Tag: publishers

Google Connected Apps Platform Preview for AI Mode & Gemini (2026)

Publisher / product takeaway: On October 28, 2026 Google opened a developer preview of the Connected Apps Platform — a single path to build once (via a cloud-hosted MCP server or Android MCP / AppFunctions), register in the Google Connected Console, and reach users inside Search AI Mode and the Gemini app. SEJ’s October 31 write-up (and Robby Stein’s “public preview” note) makes the SEO angle clear: apps that pass review can be selected when AI Mode routes a task. This is complementary to our morning piece on Alphabet Q3 AI Mode monetization — that post covers ad RPM pressure; this one covers agentic distribution and brand visibility inside the same surfaces.

Primary sources: Google’s Connected Apps Platform announcement, the Connected Apps developer hub, Search Engine Journal (Matt G. Southern), and TechCrunch. Live Search AI Mode apps (U.S. English) currently include Instacart, Canva, YouTube Music, Yahoo Fantasy Football, and Sleeper; Google says 50+ Connected Apps across Search and Gemini, with Adobe, Experian, Localiza, and Peloton moving from Gemini toward Search and Calm launching on both.

What the Google Connected Apps Platform is

Connected Apps already let people link a third-party service once, then complete real actions — grocery orders, design drafts, playlists — inside Search AI Mode or Gemini without bouncing to a separate browser session for every step. The platform preview is Google’s attempt to productize that pathway: instead of bespoke partner deals only, more developers can apply, build against standard protocols, submit for review, and monitor traffic, latency, and error rates after go-live.

Google’s blog (Chips Mistry / Mai Lowe) frames it as “build once and reach high-intent users across both Search and the Gemini app,” with brand control (verified logos, authenticated accounts) retained by the developer. Access is phased: U.S. developer preview / waitlist first, with more developers, markets, and Google products promised over coming months.

How MCP server vs Android MCP (AppFunctions) works

The platform standardizes two integration paths documented on Google’s Connected Apps hub:

MCP server (cloud / remote): You expose tools and authorized data over the open-standard Model Context Protocol. Google’s docs position this as the path to engage users across applicable Google products — including Gemini and Search users on web, Android, and iOS (per SEJ’s reading of Google’s guidance). OAuth 2.1 is used so Gemini/Search can act on a user’s behalf after they link the app. You can also design richer UIs with MCP Apps.
Android MCP (AppFunctions): AppFunctions are Android’s MCP solution. This is a client-side / on-device path: the Jetpack AppFunctions SDK lets an Android app share native features with agents such as Gemini on Android. Tool execution happens locally on the device — useful when data or actions should stay on-device rather than round-tripping through your cloud.

Dimension	MCP server (remote)	Android MCP (AppFunctions)
Protocol / SDK	Model Context Protocol (cloud-hosted server)	Jetpack AppFunctions (Android MCP)
Where tools run	Your remote server	On the user’s Android device
Reach (per Google / SEJ)	Gemini + Search users on web, Android, iOS	Gemini users on Android
Auth pattern	OAuth 2.1 for user-authorized access	Device-local app capability sharing
Best when	Cross-surface actions + personal account context	On-device features / local execution
UI options	MCP Apps for richer interactive UI	Native Android app surfaces

Analysis: Product and SEO teams should not treat these as interchangeable. If your goal is visibility inside Search AI Mode on the open web, the remote MCP path is the one that maps to that surface. Android MCP is still strategic for Gemini-on-Android retention, but it is not a substitute for Search distribution.

Registration, categories, review, and anti-gaming policy

Onboarding during preview is self-service via the Google Connected Console: register tools, run tests, submit for review and publishing, then monitor usage. Developers choose whether the app goes live in Search, Gemini, or both, and specify country / language / product availability.

Category lock: You pick a category that defines minimum capabilities; SEJ notes the prerequisites page says the category cannot be altered after registration.
Capability list: Identify at least three capabilities shown to users when they decide whether to connect.
Test accounts: Sign-in apps must provide Google with test accounts and sample data; an app Google cannot fully test may be rejected.
Anti-gaming / model-selection policy: Connected apps must not deceive or influence the model into adverse behavior — for example using overly broad or deceptive capability descriptions to get selected over another Connected App. Apps also cannot reference other tools or invent rules for when other tools should be used, and must not push third-party ads/promotional materials inside the integration (own brand info is allowed).
Enforcement: Rejection, suspension, removal from the platform, or developer-account suspension/termination.

