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AI RETAIL DATA STUDY
How eCommerce Leaders Can Break Through The Data Actionability Gap with AI Agents & Human Expertise
New research reveals why commerce teams are overwhelmed, and what's next for AI adoption
Commerce teams are drowning in dashboards but starving for action. Despite massive investments in tools, agencies, and headcount, the traditional operating model can't keep pace with algorithms that change hourly.
This Qualtrics data study commissioned by CommerceIQ surveyed 240 ecommerce leaders at $300M+ brands to uncover where teams are struggling, why the agency model is hitting its limits, and what it will take for commerce leaders to embrace AI agents.
Download the full report
Download the full report
Key takeaways
Data overload is the #1 barrier, not strategy or culture:
- Commerce teams have more dashboards than ever, yet 56% cite data trust and quality issues as their top challenge. 46% say data isn't actionable, 42% lack time to make decisions, and 40% say there's simply too much data to process.
The agency model is struggling to scale:
- 76% of commerce teams rely on agencies, with 49% allocating 15-30% of budget to agency fees alone. But 55% say costs are too high relative to results, and 40% cite slow response times that can't match algorithmic speed.
80% are ready to shift budget from agencies to AI:
- Commerce leaders aren't waiting. 82% expect AI investment to increase in the next 12-18 months, and 71% are already familiar with or actively using AI agents. The appetite is there, with conditions.
Trust, transparency, and human oversight are non-negotiable:
- 82% say unified business context is critical. 53% require security and compliance. 49% require integration with existing tools. 43% require human-in-the-loop oversight. Black-box AI won't earn adoption.
Top AI investment priorities for 2026:
- Retail media optimization (26%), PDP & content optimization (19%), and predictive demand (17%) lead the way: the same areas where speed matters most and agencies struggle to scale.
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