Vying For Generative AI: 5 Rules For Using The Technology For Marketing

Generative artificial intelligence (AI) has been getting a lot of hype. But is it really of any use to marketers? 

It sure is, judging by Ready for Launch: How Gen AI Is Already Transforming Marketing, a study by Bain & Company.   

For one thing, AI is well suited to its blend of creative and data-driven work. And 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, other image creation platforms like Midjourney and Stable Diffusion, and emerging audio and video creation technologies,” Bain Partners Jeff Katzin and Laura Beaudin and Associate Partner Max Waldron write. 

Indeed, firms are already using AI for these purposes, the study found:

  • Generative AI embedded in products/software — 49% 
  • Customer engagement and service applications — 47% 
  • Code completion, generation, copiloting — 46%
  • Knowledge assistants (for sales support and internal operations) — 42% 
  • Automation of IT administration (help desk, etc.) — 42% 
  • Marketing content generation and localization—39%
  • Product design and simulations — 35% 



But the buzz around AI comes with risks. Marketers are well placed to understand the many ways a company’s brand could suffer if the new technology’s debut is mishandled,” the authors write, adding: “Concerns include the safety of customer data and the threat to jobs. Copyright is a gray area too.”

You may think of Bain mostly as an investment firm, but it has a certain background in marketing: Bain Fellow Fred Reichhheld devised the net promoter score (NPS) in the 1990s, and it remains a key metric for many firms today.

The authors prescribe five golden rules of generative AI in marketing:

  1. Start and end with the customer—It may be tempting to use AI primarily to improve efficiency, but CMOs must remember that it has to improve the lives of customers and employees.
  2. Creative applications are only the start. The winners in this space will take a holistic approach that helps them “personalize marketing, improve behind-the-scenes processes, turbocharge measurement, enable near-real-time testing, and strengthen decision making by making sense of unstructured data.”
  3. Quick wins and complex projects must run in parallel—Rather than waiting for a solution that solves everything, companies must take “small steps today to build their expertise and gain quick, confidence-building wins.”
  4. Keep the highest-priority use cases in-house—Vendors like Google may be moving to build generative AI, 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 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 all this must be done without stifling innovation.

Bain & Company surveyed nearly 600 companies across 11 industries. 

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