Google’s MCP server guide (as cited by SEJ) says models rely on server instructions to recognize when to delegate — so clear, accurate capability text is both a policy requirement and a routing requirement. This is closer to honest tool metadata than classic keyword stuffing: overclaiming can get you rejected, not ranked.

What’s live today (Search AI Mode vs Gemini)

Per Google Help / SEJ, Connected Apps operating in Search AI Mode for U.S. English today include:

Instacart
Canva
YouTube Music
Yahoo Fantasy Football
Sleeper Fantasy Football

Google says it has launched more than 50 Connected Apps across Search and Gemini (productivity, ticketing, health/fitness, and more). Partner integrations such as Adobe, Experian, Localiza, and Peloton are live for Gemini users and, in the coming weeks, are expected in Search as well. Calm is launching a new integration across both Search and Gemini.

On the user side, AI Mode may default to the last app used for a task; users can specify another app or pick from available apps after a general query. That UX detail matters for product owners: retention and “last-used” habit can compound once you are in the catalog.

Why it matters for visibility on the agentic web

TechCrunch put it bluntly: similar to how SEO helped companies show up in rankings, Connected Apps could be an early step for businesses that want services visible when AI agents reshape browsing. For publishers and product owners reading this site, the practical map looks like this:

Citation / retrieval still matters for answers — see getting cited in AI search and schema markup for AI search — but action surfaces (book, buy, design, play) may route to Connected Apps rather than blue links.
AI Mode is already a different traffic and ad surface — Reddit’s claim that AI Mode does not drive traffic and Alphabet’s admission of lower AI Mode monetization are about referrals and RPM. Connected Apps are about who owns the completion moment when Google does keep the user in-product.
Preferred sources and generative controls remain relevant for content discovery (AI Mode preferred sources, Search Console generative AI control), while Connected Apps are a parallel track for productized services.
Measurement: if you ship a Connected App, instrument AI Mode / Gemini sessions separately — reuse patterns from tracking AI referral traffic in GA4 and add Connected Console latency/error metrics as product KPIs.

John Mueller (Google Search Advocate) called Connected Apps exciting as a search platform while stressing it is “still extremely early” and noting he does not work on the product — a useful calibration: treat this as a strategic watchlist item, not a guaranteed traffic channel.

Practical checklist for publishers, SEO, and product owners

Decide if you have an “action” product (commerce, booking, creative, media, health) that belongs in AI Mode / Gemini — not every publisher site needs a Connected App.
Join the U.S. developer preview waitlist at developers.google.com/connected-apps if you do; access is phased.
Prefer remote MCP when Search AI Mode reach (web + iOS + Android) is the goal; use Android MCP when on-device Gemini features matter.
Write narrow, truthful capability descriptions — policy forbids gaming model selection with broad/deceptive claims; clear instructions also improve routing.
Lock category and ≥3 capabilities carefully before registration (category cannot be changed later per prerequisites notes).
Prepare test accounts + sample data so Google’s review can fully exercise sign-in flows.
Choose Search vs Gemini vs both deliberately; dual presence compounds habit/default-last-app behavior.
Keep classic SEO / citation work — Connected Apps do not replace ranking, AI citation eligibility, or generative Include/Exclude decisions in Search Console.
Plan analytics for AI Mode sessions and Connected Console traffic/latency/errors separately from organic SERP clicks.
Watch the Adobe / Calm / Peloton Search rollout as a signal of how fast the Search catalog expands beyond today’s five U.S. EN apps.

FAQ: Google Connected Apps Platform for AI Mode and Gemini

What is the Google Connected Apps Platform preview?

It is Google’s October 28, 2026 developer preview for building once (MCP server or Android AppFunctions), registering in Google Connected Console, and publishing apps that run inside Search AI Mode and/or the Gemini app after Google’s review.

How do MCP server and Android MCP differ?

A remote MCP server exposes tools over Model Context Protocol and, per Google/SEJ, can reach Gemini and Search users on web, Android, and iOS. Android MCP via AppFunctions runs tools locally on Android and primarily serves Gemini users on Android.

Can I write broad capability text to get selected more often?

No. Google’s Connected Apps policy bars overly broad or deceptive capability descriptions meant to influence the model into selecting your app over another. Violations can lead to rejection, suspension, removal, or account termination.

