Imagine a world in which smart assistants are the common front end of digital interactions, transforming the experience of engaging with a brand’s app or website. A world in which the current mix of marketing channels has been shaken up—by a surge in text-based communication sparked by AI’s ability to personalize at scale, or by a boom in audio, video, and image-based marketing triggered by an acceleration of production speed at lower costs. Picture a corresponding disruption in the creative landscape as new sources of imagination and flair emerge and old ones lose their historic edge. Or one in which influencers become even more critical, with access to simplified or targeted versions of powerful digital tools that used to be out of their reach.
For marketers, all of these developments are in sight because of advances in generative artificial intelligence. Marketing is helping to lead the adoption of generative AI tools that create and personalize new content, such as OpenAI’s ChatGPT and DALL-E (which was used to produce the rocket image at the top of this page), other image creation platforms like Midjourney and Stable Diffusion, and emerging audio and video creation technologies. For instance, when we surveyed nearly 600 companies across 11 industries, speeding up the development of marketing materials was one of the top seven use cases for generative AI, with 39% of respondents saying they were using or evaluating the technology for this purpose (see Figure 1).
Marketing has a stake in at least two of the generative AI use cases gaining most traction with companies
Across consumer-facing industries, marketing has become a particular hot spot because of generative AI’s ability to engage customers, personalize content, and reduce both cost and complexity. Meanwhile, chief marketing officers with wider responsibilities are also looking to deploy it in customer service to personalize customer experience, boost sales and retention, and support frontline employees. And for companies that operate in the marketing and advertising industry specifically, adoption and evaluation of the top generative AI use cases is notably rapid, second only to IT system integrators.
For many CMOs, however, the buzz and expectation created by generative AI’s marketing potential come with new risks. Marketers are well placed to understand the many ways a company’s brand could suffer if the new technology’s debut is mishandled. Concerns include the safety of customer data and the threat to jobs. Copyright is a gray area too. That’s not just because the technology can reuse existing material in a way that breaches the intellectual property rights of human creators. It’s also unclear how much marketers will be able to assert copyright over content generated via the latest AI tools. Other potential hazards in AI-powered marketing include inaccurate content and unintended bias.
All this might lead some CMOs to advocate a wait-and-see approach, but that would create an even bigger threat to their company. One risk is that rivals deploy the technology first, leading to an advantage in innovation in customers’ eyes and an ability to set the “rules” of deployment in a given industry. A second is that early movers become hubs for top data and engineering talent required to compete.
Despite the concerns, AI is set to transform how marketers work. Pioneers will soon start to benefit from enhanced brand engagement, accelerated growth, time savings, a talent acquisition advantage, and lower costs, while slower-moving competitors will miss out. Coca-Cola offers a prime example of pacesetting—within a month of announcing that it was working with with OpenAI, it had launched its “Create Real Magic” campaign, which encouraged consumers to create Coke-related artwork using generative AI, conjuring up new touchpoints for the brand.
It’s a tricky tightrope for CMOs to walk. But while so much about generative AI is still in flux, some truths are already emerging.
Five golden rules of generative AI in marketing
Marketing leaders can draw on five golden rules as they plan how to embrace the technology over the coming months.
1. Start and end with the customer. Some executives may be tempted to use the technology primarily to improve efficiency, particularly given the current economic climate. CMOs need to ensure that deployment always comes back to “How can this improve the lives of our customers and employees?” Remember that this is a generational moment to redefine how marketers and brands engage with customers.
2. Creative applications are only the start. Early adopters are already using the latest AI tools to dazzling effect, generating new creative imagery at the click of a button. The winners in AI-powered marketing won’t stop there, though. They’ll take a holistic approach that also exploits AI’s ability to personalize marketing, improve behind-the-scenes processes, turbocharge measurement, enable near-real-time testing, and strengthen decision making by making sense of unstructured data (see Figure 2). Pragmatic moves include using unstructured data to inform audience targeting or updating the marketing brief with live campaign data. Another benefit of taking a holistic AI approach: improved collaboration with other departments.
Marketing use cases are at the forefront of generative AI deployment, from ideation through to measurement
3. Quick wins and complex projects must run in parallel. Some marketing teams are making early progress by deploying generative AI in manageable pilots, such as in employee-facing contexts, or in situations where employees can review AI-produced content before it reaches the customer. Rather than waiting for a solution to their thorniest deployment challenges, companies must take these small steps today to build their expertise and gain quick, confidence-building wins. But to realize the full long-term potential of AI, they also need to start working in parallel on complex projects, particularly those that connect to customer data lakes—things like personalized direct marketing, proactive engagement to retain customers, and sentiment prediction. We’d also encourage CMOs to carve out some capacity for the boldest innovations that transform experiences and value propositions, such as Spotify’s AI-powered DJ and Duolingo’s conversational role-play feature for language learning.
4. Keep the highest-priority use cases in-house. Software vendors such as Google are moving quickly to build generative AI into their products. That can streamline some forms of humdrum work without CMOs having to worry about building their own solutions. But a different approach is going to be needed in more specialized areas that offer genuine competitive advantage and differentiation in areas such as customer acquisition and engagement. These will require more bespoke capabilities that will likely have to remain in-house.
5. The CMO is perfectly placed to be an AI change agent. CMOs will need to exercise their brand guardian responsibilities carefully, managing risks and setting up guardrails (in partnership with the legal team) in areas such as intellectual property and data protection, while creating systems to respond effectively if AI–customer interactions go awry. But they must also ensure that this brand guardianship doesn’t end up stifling innovation. Marketing can be one of the earliest showcases for generative AI’s ability to reinvent work. Conversely, generative AI’s rollout can be a showcase for marketing teams eager to demonstrate their ability to contribute to adjacent functions such as product management and customer experience.
A CMO superpower in the making
Marketing’s prominence in the first wave of generative AI brings the right kind of pressure. A wide range of stakeholders, from boards to investors to employees, are looking to the CMO to be an inspirational early adopter. That’s an opportunity to underline the strategic importance and breadth of the marketing function.
Longer term, generative AI tools can bring new power to CMOs to better balance and integrate innovation, creativity, and data-driven decisions.