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Home Business & Finance Entrepreneurship

What CMOs Need to Know About AI Adoption in Marketing Teams todayheadline

January 8, 2025
in Entrepreneurship
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Opinions expressed by Entrepreneur contributors are their own.

Generative AI has taken the marketing world by storm over the last few years — but unsurprisingly, attitudes toward AI adoption and the results themselves have often been mixed.

As Ad Age reports, Amazon wants marketers to consider AI as the foundation of digital marketing, emphasizing the ability of LLMs to better connect with customers through dynamic and better-targeted content. However, Modern Retail notes that many are still hesitant to give up control over their brand and its creative messaging, even with pressure from Amazon, Google and others to turn more of their marketing activities over to AI.

While the level of adoption of AI and the type of AI used varies between companies, there are key trends that CMOs, in particular, must pay attention to in order to ensure that AI adoption goes smoothly for their own marketing teams.

Related: How to Successfully Implement AI into Your Business — Overcoming Challenges and Building a Future-Ready Team

Disparities exist between CMOs and entry-level marketers

One of the major concerns that has existed across various industries is the disparity in enthusiasm regarding AI between C-suite executives and lower-level employees. Particularly in the wake of mass layoffs in the tech industry, widespread anxiety regarding AI has made many workers reluctant to utilize it or view it as an opportunity in their field.

This discrepancy also exists in marketing. According to a research report from Lightricks, while 55% of marketing executives say they are very confident in AI’s ability to improve marketing, only 33% of entry-level marketers feel the same. This lack of confidence among entry-level marketers could also be attributed to differing attitudes regarding desired outcomes with AI in general. The report found that while 27% of marketing executives “want a world where little human oversight is needed,” only 5% of entry-level marketers felt the same.

Notably, the Lightricks report found that executives were far more likely to have undergone AI training and to have utilized AI in meaningful ways in their current roles. When entry-level marketers are left behind in such initiatives, feelings of fear or uncertainty become more understandable.

Such disparities can stem from a variety of factors, but a lack of communication or a clear strategic vision for AI implementation will often be to blame. CMOs may be excited about testing AI and incorporating it into their work, but failure to consider the concerns and needs of the marketing team as a whole will lead to resistance and pushback. This is particularly true of teams who lack familiarity simply because they haven’t been empowered to experiment with AI for ad targeting, visual asset design, message personalization or creative ideation.

Related: Many Employees Fear Being Replaced by AI — Here’s How to Integrate It Into Your Business Without Scaring Them.

Addressing the divide is crucial

For CMOs, the most pressing matter regarding AI adoption in their marketing teams is education — namely, helping marketing teams that may be resistant to the idea of AI understand how it can help them in their work and how it will influence the company’s marketing strategy as a whole.

Examples of AI benefiting marketing teams are commonplace. A report from McKinsey cites several examples, such as Michaels Stores using Gen AI to personalize 95% of its email campaigns to lift its clickthrough rates by 25%, Mattel using AI to quadruple its output of product concept images and Stitch Fix using Gen AI to offer product recommendations and improve understanding of customer feedback.

Such case studies are useful, but reluctant marketing teams will likely require additional context to understand how AI will benefit them and not just the company’s bottom line. Your organization’s specific use cases for AI in marketing may vary, but addressing any disparities that currently exist is a crucial first step in achieving more unified results.

CMOs can achieve this through several means. Offering training on how to use AI tools that are relevant to your team’s work can go a long way in breaking down barriers and helping all involved discover practical use cases. Those who are more experienced in using a variety of marketing AI tools should consider how they can share their knowledge and experience, as this will dramatically grow the capabilities of the organization as a whole.

CMOs should also be willing to discuss the organization’s strategic vision for utilizing AI in marketing, with an emphasis on how it will enhance rather than replace human work. As part of this effort, CMOs should be open to hearing from others within the organization (including entry-level employees) regarding their concerns or ideas about how to use AI more effectively. This can help improve trust regarding an issue where trust and transparency are often lacking.

Related: Adapting to the Digital Workforce: 4 First Steps to Training Your Team on AI

Ensuring better AI adoption in marketing

There is no one-size-fits-all approach to how a brand could (or should) use AI in its marketing operations. What works for one brand and its audience may prove to be completely ineffective or even problematic for another.

However, CMOs shouldn’t just consider the potential reaction of their target audience. As the discrepancies between CMOs and entry-level marketers regarding AI reveal, there is much work to be done to ensure that AI is integrated into marketing practices in an ethical and effective manner.

By collaborating with those they lead and looking for the most effective solutions to implement AI, CMOs can help their teams navigate this transition successfully and better position their organization to gain a meaningful competitive advantage.

Tags: Adoptionartificial intelligenceBusiness CultureCMOCMOsInnovationLeadershipManagementMarketingScience & TechnologyteamsTechnologytodayheadline
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