Marketers know AI is using bad data to make decisions
Marketers are giving AI more authority even as bad CRM data undermines revenue measurement, reporting, and the decisions AI makes.
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Marketing teams are giving AI more authority over campaigns while feeding it CRM data they know isn’t ready for the job.
Nearly 91% of marketers say data readiness is critical for adopting AI, but only 21% consider their CRM data very well prepared for the AI tools they use or plan to use, according to Validity’s “State of CRM Data Report 2026.” Meanwhile, 45% already use agentic AI that can act without human review, and two-thirds of organizations increased the number of marketing decisions delegated to autonomous agents over the past year.
Bad CRM data once meant manual cleanup and inaccurate reports. Now an AI agent can act on those errors automatically, sending a campaign, scoring a lead, personalizing an offer, or reallocating budget before anyone reviews the decision.
Marketers know the data isn’t ready
Only 26% of respondents said more than three-quarters of their CRM data is accurate and complete. Nearly half said their organization struggles with CRM data quality.

The consequences are already reaching revenue. Sixty-two percent said poor CRM data probably or definitely cost their organizations revenue due to issues such as missed renewals, inaccurate forecasts, lost deals, and misdirected campaigns.
At the same time, only 28% are very confident their CRM provides an accurate view of campaign performance and revenue impact. Organizations believe bad data is costing them money, yet they have limited confidence in the data they use to determine how much.

That uncertainty follows the numbers into meetings. Nearly 69% said a revenue, pipeline, or performance number they or their team presented was challenged or walked back because the underlying data was wrong. Among C-suite executives, SVPs/VPs, department heads, and directors, the figure rises to nearly 75%.
Better attribution and reporting can’t solve that problem if the customer, campaign, and revenue data underneath them remain questionable.
AI turns data errors into marketing decisions
The consequences of unreliable CRM data become more serious as AI makes more decisions. About 19% of respondents said they frequently presented or acted on an AI-generated recommendation that they later suspected was wrong due to poor underlying data. Another 43% said it happened occasionally.

The numbers rise sharply with seniority. Nearly 78% of C-suite executives and 92% of SVPs/VPs said they had acted on an AI recommendation they later suspected was wrong, compared with 41% of individual contributors.
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The readiness gap also has an organizational component.
Only 39% of C-suite executives, SVPs/VPs, department heads, and directors said that marketing and IT or RevOps collaborate very well to keep data usable for campaigns. Among senior managers and individual contributors, that falls to 27%.
Ownership is similarly unsettled. Only 41% said their organization has a dedicated data governance team or owner. Respondents also cited poor alignment among marketing, sales, and RevOps and a lack of clear internal ownership among the barriers preventing CRM data from reliably supporting marketing.
The result is an uncomfortable combination: more automated decisions, questionable underlying data, and responsibility for maintaining that data spread across teams.
Fixing the readiness gap
Asked what would most increase confidence in CRM data for strategy, reporting, and AI, 39% chose continuous automated monitoring that catches and fixes issues in real time. A unified platform ranked second, followed by third-party data validation or enrichment.

Validity’s “State of CRM Data Report 2026” surveyed 500 B2B and B2C marketing professionals in July 2026 at organizations with at least 100 employees. Respondents were in the U.S., U.K., Brazil, Australia, and New Zealand. It can be downloaded here. (Registration required)
MarTech is owned by Semrush. We remain committed to providing high-quality coverage of marketing topics. Unless otherwise noted, this page’s content was written by either an employee or a paid contractor of Semrush Inc.
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