Which Connected Apps are live in Search AI Mode today?

For U.S. English Search AI Mode, Google’s help materials list Instacart, Canva, YouTube Music, Yahoo Fantasy Football, and Sleeper. Google reports 50+ Connected Apps across Search and Gemini overall, with more partners (including Adobe, Experian, Localiza, Peloton, and Calm) expanding.

Is this a replacement for SEO or AI citation work?

No. Connected Apps target in-product actions and linked account context. Classic rankings, preferred sources, generative AI controls, and citation/retrieval quality still govern how content is discovered and referenced. Treat Connected Apps as a complementary agentic-distribution channel.

Who can apply, and where?

The platform is in U.S. developer preview / waitlist. Sign up and read docs at developers.google.com/connected-apps. Google says it will add more developers, markets, and Google products over the coming months.

Bottom line: The Google Connected Apps Platform preview turns AI Mode and Gemini into a reviewed app marketplace with MCP and Android AppFunctions as the pipes, Connected Console as the control plane, and an explicit ban on gaming model selection. For publishers and product owners, it is the distribution counterpart to AI Mode’s lower ad monetization and weaker referral stories — if Google keeps users in AI Mode, the brands that complete the task may be Connected Apps, not classic blue links. Apply if you have a real action product; keep citation SEO if you publish content.

November 1, 2026

Google AI Mode’s Lower Ad Monetization Slowed Search Growth (Alphabet Q3 2026)

Publisher takeaway: Alphabet’s Q3 2026 release (Oct 28) shows Google Search & other ads at $63.35B (+12% YoY) while CEO Sundar Pichai said year-over-year Search query growth hit a five-year high. On the earnings call, Chief Business Officer Philipp Schindler said strong growth in AI Mode queries impacted Search because of lower monetization in AI Mode — without disclosing how much less those queries monetize or how large the contribution was. For publishers, that is the revenue-side twin of last week’s traffic story: more AI Mode usage does not automatically mean more ad-supported clicks.

Primary numbers: Alphabet’s Q3 2026 earnings exhibit (SEC). CEO framing: Pichai’s Q3 remarks on the Keyword blog. Call reporting on AI Mode monetization: Search Engine Land (Danny Goodwin) and CNBC. This complements our coverage of Reddit’s claim that Google AI Mode “does not drive traffic” with Google’s own admission on the ad side.

Alphabet Q3 2026: the Search vs query gap

Alphabet reported consolidated revenue of $127.6B (+25% YoY). Google Cloud grew 103% to $30.7B. Diluted EPS was $2.12. Free cash flow for the quarter was −$9.065B (operating cash $42.290B minus CapEx $51.355B), per the SEC exhibit’s free-cash-flow reconciliation.

Metric (Q3 2026)	Figure	YoY context
Alphabet consolidated revenue	$127.6B	+25%
Google Search & other	$63.35B	+12% (from $56.567B in Q3 2025)
Google Cloud	$30.7B	+103%
Diluted EPS	$2.12	—
Free cash flow (ops − CapEx)	−$9.065B	ops cash $42.290B; CapEx $51.355B
Search query growth (YoY rate)	Highest in last five years	Pichai; includes commercial queries

Pichai also said the Gemini app reached 1 billion users and first-party model APIs were processing nearly 32 billion tokens per minute. Those AI product stats sit beside — not instead of — the Search ads line that still funds most of Google Services.

What Schindler said about Google AI Mode monetization

Asked why Search revenue growth slowed despite stronger query growth, Schindler acknowledged AI Mode’s role. Per Search Engine Land’s call write-up, he said: “It’s worth noting that the strong growth in AI Mode queries had an impact because of the lower monetization we were seeing in AI Mode.”

He also said foreign exchange was the single largest driver of Search deceleration versus Q2, with retail and media vertical spending changes also cited. Google did not disclose how much less AI Mode monetizes versus traditional Search, or how much of the slowdown AI Mode explained. Treat any dollar estimate as speculation — Google did not publish one.

Product behavior Google did quantify (carefully)

Query length: AI Mode queries are on average about 3× longer than traditional searches (Pichai).
Multimodal share: 1 in 5 AI Mode searches globally use voice, images, or documents.
Product listings CTR: Schindler said click-through rates are “already similar” between sponsored and organic product list items within AI Mode — that comparison covers product listings only, not all organic links or citations.
Incrementality: Most AI Mode queries were described as incremental; Google did not provide supporting figures.

