The most reliable diagnostic approach uses Search Console’s actual, available metrics in combination rather than any single number in isolation: check for impressions-versus-clicks divergence specifically on queries where AI Overviews are known or observed to appear (steady or rising impressions paired with falling clicks points toward an AI Overview or other SERP-feature effect rather than a ranking loss), check average position stability across the affected queries (genuine algorithm-driven ranking changes typically show position drops, not merely click-through-rate drops at a stable position), and check the Page Indexing report to rule out or confirm indexation problems as a separate, distinct cause entirely. Search Console cannot directly label a specific click loss as “caused by AI Overview”; the diagnosis is inferential, built from the pattern across these metrics, not a direct flag Google provides.
Building the diagnostic framework from real, available data
Impressions and clicks, tracked together rather than separately, are the starting point. A genuine ranking loss (the page dropping from position three to position eight, for instance) will typically show reduced impressions for queries where the page no longer ranks well enough to be shown as often, alongside reduced clicks, since fewer impressions naturally produce fewer clicks even at a constant click-through rate. An AI Overview or other SERP-feature effect looks structurally different: impressions can remain stable or even continue rising (the page is still being surfaced in Google’s results for the same volume of queries) while clicks decline, because the click-through rate at that same position has fallen, consistent with users increasingly finding their answer within an AI Overview or other on-page feature above the traditional listing rather than needing to click through to the page itself.
Average position is the second, corroborating check specifically because it distinguishes these two patterns cleanly. If average position for the affected queries has held steady across the decline period, that’s a strong signal the ranking itself hasn’t degraded, and whatever’s suppressing clicks is happening above or around a stable ranking rather than being a ranking loss in disguise. A position that’s actually dropped meaningfully during the same window points toward an algorithmic ranking factor (a core update reassessment, a specific quality or relevance issue) rather than a SERP-feature effect, since SERP features layering on top of results don’t typically change the underlying ranking position Search Console reports for the traditional organic listing itself.
Indexation status is the third, separate check, and it’s important to treat this as genuinely distinct from the first two rather than assuming it’s already covered by them. The Page Indexing report will show whether previously-indexed pages have dropped out of the index entirely, moved to a “crawled, not indexed” or similar non-indexed status, which is a wholly different failure mode from either an AI Overview click-share effect or a ranking algorithm change, one that would show as pages disappearing from impressions data entirely rather than showing reduced click-through at stable impressions or position. Ruling this out (or confirming it) early avoids misattributing what’s actually an indexation problem to either of the other two more discussed causes.
Sequencing the diagnosis
A sound diagnostic order checks the simplest, most structurally distinct explanation first: verify indexation status hasn’t changed for the affected URLs, since a straightforward indexation drop is the most mechanically distinct and most urgently actionable cause if present. If indexation is stable, move to the impressions/clicks/position triangulation described above, since that’s where the AI-Overview-versus-algorithm-change distinction actually gets resolved. Segment this analysis by query type where possible, since AI Overview presence and effect is genuinely uneven across query categories; simple, single-fact informational queries are documented as more likely to show AI Overview treatment and corresponding click-through effects than complex, transactional, or highly specific queries, so aggregating all affected queries together can obscure a pattern that’s actually concentrated in a specific query segment rather than uniform across the whole traffic decline.
It’s also worth cross-referencing timing against publicly announced Google core update rollout windows, since Google does publish start and completion dates for these; a decline that aligns tightly with an announced core update window, especially one that also shows an actual average position drop, points more toward algorithmic reassessment than SERP-feature displacement, while a gradual, position-stable decline with no clear core-update timing correlation is more consistent with organic AI Overview rollout expansion for the relevant query types over time, since AI Overview coverage has expanded incrementally rather than only through discrete, dated update events.
Practical implication
Build recurring monitoring around this same triangulation rather than treating it as a one-time investigation: track impressions, clicks, and average position together, segmented by query cluster, on an ongoing basis, and maintain a simple internal log of announced core update windows and any manually-observed AI Overview presence on key target queries. Where diagnosis is genuinely ambiguous, treat it honestly as ambiguous; Search Console’s real, available metrics can narrow the likely cause substantially through this pattern-based triangulation, but they can’t provide Google’s own definitive causal attribution, since that data isn’t something Google exposes, and presenting an inferential diagnosis as if it were a confirmed, labeled cause overstates what the available tooling can actually tell you.
