ChatGPT and Perplexity roll out AI shopping tools that promise smarter product discovery, personalized picks, and quicker paths to purchase. In the last 24 hours, ChatGPT and Perplexity have introduced new AI-driven shopping experiences that aim to deliver more personalized product discovery and guidance. Both experiences are meant to help users find, compare, and purchase products through conversational queries informed by preferences and past behavior.

By harnessing AI and gen AI to create the next best customer experience, front-runners could generate value for customers and themselves through increased conversion, retention, and upselling. Imagine your company had an AI-powered engine that could detect when a customer needs help—before they even realize it. And was able to coordinate and sequence customer touchpoints while personalizing communications to get the right message to the customer in the right way.

The industry is turning to AI to better understand the technology itself, all with the hope of capturing consumer attention. Consumers are increasingly using AI chatbots for shopping recommendations. The retail industry is working to catch up on generative AI as the technology evolves at a rapid pace. While plenty of companies are using it to drive efficiency, it’s also presented a change to how consumers discover new products.

In case you were wondering what problem AI should solve next, Amazon has an answer: helping you decide what to buy next. Amazon introduced a new AI-powered “Help Me Decide” button that recommends products based on shopper browsing history and preferences. Amazon said the idea is to offer a clear product recommendation with explanations.

The goal is to help shoppers save time and offer confidence in their purchase decisions, Daniel Lloyd, Amazon’s VP of personalization, said in a statement. The tool taps into AWS tech like Bedrock, SageMaker, and OpenSearch to make those calls.

Agentic AI promises to radically remake the entire shopping experience. Here’s a glimpse into the near future—and what merchants, players, and platforms need to know in order to thrive. Agentic commerce —shopping powered by AI agents acting on our behalf— represents a seismic shift in the marketplace. It moves us toward a world in which AI anticipates consumer needs, navigates shopping options, negotiates deals, and executes transactions, all in alignment with human intent yet acting independently via multistep chains of actions enabled by reasoning models.

This exclusive Metrigy eBook, commissioned by Zoom, goes beyond the hype and reveals how leading organizations are using AI today, what challenges they’re still facing and which strategies are paying off.

Inside, you’ll uncover:

The top drivers fueling AI adoption in customer experience

The biggest roadblocks CX leaders hit when integrating AI

Which features and capabilities matter most when evaluating AI solutions

It almost goes without saying that we’ve moved beyond the age of telephone-only conversations with customers. These days, customers demand interactions over text, email, social media and yes, even phone calls. The proliferation of such omnichannel customer service together with the scale of interactions means that agents are doing more work than ever before.

Yet even as their workload has increased, how they get their work done often hasn’t changed. After-call summaries and call handoffs can still happen on Post-Its at many organizations. Agents might still be evaluated on a small sample of the hundreds of interactions they engage in every week. And call complexity or the absence of automated processes means agents might have to pause interactions while they complete tasks, increasing Average Handle TIme and raising costs.

Consumer search behavior is shifting, with users now entering longer, more complex questions into search bars in pursuit of more relevant results. For instance, instead of a simple “best kids snacks,” queries have evolved to “What are some nutritious snack options for a 7-year-old’s birthday party?” 

However, many digital platforms have yet to adapt to this new era of discovery, leaving shoppers frustrated as they find themselves sifting through extensive catalogs and manually applying filters. This results in quick abandonment and lost transactions, including an estimated annual global loss of $2 trillion.