Brands are collecting more ecommerce data than ever — and acting on less of it. The gap between insight and execution is where market share is quietly being lost.
There was a time when brands could simply list a product online and expect it to sell. Today, success requires a coordinated strategy across retail media, the digital shelf, pricing, and inventory. That strategy should be informed by data, but with thousands of SKUs across numerous marketplaces, brands not only have to interpret endless insights but also act on them. At scale, consistent execution becomes nearly impossible to manage manually.
In a recent survey, nearly half of business leaders said their data isn’t actionable, and more than 40% cited a lack of data accessibility or decision-making time as a core operational challenge.
Teams don’t need more visibility — they need the ability to keep up with and act on the data they already have. It’s impossible for e-commerce teams to adjust every bid, fix every product description, and catch every stock issue themselves. To close that gap, brands need to rethink how the work gets done.
Why Today’s Execution Model Can’t Keep Up
Teams aren’t lacking data; they have too much of it. Dashboards have become more sophisticated, but seeing more doesn’t necessarily help teams do more.
Every optimization still requires someone to pull the report, identify the issue, decide what to do, and then execute. That delay between spotting a problem and fixing it is where performance starts to degrade. By the time a team corrects a content issue, the marketplace algorithms have already shifted.
What retailers are experiencing is a gap between insight and execution. The old approach was to do more: more reports, more meetings, more manual tweaks, more tools. But today, teams can spend most of their time looking for what’s broken and patching the same issues over and over.
The way the work used to get done won’t keep up with how fast modern e-commerce moves. With AI-powered discovery through Amazon’s Rufus and Walmart’s Sparky shaping how shoppers see and buy, the pace will only continue to accelerate.
Many brands have tried to address this by turning to agencies for support. In a recent survey, 67% of commerce teams said they rely on agencies, and about half said they spend 15% to 30% of their budget on agency fees alone. Yet 55% said those costs are too high for the results, and 40% said response times can’t keep up with the speed of algorithms.
While agencies can provide expertise, they don’t operate 24/7 — and the marketplaces retailers sell on never pause. Retailers can’t match that speed by adding more headcount or additional agency hours.
Brands today need an algorithm to keep pace with the algorithm. They need a new execution model that can handle the volume and velocity of decisions in modern ecommerce.
What an Agentic Retail Strategy Looks Like
The shift happening now is toward agentic AI execution, where human teams are no longer tasked with doing the heavy lifting of weeding through data, reports, and manual workflows. Instead, they drive strategy and make final decisions while their agentic AI counterparts analyze large volumes of data and identify growth opportunities.
This approach lets brands continuously extend execution across their entire catalog around the clock, rather than focusing only on top-performing SKUs. In practice, this looks like specialized agents that operate across the digital shelf:
- A content agent identifies and resolves product page issues across thousands of SKUs simultaneously, reducing the time required to update product detail pages from 35 minutes to 35 seconds.
- A media agent optimizes campaigns using dozens of signals at a scale no human team could match.
- A sales agent monitors pricing and promo performance to flag gaps or opportunities.
To keep pace with the speed of modern ecommerce, retailers don’t have to add more tools on top of the same manual process; instead, they need to fundamentally change how the work is done. With agents handling the execution layer, the brand manager’s role changes. They spend less time pulling reports and making fixes and more time setting guardrails and deciding priorities.
The Real Shift Starts in Execution
Teams already know the old model isn’t working. The speed required to compete today has outgrown what humans can manage manually. There’s too much data to interpret and too many actions required to keep up with how quickly the digital shelf changes.
Agent‑driven execution removes that bottleneck. According to a recent report, 82% of commerce leaders expect AI investment to increase in the next 12 to 18 months, and 71% are already familiar with or actively using AI agents.
With the industry moving in this direction, retailers can’t afford to be left behind. The next era of e-commerce will belong to the companies that can execute at the same speed as the market.
