How do we tackle AI Mode becoming the default Search experience?

Search is shifting from lists of links to answers, conversations, and multimodal guidance. Google’s AI Mode and AI Overviews are moving toward default behaviours in more markets and surfaces, blending text, voice, and vision while sending billions of clicks to the open web (according to Google) even as independent analyses show mixed impacts on downstream website traffic and CTR.

I’ve talked about this new blended experience before as being the multi-modal future of Search.

What’s really changing in Google Search

Google’s “AI Mode” and related capabilities (AI Overviews, Live/Voice, Lens) allow users to refine naturally, ask follow-ups, and combine text, images, and live camera input. This moves discovery upstream and compresses steps that used to require multiple queries and clicks.

Visual + shoppable by default

AI Mode increasingly supports visual exploration and product discovery, generating rich result sets that feel like a headless storefront layered on top of the open web.

Rollout and prevalence are rising

Studies from Semrush and WordStream show AI Overviews now appear on a meaningful share of queries, and appear most likely on informational intent queries. Furthermore, geographical coverage and language availability has expanded significantly in 2025, and continues to do so.

Guardrails and inconsistency persist

Google sometimes disables AI summaries on sensitive topics, underscoring evolving safety and policy boundaries that brands must monitor.

User behaviour, the new demand landscape

For simple information needs, traditional search engines still lead; for complex tasks, AI chat and AI search gain share, especially among younger cohorts.

Pew 1 in 5 US workers now use AI in their work, which has increased since the 2024 survey.

AI usage is mainstreaming

Consumer surveys show high and growing AI adoption across work and study contexts. Marketers should assume “AI-assisted journeys” are now normal.

Google and “higher-quality clicks,” while third-party trackers and marketers report uneven or declining organic traffic from AIO impressions.

Treat this as a fragmented market with channel-specific realities.

Strategic implications for brands

Answering is the new ranking

If your page cannot be safely summarized with citations, you risk exclusion or attribution loss. Structure content to produce precise, “cite-able” answers.

Entity clarity beats term density

AI systems reconcile entities and relationships. Invest in first-party entity graphs, schema, author/organisation identity, and consistent naming to improve inclusion and attribution in AI responses.

Multi-modal readiness matters

With AI Mode and Live/Lens, images and video (and their metadata) can be the first touch. Treat visual assets as structured data: authoritative captions, EXIF where appropriate, product attributes in alt and surrounding copy.

Own the journey, not just the click

Expect fewer blue-link visits on informational queries; shift KPIs toward assisted outcomes (brand recall, shortlist inclusion, direct navigations, logged-in engagement). Use media mix modelling and incrementality tests to prove value beyond SERP CTR.

Possible scenarios for the next 12–18 months

Probable baseline scenario

As AI Mode becomes the default way people interact across more regions, AI Overviews will appear in a larger share of informational and some navigational searches. At the same time, visual and voice interactions will continue to grow. The result is a shift in traffic patterns, where the winners will be those with clear, well-cited, and value-rich content that provides direct answers.

Optimistic scenario for content publishers

Google’s emphasis on “highlighting the web” could yield improved citation density and click propensity from AI surfaces, especially for authoritative sources and commerce partners supplying structured, verifiable data.

Restricted scenario based on legal constraints

More topics could be disabled or down-weighted for AI summaries, and visibility could fluctuate for sensitive categories as the compliance burden increases. This would lead to even more fragmented SERPs, and queries treated as YMYL would become more complex to optimise for.

The enterprise playbook

Enterprises cannot treat AI Mode as a marginal SEO issue. It reshapes discovery, evaluation, and conversion at scale.

The enterprise playbook is a structured response designed to help large organisations adapt quickly, preserve visibility, and capture new forms of demand. It sets out four pillars: content readiness, measurement, demand protection, and governance.

Each pillar aligns with the reality that AI systems now sit between your audience and your brand, filtering, summarising, and shaping perception.

