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Copilot Leaves WhatsApp on Jan 15 2026; Migration to Microsoft Surfaces

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Microsoft’s Copilot will stop responding inside WhatsApp on January 15, 2026, after WhatsApp’s owner revised its Business API terms to explicitly bar third‑party, general‑purpose large‑language‑model (LLM) chatbots from operating as primary services through the platform.

WhatsApp icon flows toward a calendar showing January 15, 2026, beside a colorful app logo.Background​

WhatsApp’s Business Solution (commonly referred to as the WhatsApp Business API) was originally built to let verified businesses send transactional messages, manage customer support threads, and run commerce flows at scale. Over 2024–2025, that API also became a low‑friction distribution channel for consumer‑facing AI assistants: vendors could expose an AI contact that users message like any other phone number and immediately get responses from an LLM. That experiment accelerated adoption — and friction — prompting Meta to add a new “AI Providers” clause to the Business Solution terms in October 2025. The new clause prohibits providers of LLMs, generative AI platforms, and general‑purpose AI assistants from using the Business Solution “when such technologies are the primary (rather than incidental or ancillary) functionality being made available for use,” with enforcement set for January 15, 2026. Microsoft’s Copilot team confirmed the practical consequence: Copilot on WhatsApp will be discontinued on that date, and users are being directed to Microsoft’s first‑party Copilot surfaces — the Copilot mobile apps (iOS and Android), Copilot on the web, and Copilot integrated into Windows — for ongoing access. Microsoft has also warned users to export any WhatsApp chat history they want to keep because the WhatsApp integration was unauthenticated and those conversations cannot be migrated automatically into Copilot account histories.

What changed: the policy in plain English​

The new “AI Providers” clause​

WhatsApp’s updated Business Solution terms introduce a named prohibition on “AI Providers,” a broadly worded category that explicitly includes creators or operators of LLMs, generative AI platforms, and general‑purpose AI assistants. The policy is clear about scope: if those AI capabilities are the primary functionality offered through the Business API, the provider is not permitted to use the API for distribution. The clause grants Meta wide discretion to determine what constitutes “primary functionality,” which creates a practical enforcement lever and potential ambiguity for edge cases.

Allowed vs. banned use cases​

  • Allowed: narrowly scoped, business‑centric automations (order confirmations, status updates, appointment reminders, or ticket triage) where AI is incidental to the company’s service.
  • Banned: consumer‑facing, general‑purpose AI assistants that use WhatsApp as their main distribution surface (for example, open‑ended chatbots whose primary product is conversational AI delivered through a WhatsApp contact).
This carve‑out recasts the Business API as a tool for enterprise messaging, not as a general‑purpose app store for AI assistants. Several reporting outlets and vendor notices confirm the enforcement date of January 15, 2026, and the immediate practical fallout for vendors like Microsoft and OpenAI.

Microsoft’s response and the migration plan​

Official guidance and timeline​

Microsoft published a formal advisory telling users that Copilot on WhatsApp will remain available through January 15, 2026, and will stop working on that date. The company recommends that users move to its first‑party surfaces — the Copilot mobile app (iOS and Android), Copilot on the web (copilot.microsoft.com), and Copilot inside Windows — to retain continuity and access richer features such as Copilot Voice, Copilot Vision, and the companion presence called Mico. Microsoft also emphasized that because the WhatsApp integration used an unauthenticated contact model, chat transcripts on WhatsApp cannot be imported automatically into Copilot accounts; users should export chats if they want to preserve them.

Practical migration steps Microsoft recommends​

  • Export any WhatsApp conversations with Copilot you want to keep (WhatsApp provides an Export Chat tool that can include media).
  • Install and sign in to the Copilot mobile app (iOS/Android) or use Copilot on the web to get an authenticated, account‑backed experience.
  • If you used Copilot for work flows inside WhatsApp, update any integrations or automations to reference authenticated Copilot APIs or alternative messaging channels.
Microsoft’s advisory is deliberately pragmatic: it treats the WhatsApp removal as an operational compliance obligation and points users to surfaces the company controls where identity, privacy settings, and multimodal features are implementable.