Analysis: Similar sponsored vs organic product-list CTRs does not prove classic blue-link CTR is healthy inside AI Mode, and it does not fix the lower overall monetization Google itself flagged. Publishers should not read the product-listing remark as a blanket “AI Mode monetizes fine” claim.

Why publishers should connect revenue and traffic narratives

On October 31 we covered Reddit’s Q3 commentary that Google AI Mode does not drive traffic and that search referrals fell sharply in October for Reddit. Alphabet’s call adds the other half: Google is seeing strong AI Mode query growth with lower ad monetization on those sessions. Separately, AI Overviews / AI Mode SERP studies (see our Cyrus Shepard opt-out / halo notes) already warned that generative surfaces can shrink classic organic CTR even when a “halo” remains.

None of these sources alone prove a single industry-wide CTR number for AI Mode. Together they justify treating AI Mode as a different distribution and monetization surface — not a drop-in replacement for classic Search referrals.

What Google still has not published

Exact monetization gap (RPM / CPC / ads per query) for AI Mode vs traditional Search
Share of Search queries or Search revenue attributable to AI Mode
Organic citation / blue-link CTR inside AI Mode answers (beyond product listings)
Publisher-facing payment or contribution terms for AI Mode answers (related experiments remain limited; see our AI contribution pilot overview)

Publisher checklist after Alphabet Q3

Separate AI Mode / AI Overview traffic from classic Google organic in analytics — use GA4 AI referral tracking patterns so you are not averaging two different surfaces.
Watch Search Console generative AI controls when you manage Include/Exclude for Google generative experiences — see our GSC generative AI control guide.
Optimize for citation and retrieval, not only classic rankings — getting cited in AI search / retrieval remains the complementary playbook.
Do not invent AI Mode RPM estimates for board decks; Google withheld the figure. Scenario ranges are fine if labeled as analysis.
Track advertiser product-listing behavior if you compete in shopping/commercial SERPs — Google’s only disclosed AI Mode CTR comparison is for product list items.
Keep AdSense / Search ads expectations tied to classic SERP inventory until Google publishes AI Mode monetization detail.
Re-read the Reddit traffic piece beside this revenue admission — AI Mode traffic vs logged-in referral story — so product and ad teams share one narrative.

FAQ: Google AI Mode monetization and Alphabet Q3 2026

Did Google say AI Mode hurt Search ad growth?

Yes, in part. Schindler said strong growth in AI Mode queries had an impact because of lower monetization in AI Mode. He also said FX was the largest driver of deceleration vs Q2, with retail/media verticals also contributing.

How much less does AI Mode monetize?

Google did not disclose a percentage, RPM, or revenue contribution. Any precise figure you see elsewhere is not from Alphabet’s Q3 materials.

Did Search queries grow even while Search ads slowed?

Pichai said the year-over-year Search query growth rate was the highest in the last five years, including commercial queries. Search & other advertising still grew 12% to $63.35B — growth, but slower than earlier 2026 quarters as reported by financial press.

Are AI Mode product ad clicks performing like organic product clicks?

Schindler said CTRs are already similar between sponsored and organic product list items within AI Mode. That statement is limited to product listings and does not cover all organic results or citations.

Are most AI Mode queries incremental?

Schindler described most AI Mode queries as incremental. Google did not publish supporting volume or cannibalization figures.

What should publishers do next?

Instrument AI vs classic Google traffic, manage generative visibility in Search Console where relevant, pursue citation/retrieval quality, and avoid treating AI Mode as equal RPM inventory until Google publishes more detail. Pair this article with our Reddit AI Mode traffic analysis and AI Overview CTR notes.

Bottom line: Alphabet Q3 2026 confirms Search query growth at a five-year high while Search & other ads grew 12% to $63.35B — and Google explicitly tied part of the monetization story to lower AI Mode monetization, without quantifying it. Publishers should treat AI Mode as a lower-monetization, lower-referral surface until better disclosure arrives, and keep operational focus on measurement, generative controls, and citation eligibility.

