Skip to main content
AI Best Practices for Commerce
About
McFadyen Digital

Authoritative AI Best Practices for Commerce

Built by McFadyen Digital ↗(opens in new tab)

Explore

Value ChainsUse CasesAI OverviewImplementationTechnology

Resources

AI ToolsNewsGlossaryAboutContact Us

McFadyen

McFadyen Digital ↗(opens in new tab)The Book ↗(opens in new tab)
|||Sitemap||

© 2026 McFadyen Digital. All rights reserved.

We use cookies to keep the site working and, with your consent, to understand how visitors use it (via Google Analytics, a third-party service). You can accept all, reject non-essential cookies, or choose per category. See our .

  1. News
  2. › AI adoption outpaces ability to measure ROI impact
  3. › Jun 23, 2026
AI adoption outpaces ability to measure ROI impactTuesday, June 23, 2026
  • Retail / DTC › Department Stores
AnalyticsLLMMerkleShoptalk Europedentsuconversational insight tools · merkle

Merkle: 88% of Retailers Deployed AI, Only 6% Proved ROI

Merkle research across 100 large enterprises found that 88% have deployed at least one AI application since late last year, but only 6% can draw a straight line to EBITDA value. The 82-point gap reflects a critical distinction between performative AI activity and disciplined execution that actually moves the needle on profitability.

AI-generated. Summaries are AI-generated from cited sources. Click through for the original report.

Holden Bale, Global Chief Strategy Officer at Merkle, presented research at Shoptalk Europe revealing a stark disconnect in retail AI adoption. Across a survey of 100 enterprises with revenues over a billion dollars, 88% have deployed at least one AI application since the end of last year, yet only 6% can demonstrate measurable EBITDA impact (RetailNews.ai). Bale attributed this 82-point gap to confusing visible activity with genuine execution, a distinction he framed as the central challenge facing retail leadership today.

Bale identified five patterns that separate real value from performative AI deployment: starting where an organisation's data advantage is strongest; tying every initiative to a clearly defined, time-bound ROI target; redesigning the actual work rather than layering technology onto unchanged processes; engineering trust deliberately into models so users understand and act on recommendations; and matching use cases to user altitude, from store-level staff to C-suite (RetailNews.ai). He emphasised that success metrics must measure real job improvement, not mere tool adoption, and that organisations must be disciplined enough to kill underperforming initiatives within defined timeframes rather than allowing sunk-cost bias to perpetuate them.

Looking ahead, Bale predicted that by early next year, 100% of employees at sophisticated retail organisations should have access to role-ready conversational insight tools tailored to their specific roles, with a 50 to 70% reduction in time from insight to published content (RetailNews.ai). For commerce practitioners, the takeaway is clear: the competitive advantage will accrue not to those who deploy AI fastest, but to those who close the execution gap through disciplined application of data strategy, clear outcomes, process redesign, trust mechanisms, and role-based implementation.

Sources:1 report
  • RetailNews.ai
‹ Newer storyAdobe Commerce: AI-Referred Traffic Surges 393% as Brands Optimize VisibilityOlder story ›Bing upgrades AI Performance Report with expanded visibility metrics

More from June 23, 2026

  • Bing upgrades AI Performance Report with expanded visibility metrics
  • Adobe Commerce: AI-Referred Traffic Surges 393% as Brands Optimize Visibility
  • Zebra Technologies Positions AI-First Supply Chains for Disruption Resilience
ShareLast updated: June 23, 2026