Supermetrics, the Helsinki‑based marketing intelligence platform, released the latest edition of its annual Marketing Data Report, shedding light on how artificial‑intelligence tools are actually being deployed across retail, e‑commerce and consumer‑packaged‑goods (CPG/FMCG) organizations. While the study confirms that reducing marketing spend remains a top strategic objective for most respondents, the practical use of AI to achieve that goal appears markedly limited.
AI Use in Campaign Optimization Remains Low
Among the 400‑plus marketers surveyed worldwide, a mere 17 % reported leveraging AI for the analysis and fine‑tuning of advertising campaigns—the lowest adoption rate across all AI use cases examined. This figure stands in stark contrast to the 70 % who identified “optimizing marketing spend” as a short‑term priority, indicating a sizable execution gap.
The report also highlights that AI adoption is uneven across functional areas. Content‑generation tools enjoy the highest uptake at 38 %, while workflow automation sees 27 % of respondents employing AI. In comparison, the ability to pinpoint high‑performing campaigns, channels and audience segments via AI remains underutilized.
Sector‑Specific Disparities
Retail firms lead the pack in applying AI to campaign optimization, with 22 % of retail respondents indicating active use. CPG and FMCG marketers follow at 14 %, whereas e‑commerce participants lag far behind at just 8 %, despite operating in environments rich with real‑time data.
These numbers suggest that even sectors with abundant digital footprints are not translating data availability into AI‑driven decision‑making for spend efficiency.
Barriers to Adoption
- Talent shortage: 38 % of respondents cite a lack of in‑house expertise as a blocker.
- Infrastructure gaps: 30 % say their technical stack is insufficient to support AI workloads.
- Unclear ROI: 27 % are uncertain about the business value that AI can deliver in their specific context.
The convergence of these factors creates a scenario where marketers recognize the strategic importance of AI but feel ill‑equipped to operationalize it.
Executive Perspectives
“Marketers are running more campaigns across more channels than ever before, yet many still lack the real‑time visibility needed to act on performance when it matters,” said Anssi Rusi, CEO of Supermetrics.
Adding to that, Zach Bricker, Head of Solutions Engineering & Data Activation at Supermetrics, observed, “Marketers know real‑time optimization drives results, but fragmented data keeps them reactive. Teams need to move from simply having data to activating it. AI and automation remove technical friction and allow experts to focus on strategy and revenue impact.”
Both executives stress that the current bottleneck is less about willingness and more about the ability to integrate AI into existing workflows.
Industry Context
The findings arrive at a moment when generative AI and large language models dominate headlines, yet many enterprise marketers remain cautious about extending those capabilities to performance‑driven use cases. The report underscores a broader industry trend: while AI hype fuels strategic ambitions, practical deployment—especially in the high‑stakes arena of spend optimization—still lags behind.
For enterprises, the implication is clear: to close the gap, investment must shift from isolated AI pilots to end‑to‑end data architectures that enable real‑time insight activation. This may involve adopting unified data platforms, upskilling analytics teams, or partnering with vendors that can provide managed AI services.
The complete Supermetrics Marketing Data Report 2026 is available for download, offering deeper breakdowns of methodology, regional variations, and additional insights into AI adoption trends across other marketing functions.