Why Meta says it changed the rules — and why critics disagree​

Meta’s public rationale​

Meta frames the update as a defense of the Business API’s original purpose: predictable, enterprise‑to‑consumer workflows. The company argues that open‑ended LLM assistants generate unpredictable message patterns, create elevated load, and increase moderation burdens — conditions that do not fit the Business Solution’s intended use. In comments to the press, Meta representatives stressed the API is meant to serve businesses and that new rules help ensure the API serves tens of thousands of companies building those experiences.

The counterarguments​

Industry observers and competing AI vendors see a strategic dimension to the change. By restricting third‑party LLMs and reserving the messaging surface for Meta’s own AI offerings, critics argue Meta is tilting the playing field in favor of its in‑house generative AI stack. That friction has quickly escalated into regulatory scrutiny in Europe: competition authorities have opened investigations into whether Meta’s policy unfairly disadvantages rival AI providers. Several outlets report that the EU’s antitrust bodies are examining the policy change as a possible abuse of dominant market position.

What Meta actually permitted​

Importantly, the new language does not ban AI from WhatsApp entirely. It preserves the use of AI when it is incidental to a business workflow — for example, an airline using AI to auto‑triage support tickets or a retailer sending AI‑assisted shipping updates. The line between “incidental” and “primary” remains where most disputes will land. That ambiguity gives Meta discretion to interpret and enforce the rule on a case‑by‑case basis, creating uncertainty for developers building borderline services.

Who is affected — and how severely​

Consumers​

For individual users who adopted Copilot by adding it as a WhatsApp contact, the impact is primarily convenience and continuity. Messaging Copilot like any other contact was simple and required no separate app install or sign‑in. After January 15, 2026, that convenience vanishes; users will need to install Copilot’s mobile app or use the web version to continue chatting. Users who want to keep a record of their WhatsApp Copilot chats must export them before the deadline because automatic migration is not supported.

Small businesses and developers​

Small businesses and startups that used WhatsApp as an easy distribution surface for AI‑driven customer experiences face real migration costs. The Business API’s low friction allowed many operators to reach users without developing native apps or authenticated account systems. Those services must now either:
  • Re-architect as authenticated, account‑backed experiences on web or native apps,
  • Move to alternative messaging platforms with more permissive policies, or
  • Narrow their AI functionality to be incidental to a larger business workflow to remain compliant with WhatsApp’s carve‑outs.

Large vendors and platforms​

Major vendors — Microsoft, OpenAI, Perplexity, and others — have already signaled they will comply and migrate users off WhatsApp in the months leading up to the enforcement date. For platform owners and cloud providers, the bigger strategic implication is that distribution strategies have become brittle: platform policy can invert go‑to‑market assumptions rapidly, pushing vendors to invest more heavily in first‑party surfaces and authenticated identity models.

Technical and product implications for Copilot and Windows​

Why the WhatsApp integration was limited​

Copilot’s WhatsApp deployment was, by design, a lightweight contact model: it allowed quick Q&A and short interactions but did not provide the full authenticated experience available in Microsoft’s own apps. That model limited feature parity — things like persistent memory tied to accounts, secure access to enterprise data, and advanced multimodal inputs were constrained or impossible in the WhatsApp surface. Microsoft argues the move off WhatsApp will enable a richer, more secure Copilot experience on Windows and other Microsoft‑controlled surfaces.

The push to authenticated, account‑backed experiences​

Industrywide, there is a clear migration to surfaces where vendors control identity, data retention, and richer modalities. Authenticated experiences enable:
  • Persistent, searchable conversation history associated with a user account,
  • Tighter enterprise data protections and compliance controls,
  • Rich multimodal features such as voice and vision that require enhanced permissioning,
  • Better monetization and telemetry control for vendors.
For Microsoft, consolidating Copilot usage on its own surfaces supports those product goals. For users, it means a trade‑off: more features and security in exchange for the inconvenience of installing and signing into a new app.

Legal and competition risks — the EU response​

Antitrust scrutiny​

Regulators in Europe have moved quickly. The European Commission and several national regulators opened formal inquiries into whether Meta’s policy change constitutes an abuse of dominance by limiting rival AI providers’ access to WhatsApp’s vast user base. The probe examines if the new rules unfairly favor Meta’s in‑house AI by denying access to third‑party chatbots that previously used the Business API as a distribution channel. Early reporting indicates the investigation is active, and the legal risk to Meta is material given its market position.

