In the past two years, companies have consistently and safely adopted generative artificial intelligence to transform their marketing strategies. According to a Bain survey of over 180 major North American companies, 27% of respondents stated that generative AI exceeded their expectations in the sector.
In retail, for example, technology has enabled more precise customer segmentation, agile content creation and testing, and highly personalized recommendations. AI-driven campaigns already show a return on investment between 10% and 25% higher.
Despite the initial success, expanding these initiatives is not simple. The corporate digital ecosystem is complex, and the demand for customization requires new processes. Furthermore, CMOs are under pressure to innovate with fewer resources, making it essential to accelerate the large-scale implementation of generative AI.
The research shows that 25% of organizations are still in the initial phase of implementing AI in marketing, with proof of concepts and few changes in the business model created by the technology. Most (65%) are part of a second wave, creating value through product viability and expanding IT and data teams. The remaining 10% already include autonomous tasks, redesigning processes, adding operational value and profit through the expansion of cases and innovation.
The main benefits cited by companies with the adoption of AI are agility, with up to a 50% reduction in campaign launch time; efficiency, as content creation time has decreased by 30% to 50%; and return on investment, with up to a 40% increase in click-through rates in hyper-personalized campaigns.
Defining priorities to leverage the impact of generative AI in marketing heavily depends on each company's business objectives. However, Bain identified four areas that stand out in this purpose: streamlining workflows; creating and customizing content; customer intelligence and insights; and measuring and optimizing campaigns.
Furthermore, to accelerate maturity in the use of technology, five actions are essential:
- Set ambitious and measurable goals, establishing clear objectives for operational efficiency, personalization, and financial impact;
- Prioritize large gains over multiple tests- organizations that concentrate efforts on a few high-impact use cases scale faster.
- Develop user-focused solutionsintegrated into the daily routines of the teams, involving their own professionals in the development of the tools;
- Continuously train the employees,carrying out practical training and real challenges essential to expanding the adoption of the technology;
- Expand the partner ecosystem- the supplier landscape in this area is still evolving, but companies should quickly test specialized solutions and keep up with innovations from their partners.
Generative AI is no longer a novelty and has become a competitive necessity in marketing. More advanced companies are already rethinking their partner strategies, large-scale personalization, and even the future of the industry with AI assistants. For those still stuck on point tests, it's time to accelerate adoption, scale initiatives, and capture the real benefits of this technological revolution.
