Why Traditional Retail Metrics Break Down in Agentic Commerce

Retailers are no longer asking whether artificial intelligence belongs in the business. Nearly every organization is experimenting with AI in some form, whether through personalization engines, predictive inventory tools, customer service assistants, or emerging agentic experiences.  The challenge now is understanding how to measure its impact as AI increasingly shapes discovery, decision-making and customer engagement.

This challenge is already reshaping the customer journey itself. In Valtech's recent Retail at the Crossroads 2026 research, surveying hundreds of senior retail leaders and executives from across the globe, found that nearly all (96 percent) face barriers to seamless experiences, with the big reasons why including inconsistent customer ID matching (17 percent), poor data integration (16 percent) and legacy tech (9 percent).

These findings point to the larger issue of AI adoption accelerating faster than retailers’ ability to operationalize, connect systems, unify data, and measure impact across increasingly fragmented customer journeys.

AI Adoption is Not the Same as AI Value and Results

Retailers spent the last several years rapidly investing in AI capabilities, but adoption alone does not create transformation.

Organizations often mistake activity for progress. Teams are launching pilots, testing use cases, and implementing new tools, yet still lack confidence in what's actually driving measurable business outcomes.

Our research shows nearly three-quarters of retailers are unable to connect AI investments to clear performance metrics, while almost half (48 percent) remain stuck in experimentation without scaling meaningful impact, coined “pilot purgatory.”

This has created a growing execution gap across the industry. Retailers are doing more, spending more and deploying more technology than ever before, but still rely on measurement frameworks built for a much simpler customer journey.

Data is Becoming the Foundation

The challenge becomes even more complicated when the underlying information powering AI is fragmented.

AI systems can only be as effective as the data feeding them. Product information spread across disconnected systems or governed by inconsistent standards limits everything from personalization to discovery and conversion.

The effects are already visible in customer experience outcomes. Surveys show that less than half (46 percent) of retailers offer a truly unified experience across touchpoints, while a further 35 percent say they’re “mostly integrated” but still fragmented.

As AI increasingly shapes how consumers discover products and make purchasing decisions, rich, structured and connected data is no longer simply an operational requirement; it is a competitive advantage.

Yesterday’s Measurement Models

Part of the challenge is that retailers are trying to measure a changing customer journey using frameworks built for a different era.

Consumers are increasingly discovering products through AI-powered search, chatbots and recommendation engines before ever visiting a retailer’s website, creating new touchpoints that traditional measurement models were never designed to capture. Traditional attribution models were designed for relatively linear paths to purchase. For example: A customer sees an advertisement, visits a website, browses products and eventually converts.

These journeys are becoming far less predictable. As agentic experiences increasingly shape how consumers discover products, compare options and make decisions, the purchase path becomes harder to map.

Findings point to only 14 percent of retailers currently delivering advanced personalization consistently across channels and touchpoints, while 65 percent still rely primarily on basic personalization tactics that feel anything but personal to shoppers.

The Next Competitive Advantage is Proving Impact

AI itself is quickly becoming expected. Retailers are investing heavily, but the challenge is no longer simply adoption.

The next phase of retail transformation will not belong to the companies running the most AI pilots. The real differentiator will be the ability to turn experimentation into measurable business outcomes, connect fragmented customer journeys, and understand what is truly influencing decisions along the way.

Megan Carrigan is senior vice president of strategy and innovation at Valtech Americas, where she leads multidisciplinary teams helping global brands connect creativity, technology, and human insight to drive transformation.