November 1, 2026

Bing AI Training vs Grounding Controls (2026): Publisher Guide

Publisher takeaway: On October 30, 2026, Microsoft Bing (Krishna Madhavan) announced independent preferences for AI Training vs AI Grounding while keeping traditional Bing search eligibility unchanged. Training uses the shared robots.txt User-Agent __usage_ai-training (site/path) plus optional page-level Bingbot overrides; grounding is page-level only, with Allow / Disallow / a new DisallowExtended that limits grounding to Microsoft-operated experiences. These prefs replace NoArchive/NoCache for training and grounding on a 2027 timeline — plan by March 1, 2027 if you relied on the old tags.

Primary source: the official Bing Search blog (Oct 30, 2026). Industry context: Search Engine Land and Search Engine Roundtable. This complements our morning write-up on Google/OpenAI’s shared robots.txt AI training policy token — Bing adopts that shared training signal and goes further with separate grounding controls.

Training vs Grounding: two independent levers

Microsoft is explicit: training and grounding are independent. Your training setting does not change your grounding setting, and vice versa. Both default to Allow when no applicable preference is published. Traditional Bing rankings and indexing are not flipped by these usage prefs (subject to normal crawl/index requirements). Neither Allow nor Disallow guarantees inclusion, traffic, or payment.

Preference	Where you set it	Values	What it governs
AI Training	robots.txt (site/path) and/or page meta / X-Robots-Tag	Allow (default) / Disallow	Using content to modify learned parameters of a generative AI model (IETF-aligned training definition)
AI Grounding	Page-level only (no site-wide robots.txt grounding)	Allow (default) / Disallow / `DisallowExtended`	Using content as input to help inform AI-generated responses (not traditional search ranking)

A practical combo Microsoft highlights: set Training Disallow + Grounding Allow so pages stay eligible to inform Copilot / Bing AI answers (with citations) without feeding generative model training.

AI Training: shared robots.txt + Bing page overrides

For site or path training prefs, Bing uses the same shared policy token industry partners are adopting:

User-Agent: __usage_ai-training Disallow: /

Path-level example:

User-Agent: __usage_ai-training Disallow: /example-path/

Allow is the default — you do not need a robots.txt group to allow training. An optional explicit Allow is also documented. Microsoft extends the same preference to the page level so a single URL can override robots.txt:

<meta name="Bingbot" content="ai-training:disallow">
X-Robots-Tag: Bingbot: ai-training:disallow

When Microsoft detects the new AI Training or AI Grounding prefs on a site, it will disregard remaining NoArchive/NoCache prefs on that site for those uses. Page-level training overrides robots.txt for that page.

AI Grounding: page-level Allow, Disallow, DisallowExtended

There is no site-wide robots.txt grounding preference. Publish grounding per page via meta or HTTP header:

<meta name="Bingbot" content="ai-grounding:disallow"> (or ai-grounding:disallowextended / allow)
X-Robots-Tag: Bingbot: ai-grounding:disallow (same value variants)

Grounding value	Effect
Allow (default)	Content may help inform generated responses
DisallowExtended	Grounding limited to Microsoft-operated experiences (AI Mode, AI Overview, Copilot, Microsoft 365). Excludes third-party grounding Microsoft provides (e.g. Web IQ, Foundry grounding API)
Disallow	Content is not used to help inform generated responses

Microsoft warns that Disallow or DisallowExtended will significantly reduce AI visibility without affecting Bing search eligibility. Indexing/ranking in classic results is not grounding. Bing’s traditional search syndication API (links for classic search) is also described as out of scope for the grounding preference.

Timeline: Dec 2026 → Sep 2027

Date	What happens
Dec 15, 2026	Temporary grounding transition prefs open in Bing Webmaster Tools — only for sites using NoArchive/NoCache as of that date
Feb 1, 2027	Microsoft begins honoring new AI Training / AI Grounding prefs as it crawls
March 1, 2027	Deadline: after this, NoArchive/NoCache are no longer read as training/grounding prefs. NoArchive/NoCache users who want grounding limits must (1) publish page grounding prefs and (2) record a temporary preference in BWT
Sep 30, 2027	Temporary BWT grounding prefs expire (or earlier when Microsoft recrawls and discovers the new on-page pref)

Training has no temporary BWT setting — publish robots.txt or page training prefs by March 1, 2027. If you skip the temporary grounding record by March 1, pages that only had NoArchive/NoCache default to Allow for grounding until recrawl discovers a new preference.

