The essentials
- Embrace AI now. Inaction with generative AI in marketing can lead to missed opportunities and falling behind competitors.
- Beyond efficiency. Generative AI does more than reduce 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 guard against risks such as data bias and privacy issues.
Over the past 18 months, discussions about generative AI have dominated technology and media debates, reshaping the conversation around marketing and innovation. Amid all the buzz, one fact remains clear: the implications of this technology are still being developed, and its true potential is far from being fully understood.
What emerges is a complex narrative, full of excitement and caution, as marketers, like CMOs, must grapple with AI’s promises of transformational change while navigating its ethical and legal challenges. Four key truths about generative AI in marketing begin to define and guide this journey.
Truth #1: Inaction on Generative AI in Marketing Is the Biggest Risk
The progress and commitment that global marketing teams across industries have shown in piloting generative AI in marketing tools is impressive, according to a recent study Capgemini Survey on Generative AINearly 60% of global marketing organizations are now integrating generative AI technologies into their strategies. These initiatives include custom content creationchatbot agents and predictive analytics. While the majority of these efforts are still in the testing phase, nearly 40% of organizations have moved from experimentation to implementation across multiple initiatives.
While this progress is exciting, it means that over 40% of global companies are still in the early stages of discussing the potential of generative AI capabilities and have yet to launch internal pilots. Implementing generative AI technologies is not without risk, but these companies are not looking at the big picture: they risk quickly falling behind competitors in critical areas such as customer experience innovationmarketing performance and key talent acquisition.
Companies investing in generative AI recognize that the potential consequences of inaction are far greater than the obstacles associated with implementation.
Truth #2: Generative AI delivers more value than just operational efficiency
Most CMOs my organization has consulted on generative AI in marketing are looking for ways to streamline creative output to maximize the return on their performance marketing. We often hear questions like, “Can generative AI reduce costs or boost creativity?” This is not surprising, as marketing has long been viewed as a cost center. As a result, becoming more efficient is a traditional KPI that CMOs often focus on.
However, this narrow view only offers short-term benefits and neglects the true power of machine learningIts ability to handle complex tasks that humans find difficult may open up unprecedented opportunities.
When we work with CMOs on generative AI strategy and consulting, we start by looking at current technologies and capabilities to determine where they can have the most impact. More often than not, creative teams and agencies already have access to powerful tools like Adobe Creative Cloud or Canva that have generative AI tools built in, and media teams are leveraging advanced AI algorithms that deliver targeted ads to consumers.
It’s common for marketing strategists to be challenged to develop innovative marketing strategies using disparate campaign data or outdated consumer research that they can access. By giving these upstream teams access to real-time consumer behavior data combined with predictive analytics, all powered by generative AI, their current work will be improved and they will identify new growth opportunities. Taking control of your first- and third-party data insights is the most important investment marketers can make to drive transformative change.
Related article: Generative AI in Technology: For Increased Productivity
Truth #3: Generative AI solutions fail in the traditional marketing model
Despite this optimism, there is a caveat. Generative AI won’t deliver its full potential if companies try to fit 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 report on the generative AI maturity model, 45% of CMOs believe their current organizational structure is a significant barrier to achieving the goal. full potential of generative AI.
However, not all brands are struggling with the adoption of generative AI. Retail brands like Reebok and Adore Me are changing their operating model and adopting cross-functional thinking for their products. generative AI drivers.
Reebok’s marketing, product and digital teams are working together to enable users to design personalized digital sneakers through AI, driving greater customer engagement.
Adore Me uses AI for custom lingerie design, allowing customers to create unique patterns on products, which helps to feed ideas for future products back to their product and marketing teams. These initiatives have prompted each brand to break down internal silos and create a system of collaboration and continuous learning across multiple departments.
For most traditional marketing companies, this kind of progress 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 meaningful impact.
Truth #4: Ethical governance of generative AI in marketing is essential
While the benefits of generative AI are clear, the ethical and legal implications cannot be ignored. Seven out of ten organizations have not implemented Ethical guidelines for the use of AI in marketing, according to the IBM Global Study on Generative AIThis is a significant omission, particularly given the potential risks related to data privacy, bias and intellectual property infringement.
For marketers, this means it’s not just about deploying the latest AI tools, but doing so responsibly. Establishing clear ethical guidelines and strong governance frameworks as part of your operating model is critical to ensuring generative AI in marketing is used in a way that aligns with your brand values and protects consumer trust. This starts with taking a cross-functional approach, involving legal, IT, and marketing teams to develop policies that address everything from data use 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-enhancing tool can unintentionally create a sense of threat within internal teams. Without clear governance, this perception can lead to an increased risk of compromising consumer trust.
However, when leaders position generative AI as an enabler and part of a broader transformation design, internal adoption rates increase and the benefits far outweigh the risks.
Simply put, CMOs who can see the power of generative AI as a catalyst for innovation, adapt their structures, and prioritize ethical considerations will lead the The Future of Marketing and promote sustainable growth.
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