Enforcement and fines​

If regulators conclude the policy sterically disadvantages competition, Meta could face interim measures or fines. Antitrust fines for large digital incumbents can be substantial, and enforcement could require Meta to adjust policy language or create carve‑outs that preserve neutral access for non‑Meta AI providers. For vendors, the ongoing inquiry underscores that platform policy shifts can produce regulatory consequences that extend beyond product and operational planning.

What users and admins should do now — short checklist​

  • Export WhatsApp chat history you want to keep before January 15, 2026. WhatsApp’s export tool can create a plain‑text archive and optionally include media; exported files are archival and are not importable into Copilot’s account history.
  • Install or update the Copilot mobile app on iOS or Android and sign in with your Microsoft account to get an authenticated experience and persistent history.
  • Test Copilot on the web (copilot.microsoft.com) and on your Windows devices to confirm settings, features, and any subscription requirements.
  • If you relied on Copilot inside WhatsApp for business workflows, inventory those automations and plan a migration: re‑implement as authenticated bots, place logic behind company‑controlled webhooks, or move to alternative messaging platforms.
  • For organizations subject to records retention or compliance, store exported chat archives in your corporate records systems and update processes to avoid data loss.

Alternatives and workarounds​

  • Use Copilot’s native mobile and web apps for full feature access and authenticated history.
  • For businesses needing in‑chat automation on WhatsApp, reframe features to be incidental AI (automated confirmations, structured responses) rather than primary, general‑purpose assistants to remain compliant with the policy.
  • Explore other messaging platforms with different policies (for example, Telegram or proprietary in‑app experiences) but beware of fragmentation and user adoption trade‑offs.

Strengths and weaknesses of the policy change — critical analysis​

Strengths (platforms and businesses)​

  • Predictability for enterprise customers: By refocusing the Business API on transactional, enterprise use cases, WhatsApp reduces the operational unpredictability introduced by open‑ended LLM traffic. This helps enterprises relying on stable throughput and moderation guarantees.
  • Operational control for Meta: The policy lets Meta manage capacity, abuse mitigation, and moderation across WhatsApp’s infrastructure in a way that aligns with its commercial model. That control can reduce unexpected cost spikes tied to LLM workloads.

Weaknesses and risks (competition, users, vendors)​

  • Risk of reduced competition: Removing third‑party distribution channels can tilt the landscape toward native Meta AI offerings and limit competitive choices for users and businesses. That structural effect is precisely why regulators in Europe have opened probes.
  • User friction and fragmentation: For many users, the WhatsApp contact model was convenient because it required no separate app or sign‑in. Forcing a migration to native apps increases friction and may slow adoption of AI features.
  • Ambiguity in enforcement: The policy’s reliance on Meta’s discretion to define “primary functionality” invites uncertainty for developers. Borderline services will face arbitrary or inconsistent enforcement decisions unless Meta clarifies guardrails.

Unverifiable or disputed claims — cautionary notes​

  • Microsoft and other vendors have stated that Copilot’s WhatsApp deployment reached “millions” of users. While the companies report broad adoption, independent verification of exact user counts and usage patterns has not been published; treat quantitative adoption figures as vendor‑reported and therefore indicative but not independently verified.

Broader lessons for the AI distribution era​

Platform policy is now a first‑class constraint in the architecture of conversational AI. The WhatsApp case shows that distribution strategies built on third‑party surfaces can be fragile: a single contract or terms change can remove an entire channel overnight. Companies seeking resilience should prioritize:
  • Account‑backed identity and portable conversation history,
  • Multi‑surface availability (native apps, web, OS integrations),
  • Clear legal and compliance strategies to anticipate platform policy shifts.
For users, the era of single‑tap convenience on third‑party messaging surfaces is giving way to a more fragmented but feature‑rich environment where identity and data portability matter more than ever.

