TL;DR
Google’s AI Overviews and AI Mode summarise results and are beginning to complete tasks (e.g., finding reservations) inside Search. This moves discovery upstream, reducing click-through rates on informational queries. To stay visible, B2B brands must optimise for inclusion in AI answers while focusing on converting higher-intent traffic that continues to click through.
AI is no longer just shaping how information is found; it is deciding what gets seen first. Google AI Overviews and AI Mode are pulling early discovery “into the results” by summarising answers and increasingly performing tasks within Search. For B2B brands, this means being mentioned or cited in AI answers is as critical as traditional ranking. The challenge is clear: fewer clicks on informational queries, higher value on the intent-driven visits that still make it through.
Why Are Google AI Overviews Changing Discovery?
Google maintains that “best practices for SEO remain relevant,” where helpful content, clear structure, and schema are still essential.
However, independent data shows the shift in user behaviour:
- Ahrefs reports a 34.5% CTR drop for position one when an AI Overview appears.
- Pew Research found that click-through halves when an AI summary is shown (8% vs 15%).
Meanwhile, AI Mode is rolling out to over 180 countries, testing “agentic” steps such as booking reservations, which suggests that transactions will increasingly happen inside Search itself.
What Do Google AI Overviews Mean for B2B Brands?
- Visibility is more than rank. Brands must aim for citations inside AI answers, not just SERP positions.
- Search scorecards should evolve. Presence metrics, such as mentions and citations, matter alongside rankings.
- Conversion focus deepens. Persuasive pages must be ready for the reduced, but higher-intent, traffic that clicks through.
How Can B2B Brands Optimise for AI Overviews?
- Use JSON-LD schema (Organisation, Service, FAQ, HowTo) to make facts machine-readable. This increases the likelihood that Google’s AI Overviews can lift and attribute your information directly, ensuring brand presence in cited answers.
- Publish answer-first pages (TL;DR, decision criteria) aligned with scanning behaviour and extractability. Structuring content this way not only matches how humans read but also how models extract concise, quotable responses.
- Establish a presence dashboard: track share-of-voice and citation rates for priority buyer questions. Monitoring citations alongside rankings helps teams quantify AI visibility and spot early gaps before traffic loss compounds.
- Optimise for attribution, not just ranking. Use consistent brand mentions and reinforce entity signals across site and schema, so AI models can reliably tie answers back to your organisation.
- Refresh high-value pages with clarity and concision. Short, well-structured updates make older content more extractable by AI, increasing its chances of surfacing in summaries without requiring full rewrites.
Micro-Glossary
- AI Overviews (AIO): Google’s AI summaries in Search; standard SEO still applies.
- AI Mode: Chat-style Search expanding globally; testing agentic steps.
- Agentic (in Search): AI performs tasks (e.g., finds tickets) rather than summarises.
- LLM-readable: Consistent, schema-backed facts that models can surface and attribute.
