Key Takeaways
Kohl's new assistant handles product comparisons, image-based search, promotion questions, and order tracking on web and mobile.
The tool is built on Google Cloud's Gemini Enterprise for Customer Experience, following an earlier Mother's Day Gift Finder launched in April 2026.
Kohl's posted a 1.7% net sales decline and a 1.1% drop in comparable sales in its most recent quarter, though its net loss narrowed.
Macy's, Michaels, and Lowe's have each rolled out comparable AI shopping assistants, making conversational search a competitive baseline rather than a differentiator.
The launch tests whether experience investment can move sales for a retailer where price and promotion strategy alone have not.
An Experience Fix for a Sales Problem
Kohl's launched an AI-powered shopping assistant for its website and mobile app, built on Google Cloud's Gemini Enterprise for Customer Experience, giving shoppers a conversational tool that aggregates deals, offers personalized product recommendations, and compares multiple items side by side. It can also search using a photo a customer uploads, answer questions about active promotions, track online orders, and hand off to a human customer service representative when needed, including support for buy-online-pickup-in-store transactions. The scope is broader than a typical launch-day chatbot, covering discovery, comparison, promotions, and post-purchase service inside a single conversational thread rather than routing shoppers between separate tools for each task.
The company described its goal in characteristically modest terms: using technology in practical ways that make shopping simpler, more personal, and more helpful. The assistant builds on a narrower Mother's Day Gift Finder tool Kohl's launched in April 2026, suggesting a deliberate rollout strategy of proving a seasonal, limited-scope use case before expanding to a full-catalog assistant rather than attempting a big-bang launch. That sequencing, testing on a bounded holiday use case before committing engineering resources to a permanent, year-round assistant, is a pattern worth studying for any retail technology team trying to justify a phased AI budget to a board that wants proof before it approves the next tranche of spending.
The Numbers Behind the Urgency
The context makes this more than a routine feature launch. In its most recent quarter, Kohl's reported a 1.7% decline in net sales year over year and a 1.1% drop in comparable sales, though the net loss narrowed by $1 million to $14 million. A retailer in that position does not have the luxury of treating an AI assistant as an innovation showcase, it needs the tool to move a measurable number, whether that is conversion rate, average order value, or return visit frequency, within a few quarters.
That is a materially different bar than the one large, growing retailers apply to similar launches. When a retailer with strong topline growth adds a shopping assistant, the investment reads as incremental optimization. When a retailer fighting sales declines does the same thing, the assistant needs to function as part of a turnaround thesis, and Kohl's leadership will be under pressure to show attribution data faster than a company with more room to experiment.
Conversational Search Is No Longer a Differentiator
Kohl's is not alone, and that is the more important story. Macy's, Michaels, and Lowe's have each built their own AI shopping assistants over the past year, and Michaels has separately reported that its Google-powered version doubles the conversion rate of traditional search. What was a bold bet eighteen months ago is now closer to table stakes for any mid-size retailer competing for attention against Amazon and specialty e-commerce players with more mature AI tooling.
That shift changes the strategic question retail technology leaders should be asking. It is no longer whether to deploy a conversational shopping assistant, most competitors already have or will within a year. It is whether a given implementation delivers a genuine experience advantage, faster answers, better product matching, tighter integration with loyalty and promotions, or whether it is simply matching a checklist item that customers now expect by default and will not reward with additional spend.
Why the Vendor Choice Matters Here
Kohl's decision to build on Google Cloud's Gemini Enterprise rather than a proprietary model reflects a broader pattern among mid-size retailers that lack the data science headcount of an Amazon or Walmart: renting the model layer and focusing internal engineering effort on integration with existing commerce, loyalty, and fulfillment systems. That is a defensible strategy when speed to market matters more than owning the underlying model, but it also means Kohl's differentiation has to come from data and integration depth, not from the AI itself, since competitors can license comparable models from the same handful of cloud providers.
The image-based search capability is the most technically interesting piece, since letting a shopper upload a photo and receive comparable product matches requires real integration between the vision model and Kohl's product catalog and inventory data, not just a chat wrapper around a search bar. Retailers evaluating similar builds should treat that catalog-integration work, ensuring product data is clean, tagged, and current enough for a vision model to match against reliably, as the real project risk, not the conversational interface itself.
The Test Ahead
Kohl's has given itself a relatively low-risk way to test whether AI-driven experience investment can move the needle where price competition and promotional strategy have not. The assistant is additive to existing channels rather than replacing them, and its cost structure, licensed from Google Cloud rather than built from scratch, limits the downside if adoption disappoints. That makes it a reasonable bet even under financial pressure, and it gives Kohl's leadership a concrete initiative to point to when explaining the turnaround plan to investors who have watched comparable sales decline for several consecutive quarters.
The real test will come in Kohl's next few earnings reports, where analysts and investors will be watching for any measurable link between assistant usage and the comparable sales trend the company is trying to reverse. If Kohl's can show that connection, even a modest one, it becomes a template for other declining mid-size retailers weighing whether AI investment is a defensible use of scarce capital or a distraction from more fundamental merchandising and pricing problems. If it cannot, the assistant risks joining a long list of retail technology launches that generated press coverage without moving the underlying financial metrics that actually determine the company's trajectory.
