Google Search Console reporting for AI Overviews may give businesses an incomplete picture of how visible they really are in search. According to a report from Search Engine Journal, Google uses what is described as block flattening in Search Console data for AI Overview results, which can make a site appear to rank very highly even when its actual prominence inside the AI-generated result is limited.

For businesses that rely on SEO reporting, the practical message is clear: position metrics alone may be less useful in understanding performance in AI-driven search interfaces. Traffic, clicks and conversions are likely to be more meaningful indicators.

What happened

The report says Search Console uses a reporting method referred to as block flattening for AI Overviews. In practical terms, this means an AI-generated results block may be treated in a simplified way in Search Console reporting, rather than reflecting the exact prominence of each cited source within that experience.

If this interpretation is correct, a business might see what looks like a strong ranking signal in Search Console while receiving relatively little attention, traffic or user engagement from that search result.

The source article frames this as a measurement issue rather than a direct change to search rankings themselves. It does not mean a website is necessarily performing better or worse in Google Search; it means the reporting may not fully represent how users encounter links inside AI Overview layouts.

Why it matters for European businesses

Many European SMEs, e-commerce teams and marketing departments use Search Console as a primary source for SEO reporting. If average position or impression data becomes harder to interpret in AI-led search results, businesses could make poor decisions based on misleading signals.

This matters in several ways:

• SEO reporting may become less reliable if viewed in isolation. A strong reported position may not translate into meaningful visibility.
• Marketing teams may overestimate organic performance. If reports show apparent top placement, stakeholders may assume a page is winning search demand even when clicks remain weak.
• Budget allocation decisions could be affected. Teams may continue investing in content formats or keywords that appear successful in ranking reports but do not generate business outcomes.
• AI search changes the user journey. As more answers are summarised directly in search interfaces, businesses may need to judge performance by assisted conversions, branded search growth and qualified visits, not only by traditional ranking metrics.

For companies operating across multiple European markets, this is particularly important because SEO reporting is often aggregated at country, language or product-category level. Small distortions in visibility data can lead to incorrect conclusions about local market performance.

Who may be affected

• SMEs that depend on organic search for lead generation and use Search Console as a core reporting tool.
• E-commerce businesses monitoring category and product visibility in Google search.
• Marketing teams and agencies reporting SEO success through ranking trends and average position metrics.
• Content teams creating informational pages intended to appear in AI-generated search features.
• Digital and analytics teams responsible for attribution, search performance dashboards and forecasting.

Businesses are most exposed where SEO reporting still prioritises rank-based KPIs over business outcomes such as revenue, enquiries, subscriptions or qualified leads.

What companies should consider

• Review SEO KPIs. Give more weight to clicks, sessions, leads, sales and conversion rate from organic search rather than average position alone.
• Audit reporting dashboards. Check whether internal or agency reports may overemphasise ranking-based metrics that are harder to interpret in AI Overview contexts.
• Segment branded and non-branded search performance. This can help distinguish general visibility from intent-driven visits that are more likely to convert.
• Compare Search Console data with analytics and CRM outcomes. Look for alignment between reported visibility and actual business results.
• Track landing-page performance over time. Pages cited in AI-related search experiences should be assessed by engagement and conversion quality, not just search appearance metrics.
• Prepare stakeholders for reporting changes. Explain that AI-driven search interfaces may reduce the value of simple position reporting and increase the importance of outcome-based measurement.

For European businesses, the broader lesson is that AI search is changing not only how users discover information, but also how performance should be measured. Search visibility still matters, but reported position on its own may no longer be a reliable proxy for business impact.