4 Truths CMOs Must Learn About Generative AI in Marketing
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 thing remains clear: the implications of this technology are still unfolding, and it's true potential is far from being fully understood.
What’s emerging is a complex narrative—a mix of enthusiasm and caution, as marketing leaders grapple with AI’s promise of transformational change while navigating its ethical and legal challenges. Four key truths are beginning to define and guide this journey.
Truth #1: Inaction with GenAI Is the Greatest Risk
The progress and commitment global marketing teams across industry sectors have shown in piloting GenAI tools is impressive. According to a recent Capgemini GenAI survey, almost 60% of global marketing organizations are now integrating GenAI 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% have moved from experimentation to implementation across multiple initiatives.
While this is exciting progress, that means over 40% of global companies are still just discussing the potential of GenAI capabilities, and have not started any internal pilots of their own. Implementing GenAI 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 product & customer experience innovation, marketing performance or key talent acquisition. Companies investing in GenAI are recognizing that the potential consequences of inaction are far more significant than the hurdles associated with implementation. As one CMO put it, “Standing still isn’t an option when the market is moving at lightning speed.”
Truth #2: GenAI Offers More Value Than Operational Efficiency
Most of the CMO’s we’ve consulted with regarding GenAI applications are looking for a means to streamline creative output to make their performance marketing work harder. We often hear questions like, “Can GenAI 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 CMO’s feel the need to focus on. However, this narrow view offers only short-term benefits and overlooks the true power of machine learning. Its ability to handle complex functions that humans struggle with can unlock unprecedented opportunities.
When we work with CMO’s on GenAI strategy and consulting, we start by reviewing the current technologies and capabilities to determine where GenAI can have the greatest impact. Most of the time, the creative teams & agencies already have access to high-powered tools like Adobe Creative Cloud or Canva that have GenAI tools built in, and media teams are leveraging advanced AI algorithms that serve targeted ads to consumers. However, it’s typical that Marketing Strategists are being asked to develop new innovative go-to-marketing strategies using whatever disjointed campaign data or outdated consumer research they can get their hands on. Giving these upstream teams access to real-time consumer behavior data combined with predictive analytics, all powered by GenAI, will make the current work better and identify new opportunities for growth. Getting control of your 1st and 3rd party data insights is the number one most important investment marketing leaders can make in driving transformative change.
Truth #3: GenAI Solutions Fails In the Traditional Marketing Model
Despite the optimism, there's a caveat. GenAI 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 GenAI promises. According to an EY GenAI maturity model report, 45% of CMOs feel that their current organizational structure is a significant barrier to realizing the full potential of GenAI.
However, not all brands are struggling with GenAI adoption. Retail brands like Reebok and Adore Me, are changing their operating model and embracing cross-functional thinking for their GenAI 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 & marketing teams. These initiatives prompted each brand to break down internal silos and build a system of collaboration and continuous learning development across multiple departments.
For most traditional marketing organizations, this will involve restructuring teams, redefining roles, and even rethinking how success is measured. Without these changes, even the most advanced GenAI tools will struggle to make a significant impact.
Truth #4: GenAI Governance Is Still Overlooked
While the benefits of GenAI are clear, the ethical and legal implications cannot be ignored. Seven in ten organizations have not established ethical guidelines for the use of AI in marketing, according to the IBM global GenAI 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 marketing operating model is essential to ensure that GenAI 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.
The Future Is Here. Are You Ready For A Revolution?
Eighteen months into the GenAI revolution, the success of implementations varies widely. Framing GenAI 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. However, when leaders position it 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 GenAI as an innovation enabler, adapt their structures, and prioritize ethical considerations will lead the future of marketing and drive lasting growth.
Source: CMSWire
