Tech is awash with hype cycles, but experts agree that generative AI has firmly established its staying power.
“AI is really allowing us to free up our resources to do human things, to think creatively, to do things the bots can’t do today that we tend to get bogged down with,” Jenna Flateman Posner, Solo Brands’ chief digital officer, said at our “Attention! Trends and Predictions for 2024” summit held last week.
“We’ve just scratched the surface. There are so many more applications that we have yet to prove out and measure, and I’m really bullish that generative AI is absolutely here to stay,” Flateman Posner said.
Here are three growth areas in generative AI for marketing and ecommerce.
Etailers that mimic the personalized, customer-centric in-store experience stand to convert consumers who prefer shopping from brick-and-mortars.
“Right now, we put the onus on the consumer to filter down and engage with a wide array of products in order to find what they’re looking for,” Flateman Posner said. “[Conversational search] allows you to create real connection and context with the consumer very early in their buying cycle, to really filter down those results and drive conversion as effectively as possible.”
Investments in generative AI lead to better products. In fact, more than 40% of AI and machine learning (ML) decision-makers cite product and service improvements as their primary drivers for developing AI and ML applications, per an August 2023 report from S&P Global Marketing Intelligence commissioned by WEKA.
“I deal so much with our product engineering team and all of the deferred maintenance tasks that can get hidden in the road map, where you just can’t push the big innovation through fast enough,” said Lizzie Widhelm, senior vice president of B2B marketing and ad innovation at SiriusXM. If you can leverage AI to handle maintenance tasks at scale, you can accelerate innovation and build more of what your customers want from your brand, she said.
The future of generative AI in marketing is not just about the technology itself but also how it is developed, implemented, and regulated to be inclusive.
Generative AI has much left to define, including legal and ethical considerations, Thomas-Moore said. There’s a long way to go in ensuring generative AI models understand those sensitivities, and it starts with looking at the diversity of people who are coding. That focus will help businesses engage wider, more diverse audiences, he added.
This was originally featured in the eMarketer Daily newsletter. For more marketing insights, statistics, and trends, subscribe here.