The news: AI often delivers old or incorrect information, leading to faulty decisions and brand safety risks.

• 58% of marketing, insights, and agency professionals in the US, the UK, and Singapore have made a “significant” decision based on an AI answer that wound up being wrong or misleading, per GWI.
• 63% have unknowingly acted on outdated information from an AI tool.
• 82% have experienced at least one negative consequence from faulty AI-generated information, including delayed decisions (36%), customer complaints (34%), financial loss (27%), and reputational damage (26%).

Despite these issues, only 36% verify AI answers “most of the time," and 22% check only occasionally.

Zooming in: AI adoption is outpacing governance and verification practices, and the productivity benefits of automation could be diminished if teams act on bad outputs.

• Efficiency gains across analysis and campaign planning could be reversed if decisions take longer or more time goes into fixing mistakes.
• AI-related errors can also compound when inaccurate information is shared across departments or teams, making mistakes harder to identify and correct.

Recommendations for marketers: Clear verification standards for AI-assisted research, campaign planning, customer communication, and strategic decisions are crucial, especially when outputs affect spending or feed into public-facing operations.

• Establish vetting routines that use company documents and credible third-party information, rather than using a separate AI tool to check the original AI’s work.
• Be up front with customers about when AI is used in external communications, both to promote transparency and to let them know that they may want to scrutinize answers more than they would with human assistance.
• Track the frequency and cost of AI-related errors, including time spent correcting mistakes and customer complaints, to determine whether automation is delivering ROI and identify places where human oversight is most necessary.

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