3 growth areas for generative AI, according to digital experts

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.

1. Conversational search

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.”

• Some 45% of US adults prefer shopping in-store over digitally, according to February 2023 Morning Consult data.
• In May, Instacart added a conversational search function to its storefront, allowing customers to ask open-ended questions such as, “What do I need to meal prep five healthy lunches?”
• Rather than getting a “firehose of search results,” AI is enabling what feels like real interactions, said our analyst Paul Verna.

2. Low- or no-code automation

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.

• Half of executives worldwide say coding is one of the generative AI applications that is most relevant to their business, according to April 2023 Capgemini Research Institute data.
• In partnership with Microsoft, Domino’s developed AI-driven predictive tools that help store managers streamline pizza preparation and quality control.
• “We’re hoping that, through this partnership, we can understand how to bring to life more enriched and personalized [ordering] experiences for both our customers and team members,” said Christopher Thomas-Moore, Domino’s senior vice president and chief digital officer.

3. Inclusivity

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.

• AI platforms have been widely criticized for their lack of representation.
• At a Senate Judiciary hearing, OpenAI CEO Sam Altman emphasized the importance of inclusivity, pointing to the increased language capabilities of GPT-4 compared with its earlier models. For less widely spoken languages, such as Icelandic, he said, the company is working on “custom partnerships” to make sure they are represented.
• “We’re excited to work with people who have particular data sets, and to work to collect a representative set of values from around the world to draw these wide bounds of what the system can do,” Altman said.

Watch the full session.

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