Make your content “AI-ready”

  • Design for summarisation. Standardise problem → approach → constraints → outcome → sources blocks in pages so AI can extract safe, precise snippets with citations.
  • Fortify entity signals. Comprehensive schema (org, product, how-to, medical where applicable), authorship, canonical naming, and consistent IDs across CMS, PIM, DAM.
  • Publish evidence, not just claims. Add methods, datasets, FAQs, and expert quotes with provenance to increase “citable credibility”.
  • Provide crisp product imagery, step-by-step photos, diagrams, and short clips with strong metadata to feed visual and live search.

Replatform measurement

  • Track AI surface exposure. Where available, tag impressions from AI modules; triangulate with panel-based research and on-site brand search lifts (Pew Research 2024).
  • Adopt assisted-outcome KPIs. Include shortlist adds, sample requests, configurator starts, and return visits, then calibrate with MMM or geo-holdouts.
  • Develop attribution models that account for AI touchpoints. Move beyond last-click analysis and incorporate customer journey stages where AI summaries influenced awareness or preference.
  • Build cross-functional dashboards. Ensure marketing, analytics, and finance teams have a unified view of AI-driven impressions, CTR impact, and downstream conversions.

Protect and grow brand visibility

  • Shift informational top-funnel to owned channels. Guides, calculators, and tools that build first-party audiences (newsletter, community, trials) hedge against thinner organic click-through.
  • Strengthen product feed and merchant data. For shoppable AI experiences, prioritise completeness and freshness in feeds, attributes, and reviews to qualify for richer placements.
  • Invest in brand queries. Brand and navigational demand is less exposed to AIO cannibalisation; build them via PR, creators, and category leadership content.
  • Build loyalty ecosystems. Encourage logged-in use, loyalty programmes, and exclusive content access that capture audiences beyond initial AI-driven discovery.
  • Test direct demand accelerators. Use influencer partnerships, co-branded campaigns, and offline-to-online bridges that create brand recall independent of AI intermediaries.

Governance for a moving target

  • Create an “AI surfaces council.” SEO, product, data, legal, and brand meet monthly to review visibility shifts, policy changes, hallucination risks, and experiment results.
  • Run red-team reviews. Stress-test your content for mis-summaries on sensitive topics; define takedown/escalation pathways aligned to Google’s evolving guardrails.
  • Establish escalation protocols. Define rapid-response processes for when AI summaries misrepresent or omit your brand.
  • Integrate risk management. Make AI visibility and policy monitoring part of enterprise risk frameworks, ensuring board-level oversight.
  • Continuously train teams. Ensure editorial, analytics, and PR teams understand how AI surfaces operate and what content practices increase inclusion and accuracy.

What “good” looks like in 90 days

Translating strategy into action requires tangible milestones.

The next 90 days should be treated as a sprint to establish baselines, implement AI-ready practices, and validate new measurement approaches.

This section outlines the practical steps enterprises can take immediately to prepare for AI Mode becoming the default search experience.

  1. Inventory & baseline. Map your top 500 queries/pages to: AIO presence, citation presence, and click propensity differences vs. non-AIO SERPs.
  2. AI-ready templates live. Ship new page templates with evidence blocks FAQs, structured data, and visual assets.
  3. Visual discovery pack. For top product/problem pages, add Lens-friendly imagery and short clips with descriptive text and attributes.
  4. Measurement patch. Stand up assisted-outcome dashboards and a lightweight MMM or geo-test to quantify non-click value.
  5. Policy monitors. Automate alerts when AI summaries are enabled/disabled for sensitive topics in your domain.

Board-level takeaways

At the board level, the conversation around AI Mode needs to be practical and forward-looking rather than buried in technical detail. Here are the plain truths:

  • This is not just “SEO with extra steps.” Think of it as designing experiences that machines can understand and safely retell to users.
  • You will likely see fewer clicks on informational queries. That does not mean you lose, success comes from being cited, remembered, and trusted.
  • Multimodal is not optional. People will discover brands through voice, camera, and shoppable visuals, so treat those assets as core brand touchpoints.
  • Do not rely solely on last-click metrics. Google says AI brings quality traffic, but outside data shows a mixed picture. The smart move is to test, measure influence earlier in the journey, and diversify how you judge ROI.