Agentic commerce in fashion: Shoppers want AI to save them money, not spend it

The first phase of agentic commerce is clearly not about handing over the wallet. It’s about outsourcing the hard work. Call it shopping agent AI: software that does the browsing, comparing, and price-tracking, while the shopper keeps the final say.

New consumer research commissioned by ACI Worldwide, at the intersection of fashion and AI, among 3,000 fashion and sportswear shoppers in the US and UK shows that shoppers are far more interested in AI that helps them save money, discover products, and compare options than AI that actually makes purchases for them. According to the study, 35% of shoppers see value in AI-powered price-drop alerts, 35% want AI to compare prices across retailers, and 27% would welcome help finding similar products. Meanwhile, 53% remain unwilling to let AI purchase on their behalf under any circumstances.

This creates an important opportunity for fashion retailers.

The question isn’t whether agentic commerce will arrive. AI agents are already driving traffic and helping consumers navigate increasingly complex shopping journeys. The real question is how retailers prepare for the phase that is happening right now. The answer starts with becoming discoverable, understandable, and accessible to AI shopping assistants while ensuring checkout can support the new forms of shopper intent those assistants generate.

The research reveals clear boundaries around how much control shoppers are willing to surrender. Just 7% of respondents would allow an AI assistant to purchase with some degree of autonomy, either within a predefined budget (5%) or for certain retailers only (2%).

What shoppers do want is practical assistance. The most appealing AI features are those that improve value and convenience without removing decision-making authority. Price-drop alerts and cross-retailer price comparisons top the list, followed by suggestions for similar products, personalized recommendations, and outfit recommendations.

In other words, consumers are adopting AI the same way they adopt most retail innovations: gradually. They start with low-risk, high-value use cases and expand from there as trust grows.

One of the clearest findings in the research emerges when two separate data points are analyzed together. First, 41% of shoppers say sales and promotional events trigger impulse fashion purchases. Among sportswear shoppers, that rises to 49%. Second, price-related AI features are the most desired agentic commerce capabilities, with both price-drop alerts and cross-retailer comparison tools attracting 35% of respondents. These findings suggest that AI is not introducing a new purchasing trigger. It is automating the trigger that already works.

Historically, consumers needed to discover a promotion at the right moment. They might receive an email, notice a discount while browsing, or happen to revisit a product page at the right time. Agentic commerce removes much of that timing dependency. An AI assistant can monitor products continuously, notify shoppers when prices fall, and surface the best offers automatically.

For retailers, this means promotions become increasingly visible and searchable. Competitive pricing, discount strategies, and inventory management may become more important as agents compare offers at scale.

It also introduces operational implications. When price-driven demand surges occur, retailers need the payments and checkout infrastructure to keep up. As the report notes, impulse-driven shopping patterns make demand less seasonal and less predictable, increasing the importance of systems that can absorb sudden spikes without creating friction or failure points.

The consumers most receptive to AI are frequently the same consumers retailers most depend on for growth.

The research shows younger shoppers display significantly higher interest in AI-powered personalization. Twenty-five percent of consumers aged 18-24 value personalized product suggestions, compared with just 11% of those aged 55-65. Younger shoppers also show stronger interest in outfit recommendations and other discovery-oriented AI features.

Sportswear shoppers are even more receptive. Compared with the survey average, they demonstrate higher interest in virtually every AI-powered shopping capability, including price-drop alerts, price comparison, personalized recommendations, product discovery, and AI-assisted returns support. Importantly, they are also less likely to reject AI-assisted shopping outright.

These audiences matter because they are already driving many of retail’s most important behavioral shifts. The report shows women and younger shoppers lead app adoption, digital wallet usage, hybrid shopping journeys, and other emerging behaviors. Sportswear consumers also score high on omnichannel engagement and app usage. In many cases, they are among the retailer’s highest-value customers.

That means retailers waiting for mass-market adoption before investing in agentic readiness may be overlooking the very shoppers most likely to adopt these experiences first.

The path to agentic commerce is often portrayed as a future technology challenge. In reality, much of the preparation for agentic commerce involves capabilities retailers already need today, even if the final green light on payment isn’t fully in place yet.

• Catalog legibility
  If AI assistants are increasingly helping shoppers find products, compare prices, and evaluate options, retailers must ensure product information is structured, comprehensive, and machine-readable. Product descriptions, availability, pricing, sizing information, and promotional details need to be easy for both humans and machines to interpret.
• Distinguishing legitimate agents from malicious bots
  Retailers already deal with a constant stream of bot traffic. As shopping agents become more common, the challenge becomes identifying which automated interactions represent genuine consumer intent and which represent fraud, scraping, or other unwanted activity.
• Checkout readiness
  Even if shoppers continue approving purchases themselves, AI shopping agents will increasingly influence how those transactions begin. Retailers need checkout experiences capable of accepting and completing agent-assisted transactions while maintaining appropriate authentication, authorization, and consumer control.

This preparation delivers value regardless of how quickly autonomous commerce develops. Better product data improves discoverability. Better fraud controls improve security. Better checkout performance improves conversion.

In other words, becoming agent-ready is less about predicting the future and more about strengthening the fundamentals.

The survey reveals that trust in agentic payments needs to develop. Very few respondents are comfortable with unlimited purchasing authority, but some are willing to grant conditional permissions. 5% of respondents would permit purchases within predefined spending limits. 2% would authorize purchases for selected retailers only. Those figures are revealing. Consumers want to retain oversight, understand what an agent is doing, and establish clear limits.

The future of agentic commerce may therefore depend less on AI capability and more on confidence. Consumers are already telling retailers what they are willing to trust today. The brands that build around those preferences will be best positioned when trust expands tomorrow.

Today’s shopping journey often involves countless tabs, comparison sites, saved wish lists, and repeated searches. Agentic commerce aims to simplify that complexity.

But the data suggests the transition will be gradual. Consumers are not rushing to hand purchase decisions to AI. They are asking AI to help them find better deals, compare options faster, and make more informed decisions. For fashion retailers, that is actually good news.

It means there is a clear and practical starting point. Retailers do not need to solve fully autonomous shopping overnight. They need to ensure their products can be discovered by AI assistants, their systems can identify legitimate agent activity, and their checkout experiences can support the evolving ways shoppers buy.

The winners in this next phase of commerce will not necessarily be those with the most advanced AI. They will be the retailers that make themselves easiest for AI and consumers to evaluate, compare, trust, and buy from.