// . //  Insights //  Amplifying The Impact Of Modern Marketing With Generative AI

Generative artificial intelligence (AI) is disrupting marketing organizations around the globe. The technology already has shown how it can accelerate “personalization at scale,” enabling marketers to quickly and easily create new content and optimize existing content targeting specific customers. It’s also improving marketing efficiency, leading to tangible benefits and a better marketing return on investment (MROI). Across industries and geographies, chief marketing officers (CMOs) and other marketing executives are scrambling to take advantage: In a recent eMarketer study, 43% said they were planning to extensively use generative AI in the next two to three years. 

Exhibit: CMOs and executives who plan to use generative AI for marketing in two to three years
Average, % of respondents
Source: eMarketer study of CMOs & Executives Worldwide, December 2023, n=1,112

For any marketing leader — whether at a large organization trying to modernize its operations or a private equity-owned portfolio company looking to “do more with less,” generative AI can offer significant value when structured properly around the right use cases. In this article, we cover three primary areas where these leaders can better leverage generative AI to unleash personalization at scale and drive more modern marketing in their businesses.

Three ways to effectively leverage generative AI for modern marketing


While one-to-one marketing has been long been discussed, generative AI has a proven ability to help marketers create new content tailored to specific audiences at an unprecedented pace. Among other applications, marketers are using the technology to generate social media posts, email marketing content, and creative images. Beauty brand L'Oréal, for instance, has launched an app that provides haircare and makeup recommendations tailored to individual customers. Walmart is testing a generative AI-powered mobile shopping assistant. Instacart is leveraging ChatGPT to help with personalized meal planning.

MarTech platforms can serve up the most relevant ad creative based on customer preferences, past purchases, and shopping history and do a lot to enhance the customer journey and overall customer experience. And personalization has real benefits: our 2023 analysis of US banks, in collaboration with Morgan Stanley, found that improved product personalization can improve customer lifetime Value (CLV) and lead to a 3-5% increase in revenue.

Not surprisingly, there has been a lot of concern over whether generative AI will lead to the elimination of marketing jobs. But in a recent discussion on generative AI and its impacts on marketers, Pfizer Global CMO Drew Panayiotou asserted that the role of humans is not going away any time soon. Again, generative AI can significantly increase the quantity and variety of marketing content “stimuli”— and marketers still have a very important role in reviewing and optimizing it. The technology also can take on low-value or time-consuming tasks. Our bank study, for example, found that it could be used to create 60% of new product documentation, resulting in faster time to market for new products. Further to that point, without the burden of work like content tagging and synthesizing research, marketers are freed up to focus more of their time on designing strategic experiences for customers.  


Generative AI enhances the precision of customer targeting by leveraging real-time customer data such as geolocation, browsing behavior, and sentiment from social listening, product reviews and other sources. With a massive breadth of data at their disposal, organizations also can better identify who their high-priority customers should be and how best to reach them. The technology can then generate hyper-personalized content that captures attention and increases click-through and conversion rates. Now thousands of different customers can each have their own unique experience with a company’s marketing content, including ad creative, offers, taglines, and other key elements. In situations where customer data is unavailable, generative AI can support "lookalike modeling" by creating synthetic data points for target audiences that share similar demographic, behavioral, or psychographic characteristics with the base audience.

Of course, with the power of enhanced targeting and personalization comes increased responsibility both in terms of maintaining brand integrity and customer data privacy. In the wake of regulations such as the California Consumer Privacy Act (CCPA), the European Union’s General Data Protection Regulation (GDPR), and others, it’s vital for marketers to be good stewards of customer data. In particular, it is crucial that they ensure compliance with privacy rules and ethical considerations when using generative AI for lookalike modeling, implementing proper data anonymization and protection measures to safeguard individual customer information.


Generative AI possesses the capability to enhance agile marketing efforts by optimizing campaigns and other activities more rapidly. For example, it can generate multiple variations of marketing content and conduct real-time testing on target audiences to refine paid campaigns on the fly. It can also assist with search engine management (SEM) by deploying cost-effective keywords that yield the highest returns. The technology offers another, related boost to efficiency as well: real-time performance tracking. Its measurement capabilities allow marketers to make necessary adjustments — or even develop entirely new and different campaigns — and unlock higher MROI through faster feedback loops. 

There are a few “watch outs,” though. Marketers should exercise caution regarding potential negative impacts if content or campaigns are excessively optimized. Generative AI optimizes based on the metrics it is trained upon, which could result in false positives or create discomfort if it generates personalized content using data that customers were not aware they were sharing.

As generative AI surges, marketers must adapt or get left behind

The popularity of generative AI is exploding. According to eMarketer research, generative AI use in the US jumped from 7.8 million people in 2022 to 100.1 million people — or nearly a third of the country’s entire population — in 2024. Its adoption by marketing executives has similarly increased, making it even more important for them to leverage it properly and be aware of data and security risks, false positive campaign results, and other concerns.

Now more than ever, marketing leaders must take steps to prioritize and organize around the most crucial generative AI use cases to unlock personalization at scale. Failing to embrace generative AI carries substantial business risks, including challenges in attracting and retaining top talent and losing customers to more visionary competitors with more compelling content. By harnessing the power of this technology, marketing organizations can position themselves for success in the future and stay ahead in the rapidly evolving landscape of modern marketing.