CMOs are navigating a tough environment, balancing demands to achieve short-term improvements in marketing efficiency and effectiveness with long-term investments in digital transformations, tech stack upgrades, and AI adoption. Boards, CEOs, and CFOs are scrutinizing marketing’s overall contribution to performance and whether recent technology investments are paying off.

In the face of this pressure, many CMOs view GenAI as a tool to improve efficiencies and unlock growth. A majority of the respondents in our April 2024 survey of over 200 CMOs in 7 countries, conducted in partnership with the Association of National Advertisers (ANA), cited the adoption of AI or GenAI as one of their top five priorities over the next year. Around 80% said that GenAI is already improving automation, speed, and productivity. But the transformation is not progressing at the same speed for all, because it is exposing current shortcomings in the core operating models and data foundations that marketers will need to deploy GenAI at scale.

CMOs remain very optimistic about the promise of GenAI, as Exhibit 1 shows. In the year since our previous survey in April 2023, however, their expectations have shifted from wide-eyed to pragmatic. They have identified the operational areas where they can scale GenAI initiatives rapidly and which initiatives will take longer to scale. They have learned firsthand where they can automate certain tasks to achieve step-change improvements in efficiency—and where human intervention will remain essential.

As this rapid transition from experimentation to scale continues, the way that brands manage social media channels is likely to become the first area for real disruption in marketing. But to complete the journey, brands need to learn to manage lingering risks, such as how to avoid copyright infringement by properly implementing tools and ensuring that all content elements are sourced from preapproved libraries. Many of the operational aspects of social media will become automated and commoditized, but the increased volume of content might make it harder for a brand to stand out. That, in turn, will put more pressure on marketers to generate fresh creative ideas and increase the quality of the experiences that AI tools generate. In other words, efficiency will put more pressure on effectiveness.

In one example, a large direct-to-consumer pharmaceutical company made its content creation process 60% more efficient when it applied GenAI tools and made process improvements such as embedding creative resources on agile marketing teams and reducing the number of handoffs between teams. The largest efficiency gains came in creative brief writing and in the image-, copy-, and video-generation steps. Applying GenAI also accelerated quality control and compliance approvals. Automated dashboards flagged outliers and potential conflicts with brand guardrails, which themselves became better refined and clarified through this work. The new content ultimately doubled the ROI of the company’s social media advertising spend because the firm chose to reinvest the freed-up resources into creating more personalized content for its brand campaigns and better tailoring them to individual channels and customer cohorts, instead of cutting costs.

Personalization Will Require a Step Change

Successes in personalization fueled by GenAI are not yet as widespread. Personalization was the most common experimental use case in our 2023 survey, but CMOs have since learned that it is among the harder use cases to deploy quickly at scale. The operative word is “quickly.” GenAI tools can help create the necessary content variation for personalization, but it takes predictive AI to know what action to take next with each customer, and therefore what content is appropriate, in what sequence, and in which channel.

An organization builds that intelligence through constant testing, learning, and refinement by feeding machine-learning models with a nonstop flow of data. The process yields a richer, more granular understanding of what it takes to change the behavior of each customer. Marketers also need to rethink how to conduct testing, because their dominant operating approach—running campaigns and periodic promotions—doesn’t generate the data needed to inform a personalization engine. Instead, they need small agile teams running constant experiments to move fast and build the scale of learning.

In our recent research, we have established a new way to measure personalization maturity, which we call the Personalization Index. Personalization leaders—the 15% of companies that scored highest on the index—have often gone through a multiyear change journey. They achieve quick wins to fund investments in the first year, then make further AI and tech investments and implement operating model and governance changes that drive larger shifts in their organizational structures and incentives over the medium term.

The work is difficult and time-consuming, but our experiences with leading clients confirm that personalization at scale offers the greatest upside from the adoption of GenAI. Companies are increasingly competing on the volume of quality interactions with customers and the speed with which they learn from them and make them better. Personalization is the ultimate way for a company to unlock growth from AI, instead of only focusing on efficiency.

Bland Puts Brands at Risk

GenAI has had its greatest impact thus far on internal processes: better speed, higher productivity, and less manual labor. In terms of content quality, however, CMOs now have firsthand proof that GenAI content can be bland or unimaginative. Over 70% are concerned about GenAI’s impact on creativity and brand voice, two domains in which humans continue to outperform algorithms. In the supplementary interviews we conducted, CMOs said they are challenging their teams to maintain their focus on creativity and emotional connection as they move toward tools that do a better job of incorporating brand voice.

To achieve these goals, about half of our respondents said that they are hiring talent with GenAI-specific skills. In addition to having the right talent, they will also need to change their ways of working. Cross-functional, agile teams will allow them to move quickly and maintain the focus on creativity.

Mastering the Shift from Automation to Innovation

CMOs are optimistic about the impact of AI and GenAI on their topline growth and are investing accordingly. Over half of survey respondents are projecting at least 5% topline growth in their GenAI-related business cases, and three out of five will invest at least $10 million annually in AI and GenAI initiatives over the next three years.

To ignite this growth, however, CMOs will need to find a way to focus on innovation with GenAI and not concentrate solely on automation. Currently, they are investing primarily in low-hanging fruit (content creation, social media engagement, and ad copywriting). (See Exhibit 3.) But to get the most from GenAI, they must shift their priorities to strategic areas such as customer insight generation, personalization, segmentation, and predictive analytics.