Global marketers risk strategic pitfalls as artificial intelligence (AI) agents amplify the quality of audience data they are fed, making good data better and bad data worse, rather than correcting inherent flaws.
AI agents process audience data at a scale and speed unmatched by humans, meaning any existing data quality, whether positive or negative, is significantly magnified in their output, according to industry experts.
Mallory Gray, creative director at Skydeo, emphasized that human input remains important for determining what truly matters and what a brand’s strategic actions should be. She added that AI agents primarily expand the raw material available for human decision-making.
Many marketers mistakenly equate being cited by AI tools like ChatGPT or Gemini with being chosen for the right reasons, a misconception that can lead to automated blind spots in their strategies.
A key warning sign of a flawed AI strategy is an increase in output, such as content or campaigns, while engagement or conversion rates either flatten or decline, Gray reported.
The current reliance on AI agent strategies echoes the challenges faced during the Data Management Platform (DMP) era, where extensive use of third-party data often failed due to widespread data inaccuracy.
Brands should conduct thorough audits of the audience signals feeding their AI tools, differentiating between declared, observed, and inferred customer data, Skydeo advised.
Marketers should also cease measuring AI visibility solely by citation count, as this metric does not accurately reflect strategic effectiveness.
An important check for brands is to ensure that team members can articulate the rationale behind audience targeting or messaging decisions, rather than simply attributing these choices to AI.
This human oversight helps prevent a dependency on AI without understanding the underlying data quality or strategic justification.
Source: Search Engine Journal
