AI Chatbots for eCommerce Retailers: Worth it in 2025?

We’ve all experienced some frustrations with robot agents who don’t seem equipped to address our problems. Even worse, sometimes it’s not even possible to get ahold of a human when the AI agent fails. AI chatbots have come a long way in just the past year. They’ve gone from being frowned upon and under-utilized due to their inability to provide support in the way that eCommerce retailers needed to becoming the next big thing that everyone wants to get involved in.

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We’ve all experienced some frustrations with robot agents who don’t seem equipped to address our problems. Even worse, sometimes it’s not even possible to get ahold of a human when the AI agent fails. AI chatbots have come a long way in just the past year. They’ve gone from being frowned upon and under-utilized due to their inability to provide support in the way that eCommerce retailers needed to becoming the next big eCommerce integration that everyone wants to get involved in.

When we started our research to uncover the truth about AI chatbots and what they’re really capable of nowadays, it was difficult to find solid information about the progression of this technology. What’s changed in the past year, and what can we expect from this technology going forward? Is an AI chatbot really worth it for your eCommerce store? 

Predictive and Generative Chatbots

The first chatbots that started popping up on eCommerce storefronts a few years ago were quite limited in what they could do. Merchants were looking for ways to reduce the burden on their support teams who were wasting time on low-level, simple support issues. Chatbots started out as a tool to simply plug in answers to customer questions that already existed somewhere on the website, so bots didn’t have to work very hard to support most customer issues. 

Predictive AI models are used to analyze pre existing data in order to recognize patterns that could influence future strategies. They can be used across industries to provide valuable insights and improve sales forecasting, marketing campaigns, operational efficiency and more. 

Generative AI models revolutionized the industry, however, as we finally had widespread access to models that didn’t just pull historical data, but could actually create content. Generative AI models like Chat GPT are capable of creating many different kinds of content including marketing materials, code, and even images and video based on existing creative work from across the internet. 

Though these models revolutionized the industry, they came with many limitations and opportunities for improvement. Previous versions of AI chatbot technology could only function properly under a set of strict rules. This meant that bots couldn’t act autonomously and required significant human guidance. But what if it was possible for chatbots to understand a customer's goals and interpret the context of their issues in order to make independent decisions on their behalf? 

Agentic AI Chatbots

AI models have evolved with the help of both predictive and generative model technology to create AI “agents” that are capable of decision-making based on their own conclusions, without the need for human oversight. Agentic or conversational AI is an exciting new innovation because it’s the closest the technology has to come to mimicking real-life interactions, where the bots have to adapt in real-time to assist more complex challenges that previous AI models would have never been equipped to tackle without human intervention. 

However, there are concerns about whether or not AI models are sophisticated enough at this stage to act independently. The short answer is no, but it’s a little bit more complicated than that. Agentic AI models are for the most part a continuation of the same technology that generative AI follows to create content and solve problems. Agentic technology tends to simply be a more advanced large language model (LLM), so rather than a certain phrase triggering code, it triggers a workflow instead, which may result in an agent that appears to be autonomous but is really just a generative model with a couple of extra steps. Truly autonomous chatbots tend not to respond very well to failure, and are often prone to hallucinations. Not to mention, they are much more difficult to train compared to the way that humans and animals learn. The reality is that the architecture of large language models itself is limited, so anything we create using these models will always have the same core issues, and remain notoriously hard to control.

Decision-making machines are exciting, but it’s important to recognize the limitations before jumping in. Though AI models have become ubiquitous in the eCommerce industry, it’s important to question the capabilities of this technology so that you don’t fall for misleading marketing that makes optimistic claims about what Agentic AI can actually do. If you’re looking to implement this technology, it does tend to work best for a more narrow scope of issues, technology is always evolving, however. Depending on your intended use, they can be a great option for your eCommerce store, but can be tricky to implement as well. There are many services that help retailers build AI agents, the technology may even be available from your eCommerce platform provider. Our eCommerce platform marketAgility is built with flexibility and scalability in mind. Whether you're looking to implement complex eCommerce integrations, or just need some things taken off your plate, contact us today and we can help you build an eCommerce site that has everything you need and nothing you don’t. 

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