Conversational commerce is reshaping how people shop online, blending real-time chats with AI to drive faster buying decisions.
Remember the buzz around voice assistants? When Google and Amazon launched theirs, voice shopping was supposed to be the future, but it quickly faded.
Many wrote it off as a failed trend. But something changed: generative AI entered the picture. Between 2021 and 2023, voice commerce transactions jumped more than fourfold. Consumers, especially Gen Z, are now engaging monthly with AI-powered voice shopping.
Conversational commerce is making a strong comeback. Thanks to smarter, more responsive AI chatbots and assistants, shoppers are no longer browsing—they’re buying instantly, with just a few words.
ChatGPT, the new shopping engine
OpenAI’s ChatGPT has quietly entered the shopping arena, and it’s already changing how products are discovered, as we have previously reported in this shopping with GPT article.
Unlike traditional search engines, ChatGPT doesn’t rank products based on ads or keyword stuffing. Instead, it relies on a user-intent-driven algorithm that factors in individual preferences, past interactions, and AI reasoning.
Here’s how the product selection process works, as described by Kevin King in his LinkedIn newsletter:
User-Centric Search
ChatGPT evaluates the query for clues about intent, like budget, dislikes, or style, and selects products it believes fit those needs.
Structured Third-Party Data
It pulls product information such as price, description, and reviews from external sources, not directly from Amazon or brand websites.
AI-Based Filtering
The model decides what attributes matter most (e.g., affordability, ease of use) and filters results accordingly.
Internal Safety Review
Only listings that pass OpenAI’s safety checks are eligible to be shown in the interface.
Paid placements do not influence results. ChatGPT doesn’t run ads or accept product sponsorships, so rankings are fully AI-driven. That means sellers can’t buy visibility, they have to earn it through relevance.
Displayed results come in a visual carousel inside the chat, including:
Image and Price – pulled from the first-listed seller.
Simplified Description and Link – makes it easier for users to scan and click.
AI Labels – tags like “Budget-friendly” or “Most popular” may appear but aren’t independently verified.
Review Summaries – some listings show AI-generated pros and cons using third-party review data.
The selection of merchants also follows a different path:
External Data Sources – merchants shown are based on pre-set third-party rankings, not OpenAI’s own.
No Direct Submissions- sellers cannot upload listings or tweak rankings manually.
This matters because ChatGPT is shifting from a Q&A tool to a discovery engine. For sellers, adapting to this new channel means:
Optimizing product data across all major marketplaces.
Ensuring visibility on third-party platforms where OpenAI might pull data.
Focusing on user-intent positioning, like budget options, trending items, or high-rated products.
As voice and chat-based shopping experience accelerate, understanding how AI engines like ChatGPT curate products will be critical to staying competitive.
Conversational Commerce enters the checkout lane
Search Engine Land"People are making high purchase intent queries in AI, although the ability to purchase with AI is still new."
Agentic AI is quietly restructuring the way consumers shop online, transforming digital conversations into instant transactions. As reported by PYMNTS, the traditional eCommerce journey of toggling between tabs is rapidly giving way to single-command purchases facilitated by large language models (LLMs) like Perplexity.
How conversational AI enhances the purchase funnel
Unlike older chatbots, these conversational AI systems don’t just suggest products, they complete purchases on the consumer’s behalf. They connect directly with merchant APIs to check inventory, apply promotions, and process payments in seconds, all within the same conversational thread.
This technology reduces friction by eliminating multiple points of potential dropout in the funnel, such as account creation or manual coupon code entry. Every unnecessary click between discovery and purchase increases the likelihood of cart abandonment, something agentic AI is designed to prevent.
The architecture powering this shift includes real-time integration hubs that pre-cache frequently requested product data and stream order confirmations back to the AI nearly instantly. According to PYMNTS, Firmly’s system completes these actions with latency as low as 50 milliseconds, preserving the seamless experience users expect.
This new buying journey also changes how merchants think about customer acquisition and attribution. If shoppers now complete the entire funnel, from product discovery to checkout, within the same AI interface, traditional advertising models like pay-per-click campaigns may give way to deeper integrations with product catalogs and order systems.
Key elements of the agentic AI approach include:
Real-time product, inventory, and pricing data sourced via API, not scraping.
Ability to place orders from any conversation-starting context—email, voice assistants, maps, or social media.
Full compliance and audit trails maintained through direct backend integration.
Support for merchant loyalty programs, even without storefront visits.
Firmly reports it has integrated with APIs from 11 million merchants, covering most of the U.S. eCommerce gross merchandise value. That breadth allows agents to respond with precise, up-to-date options for nearly any user query.
Merchants, however, still wrestle with questions about brand visibility and customer data ownership. Firmly assures that the merchant remains the merchant of record and retains access to order information and brand engagement features.
Conversational commerce also taps into behavioral shifts that surfaced during the pandemic. Just as one-click checkout and curbside pickup became expected standards, instant AI-facilitated purchasing may soon become the baseline.
Net Solutions"Today’s customers expect real-time, personalized guidance that simplifies choices and builds trust."
With only 2-4% of organic product searches currently converting to sales, proponents argue that agentic AI can significantly improve that figure. It does so by answering complex product questions in context and enabling purchases before hesitation sets in.
Real-world examples already range from quick replenishment orders to assisted buying of higher-consideration items. A voice agent can now recommend espresso pods, select a mid-century lamp under $150, or even coordinate a vacation package. All while preserving customer preferences and merchant policies.
The evolution is ongoing, but the direction is clear: as conversational AI becomes more capable, retailers who engage early will be positioned to meet customers where and when they’re ready to buy.
Preparing for the AI-assisted conversational online shopping
Reported on CFOtech Asia, the rise of conversational commerce is reshaping how brands engage consumers and produce creative content. eCommerce stakeholders must adapt their strategies beyond technology to prioritize authentic, conversation-driven brand experiences.
Merchants should recognize that AI assistants are accelerating purchase journeys by up to 30%, signaling a need to rethink traditional marketing funnels. Embedding commerce directly within conversational flows reduces friction and opens new paths for instant purchases.
To succeed, brands must shift creative focus from keyword-heavy optimization to designing conversational experiences that reflect brand personality and emotional resonance. This approach enables brands to move from rigid platform demands toward flexible, context-aware interactions that feel natural to consumers.
Ecommerce teams should build creative frameworks that serve as the blueprint for AI-driven conversations, establishing brand values and storytelling as the core of customer engagement. By doing so, they empower AI systems to deliver consistent, scalable, and personalized dialogue across millions of touchpoints.
Invest in creative operations that balance strategic vision with AI-enabled efficiency.
Partner with technology providers like Glu.ai that streamline digital asset management and automate routine tasks such as bulk content resizing and tagging.
Develop internal capabilities to quickly iterate conversational content, enabling agile adaptation to emerging AI commerce channels.
Service providers like an Amazon agency must evolve to guide sellers through this transformation by integrating creative storytelling with technical implementation. They should focus on how brand identity translates into conversational commerce, helping clients maintain control over customer experiences while embracing automation.
Stakeholders are encouraged to evaluate their current workflows and invest in platforms that go beyond productivity tools to become creative foundations for the future. Early adoption of AI-driven creative operations will accelerate readiness and improve competitive positioning as conversational commerce becomes the new standard.
The era of conversational commerce is advancing rapidly. Those who cultivate a fluent conversational brand voice today will ensure resilience and relevance tomorrow, avoiding the pitfalls of reactionary adaptation. The conversation shaping brand success is already underway, and e-commerce stakeholders must prepare to lead it.
