SEO professionals globally value data from artificial intelligence (AI) search visibility tools but distrust the platforms designed to provide it, according to a recent survey.
The findings indicate a substantial “trust gap” within the market, where practitioners recognize the importance of AI-driven insights but are reluctant to invest in dedicated measurement platforms due to concerns over credibility and transparency.
A survey of 163 AI search visibility practitioners reported an average perceived value of 4.20 out of five for AI visibility data, while willingness to invest in specialized platforms averaged only 3.19 out of five. Less than half of respondents, 44 percent, believed purchasing such a tool was worthwhile, with nearly one-third rating its value at one or two out of five.
The primary objections raised by respondents focused on trust, accuracy, and opaque methodology, accounting for 24 percent of concerns. Return on investment (ROI) and the ability to attribute business value followed closely at 20 percent.
Cost was not a significant barrier, with only 7 percent citing it as an objection. In contrast, 57 percent of respondents questioned either the credibility of the data or its direct connection to financial outcomes.
Respondents who expressed trust concerns valued the data as highly as their peers but were notably less inclined to invest in the platforms, the survey reported. This suggests a desire for external solutions to address these trust issues rather than developing internal tools.
Only 8 percent of practitioners reported building their own tooling for AI search visibility, indicating a preference for third-party solutions if trust could be established. The discrepancy between data valuation and platform funding was consistent across various professional settings, including agencies, in-house teams, and independent consultants, suggesting a widespread market challenge.
Industry expert Duane Forrester, who has shared insights on platforms like LinkedIn and X, previously highlighted the evolution of AI in search and the challenges practitioners face in adapting to new measurement paradigms.
Source: Search Engine Journal
