Preserve the experiences that prepare junior marketers for leadership. Require employees to develop their own recommendations, participate in constructive critiques and gain direct client experience.
• Establish clear ethical standards for AI use. Create policies covering data privacy, bias, intellectual property and disclosure, with employees accountable for final outputs.
• Teach marketers to defend their creative decisions. Use real campaign briefs to help teams evaluate AI-generated ideas for originality, strategic fit and brand alignment.
• Prioritize curiosity and adaptability in hiring and promotion. Look for professionals who embrace continuous learning and demonstrate the ability to apply new capabilities thoughtfully.
• Measure AI’s contribution to marketing performance. Focus on improved decision-making and time freed for higher-value work rather than tool adoption rates or usage volume.
• Balance data-driven predictions with human understanding. Consider customer emotions, cultural influences and real-world experiences when evaluating AI-generated recommendations.

Building Better Marketers, Not Just Better AI Users 

As AI becomes embedded in everyday marketing work, technical fluency will be essential—but it won’t be enough. Marketing leaders must create an environment where employees can experiment with new tools while developing the judgment, creativity and customer understanding that technology can’t replace. That means making room for hands-on experience, constructive feedback and independent thinking, even when automation offers a faster path.

The strongest marketing teams won’t necessarily be those using AI most extensively. They’ll be the ones that know when to trust it, when to challenge it and when to rely on human expertise. As the technology evolves, that combination of technical capability and sound judgment will help marketers protect brand trust, make smarter decisions and deliver lasting business value.