Editorial
The Gist
- Adopt AI now. Inaction with generative AI in marketing can lead to missed opportunities and falling behind competitors.
- Beyond efficiency. Generative AI does more than cut costs — it encourages creativity and drives innovation through real-time data and predictive analytics.
- Prioritize governance. Ethical and legal frameworks for generative AI are essential to maintain consumer trust and safeguard against risks like data bias and privacy concerns.
Over the past 18 months, generative AI discussions have dominated both tech and media, reshaping the conversation around marketing and innovation. Amid all the buzz, one fact remains clear: The implications of this technology are still unfolding, and its true potential is far from being fully understood.
What’s emerging is a complex narrative full of both enthusiasm and caution, as marketing leaders like CMOs grapple with AI’s promise of transformational change while navigating its ethical and legal challenges. Four key truths about generative AI in marketing are beginning to define and guide this journey.
Truth #1: Inaction With Generative AI in Marketing Is the Greatest Risk
The progress and commitment that global marketing teams across industry sectors have shown in piloting generative AI in marketing tools is impressive. According to a recent Capgemini generative AI survey, almost 60% of global marketing organizations are now integrating generative AI technologies into their strategies. These initiatives include personalized content creation, chatbot agents and predictive analytics. While the majority of these efforts are still in the testing phase, almost 40% of organizations have moved from experimentation to implementation across multiple initiatives.
While this is exciting progress, that means that over 40% of global companies are still just discussing the potential of generative AI capabilities, and they have not started any internal pilots of their own. Implementing generative AI technologies is not without risk, but these companies are not grasping the bigger picture: They risk quickly falling behind the competition in critical areas such as customer experience innovation, marketing performance and key talent acquisition.
Companies investing in generative AI are recognizing that the potential consequences of inaction are far more significant than the hurdles associated with implementation.
Truth #2: Generative AI Offers More Value Than Just Operational Efficiency
Most of the CMOs my organization has consulted with regarding generative AI in marketing are looking for the means to streamline creative output to make their performance marketing work harder. We often hear questions like, “Can generative AI cut costs or boost creativity?” This isn’t surprising as marketing has long been viewed as a cost center, so becoming more efficient is a traditional KPI that CMOs often focus on.
However, this narrow view offers only short-term benefits and overlooks the true power of machine learning. Its ability to handle complex tasks that humans find challenging can unlock unprecedented opportunities.
When we work with CMOs on generative AI strategy and consulting, we start by reviewing the current technologies and capabilities to determine where it can have the greatest impact. Most of the time, the creative teams and agencies already have access to high-powered tools like Adobe Creative Cloud or Canva that have generative AI tools built in, and media teams are leveraging advanced AI algorithms that serve targeted ads to consumers.
It’s common for marketing strategists to be asked to develop innovative marketing strategies using whatever disjointed campaign data or outdated consumer research they can access. Giving these upstream teams access to real-time consumer behavior data combined with predictive analytics, all powered by generative AI, will make their current work better and identify new opportunities for growth. Getting control of your first and third party data insights is the number one most important investment that marketing leaders can make in driving transformative change.
Related Article: Generative AI in Technology: Unleashing Higher Productivity
Truth #3: Generative AI Solutions Fails in the Traditional Marketing Model
Despite the optimism, there's a caveat. Generative AI won’t deliver its full potential if organizations try to plug it into outdated operating models. Traditional marketing structures, with their siloed departments and rigid processes, will limit the innovation that generative AI promises. According to an EY generative AI maturity model report, 45% of CMOs feel that their current organizational structure is a significant barrier to realizing the full potential of generative AI.
However, not all brands are struggling with generative AI adoption. Retail brands like Reebok and Adore Me are changing their operating model and embracing cross-functional thinking for their generative AI pilots.
Reebok’s marketing, product and digital teams are working together to allow users to design custom digital sneakers via AI, fostering greater customer engagement.
Adore Me uses AI for personalized lingerie design, enabling customers to create unique patterns on products which drives future product ideation ideas back to their product and marketing teams. These initiatives prompted each brand to break down internal silos and build a system of collaboration and continuous learning across multiple departments.
For most traditional marketing organizations, progress like this will involve restructuring teams, redefining roles and even rethinking how success is measured. Without these changes, even the most advanced generative AI tools will struggle to make a significant impact.
Truth #4: Ethical Governance of Generative AI in Marketing Is Critical
While the benefits of generative AI are clear, the ethical and legal implications cannot be ignored. Seven in 10 organizations have not established ethical guidelines for the use of AI in marketing, according to the IBM global generative AI study. This is a significant oversight, especially given the potential risks around data privacy, bias and intellectual property infringement.
For marketers, this means it's not just about deploying the latest AI tools; it’s also about doing so responsibly. Establishing clear ethical guidelines and robust governance frameworks as part of your operating model is essential to ensure that generative AI in marketing is used in a way that aligns with your brand values and protects consumer trust. Getting started requires a cross-functional approach, involving legal, IT and marketing teams to develop policies that address everything from data usage to content creation.
Related Article: Generative AI: Exploring Ethics, Copyright and Regulation
Embrace Generative AI Today
Eighteen months into the generative AI revolution, the success of implementations varies widely. Framing generative AI as a productivity enhancer can inadvertently create a sense of threat among internal teams. Without clear governance, this perception can lead to a heightened risk of compromising consumer trust.
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However, when leaders position generative AI as an enabler and part of a larger transformation design, the internal adoption rate increases and benefits far outweigh the risks.
Simply put, CMOs who can see the full power of generative AI as an innovation enabler, adapt their structures and prioritize ethical considerations will lead the future of marketing and drive lasting growth.
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