What this means vs Google’s shared training token

Same day (Oct 30), Google and OpenAI announced plans around the shared __usage_ai-training token — covered in our policy token guide. Bing’s post confirms Microsoft is participating in that shared training preference and shipping a separate Microsoft grounding control with DisallowExtended. Do not collapse:

Shared training token — cross-provider training preference in robots.txt (Bing + Google/OpenAI direction).
Bing page training override — Bingbot meta / X-Robots-Tag for one URL.
Bing grounding — Microsoft-only page prefs; not a Google Search Console generative AI control equivalent.
Classic Bingbot crawl Disallow — still about crawl access; usage Allow does not override a robots.txt block on Bingbot.

Update mental models from our older AI crawlers allow/block cheat sheet: treating noarchive/nocache as the durable Copilot / Bing AI usage switch is being retired. Migrate to the new training + grounding prefs on the calendar above.

Activation caveats publishers miss

Publishing ≠ activation. Microsoft must crawl the page to discover the setting.
IndexNow can signal change and may improve recrawl chance — it does not guarantee a date.
Defaults matter. Sites that never set NoArchive/NoCache and never publish new prefs stay Allow/Allow.
NoArchive/NoCache users should not assume old restrictions carry over after March 1, 2027.

Publisher checklist (Oct 31, 2026)

Inventory pages/templates that emit NoArchive or NoCache today — those are your migration set.
Decide Training vs Grounding independently (e.g. Training Disallow + Grounding Allow for citation eligibility without training).
Publish training via __usage_ai-training in robots.txt and/or Bingbot page overrides where needed.
Publish grounding page-by-page (Allow / Disallow / DisallowExtended) — there is no robots.txt grounding group.
If you use NoArchive/NoCache: calendar Dec 15, 2026 (BWT temporary prefs), Feb 1, 2027 (honor-as-crawled), March 1, 2027 (hard deadline), Sep 30, 2027 (temp expiry).
Use IndexNow after publishing prefs to improve odds of timely recrawl — still verify in Bing Webmaster Tools.
Measure AI visibility separately from classic SEO — see tracking AI referral traffic in GA4 (Bing AI Performance reporting is a useful companion surface) and keep Google halo/CTR context from the Shepard opt-out notes.
Do not confuse with Google’s GSC generative AI Include/Exclude — different product; see our GSC control guide when you manage Google Search generative visibility.

FAQ: Bing AI Training vs Grounding controls

Does Disallow grounding hurt Bing search rankings?

No — Microsoft states these usage preferences do not change eligibility for traditional Bing search results (normal crawl and indexing rules still apply). Disallow / DisallowExtended mainly reduce visibility in AI-generated experiences.

What does DisallowExtended actually block?

It limits grounding to Microsoft-operated products such as AI Mode, AI Overview, Copilot, and Microsoft 365, and excludes grounding services Microsoft provides to third parties (examples cited: Web IQ and Foundry grounding API access).

Can I set grounding once in robots.txt for the whole site?

No. AI Grounding is page-level only. AI Training can be site/path in robots.txt via __usage_ai-training, with optional per-page Bingbot overrides.

We already use NoArchive / NoCache for Copilot — are we done?

Not for the long term. New prefs start being honored as crawled from Feb 1, 2027. After March 1, 2027, NoArchive/NoCache are no longer read as training/grounding prefs. Sites on those tags as of Dec 15, 2026 should also record temporary grounding prefs in Bing Webmaster Tools and publish new page prefs.

Is publishing a meta tag enough?

It is necessary but not sufficient until crawl. Microsoft must discover the setting; IndexNow may help recrawl odds but does not guarantee timing. Temporary BWT prefs bridge NoArchive/NoCache sites until recrawl or Sep 30, 2027.

How does this relate to Google’s shared __usage_ai-training token?

Bing is adopting the shared training preference in robots.txt (same industry direction as Google/OpenAI). Separately, Bing adds Microsoft-specific grounding controls and page-level training overrides. Read both this guide and our Google/OpenAI policy token article.

Bottom line: Bing’s Oct 30, 2026 controls split AI Training (shared __usage_ai-training + Bing page overrides) from AI Grounding (page-only Allow / Disallow / DisallowExtended). Classic Bing rankings stay separate; AI visibility shrinks if you Disallow grounding. Migrate off NoArchive/NoCache before March 1, 2027, and treat crawl discovery as part of activation. For adjacent publisher tooling, keep the AI crawler cheat sheet, shared training token notes, and getting cited in AI search in the same ops doc.

October 31, 2026