Even as more organizations adopt advanced measurement techniques, the perceived actionability of that measurement hasn’t kept pace. According to Forrester’s 2025 and 2026 global marketing surveys, adoption of marketing mix modeling and incrementality testing increased substantially year over year, but 49% of B2C marketing decision-makers in 2026 still say that analytics findings don’t translate into action.

Outputs from even the most advanced models aren’t delivering at the critical moment when marketers ask, “What should I do next?” Two compounding factors pull the brake on actionability: plan creation and the time decay inherent in insights. Translating insights into a marketing plan can take weeks, depending on available resources and approval processes. This delay negates the advantage of most insights: The older an insight is, the harder it is to capture value from it.

AI Shifts Measurement Conversations From “What Happened?” To “What’s Next?”

We just published a report, Marketing Measurement In The Age Of AI, that explores how generative and agentic AI address these challenges. It also outlines the skills and guardrails necessary for success. AI shrinks the gap between insights and value creation because it:

  • Automatically flags risks and opportunities in marketing performance. AI supports data ingestion and analysis by agentically monitoring data as it is ingested, identifying unexpected spikes or drops in performance or media data. By flagging these surprising occurrences as errors or anomalies, corrections can be made before models are impacted. In addition to finding problems, early detection also captures high-performing media buys and tactics while they are still actionable, giving marketers a chance to move budget quickly before advantage is lost.
  • Turns measurement into decision support. AI provides the possibility of near-instant translation of insights and recommendations into campaign tactics or media plans. They require some human oversight but significantly fewer resources than the historical insights-to-action processes, which involved analysts, planners, agencies, and manual queries or prompts. Trained on benchmarks, historical performance, and brand-specific goals, AI agents recommend actions based on current trends and campaign performance. Companies such as Adobe and Google already offer AI insight capabilities enhanced with recommended actions as part of their analytics solutions; many others have the same capabilities or will soon.
  • Bridges the gap between target and execution. AI eliminates time spent modeling and building target audiences by recommending and creating target segments based on previous performance and marketing goals. Agents then match these segments to the most effective creative and messaging elements for that segment, according to test results and previous performance. Time-related insight decay decreases substantially when AI-driven processes are used, though a human in the loop is still required to check for errors or strategic missteps.

Use Forrester’s Research On Measurement To Improve Marketing Performance

In addition to Marketing Measurement In The Age Of AI, here are some other key pieces of research to help marketers improve their measurement efforts:

Request a guidance session with me to discuss how to effectively leverage AI and apply best practices in marketing measurement to your own organization.

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