Final takeaways​

  • Copilot will stop functioning on WhatsApp on January 15, 2026; Microsoft has advised users to migrate to Copilot’s mobile apps, the web, or Windows and to export WhatsApp chat histories if they want to keep them.
  • WhatsApp’s Business API update draws a firm line between business‑centric automations and general‑purpose AI assistants, privileging the former and disallowing the latter as primary uses.
  • The decision has attracted regulatory attention in Europe, where competition authorities are probing whether Meta’s policy change raises antitrust concerns by favoring its own AI offerings.
  • Users and businesses should act now: export chat histories they want to keep, install Copilot’s native apps or test the web experience, and plan any necessary migrations for business workflows that relied on WhatsApp as a distribution channel.
The Copilot‑on‑WhatsApp experiment illustrated how quickly convenience can collide with platform economics, infrastructure realities, and regulatory scrutiny. January 15, 2026 is a hard deadline for this chapter; what follows will be defined by where AI vendors choose to invest — native experiences under their control, or alternate, more permissive distribution channels — and by whether regulators force a recalibration of the new rules.
Source: Windows Central Copilot users on WhatsApp, brace yourselves: Support ends mid‑January 2026
 

Click to expand...
Illustration of a smartphone with chat bubbles and a friendly robot, labeled AI PROVIDERS.
WhatsApp will remove general‑purpose AI chatbots — including ChatGPT and Microsoft Copilot — from its platform on January 15, 2026, after a quiet October policy update that bars “AI Providers” from using the WhatsApp Business Solution when the AI is the primary functionality being offered.

Background / Overview​

In mid‑October 2025 WhatsApp updated its Business Solution terms to add a new “AI Providers” restriction that broadly defines and prohibits the use of large language models, generative AI platforms, and general‑purpose AI assistants as a primary product through the Business API. The enforcement date for that change is January 15, 2026, and the language gives Meta (WhatsApp’s owner) wide discretion to judge what counts as an AI Provider or as “primary” functionality. Major AI vendors and services that had been using WhatsApp as a zero‑friction distribution surface — notably OpenAI’s ChatGPT and Microsoft’s Copilot — have confirmed they will discontinue WhatsApp integrations when the policy takes effect. Microsoft’s Copilot team posted a migration notice telling users Copilot will stop functioning on WhatsApp after January 15, 2026, and OpenAI’s help documentation gives the same cutoff while offering linking and migration options for ChatGPT users. This change does not ban AI functionality on WhatsApp entirely. The Business Solution update keeps a clear carve‑out for task‑specific, business‑incidental automation — for example order confirmations, delivery tracking, and limited customer‑service agents — while cutting off consumer‑facing, multipurpose assistants that operate like standalone chat products.

What WhatsApp actually changed (technical summary)​

  • The Business Solution terms now contain an “AI Providers” clause that names “providers and developers of artificial intelligence or machine learning technologies, including but not limited to large language models, generative artificial intelligence platforms, general‑purpose artificial intelligence assistants…” and forbids their use of the Business Solution “when such technologies are the primary (rather than incidental or ancillary) functionality being made available for use.”
  • The effective enforcement date is January 15, 2026. Existing integrations built on the Business API that deliver open‑ended conversational AI must wind down by that date.
  • The policy preserves the API for predictable, business‑oriented automations and explicitly excludes consumer‑facing assistants that rely on WhatsApp as a distribution channel. That line is short in words but broad in effect because the policy leaves “primary functionality” subject to Meta’s judgment.

Why WhatsApp made the change — three defensible explanations​

1) Infrastructure, safety and moderation strain​

WhatsApp’s public justification focuses on the platform being designed for business‑to‑customer workflows, not for the heavy, open‑ended conversational loads produced by general‑purpose LLM assistants. Long, context‑heavy sessions and multimodal payloads increase message volumes, moderation workload, and operational complexity on a scale WhatsApp did not anticipate. The company has said that chatbots running at scale put strain on systems built for transactional flows. From a safety standpoint, general LLMs can produce hallucinations, unsafe advice, or convincing but unverified claims inside private chats that are difficult for platform owners to monitor and moderate proactively. By narrowing the Business API’s permitted uses, WhatsApp reduces the surface area for those unpredictable, private‑chat risks. Several industry reporters and security analysts point to these operational concerns as core parts of WhatsApp’s rationale.

2) Data‑handling and regulatory pressure​

WhatsApp handles highly sensitive communications and operates across jurisdictions with stricter data‑protection rules than in the past. Allowing large third‑party AI systems to ingest private conversations adds layers of cross‑border data transfers and uncertain processing flows that regulators view skeptically. Tightening who can run AI through the Business API simplifies WhatsApp’s compliance posture by limiting third‑party access to message content and reducing ambiguous data flows. This regulatory angle is repeatedly cited in reporting and in public comments from both WhatsApp and European regulators.

3) Strategic product and competitive positioning​

Meta has been building Meta AI as a first‑party assistant across its apps and appears to be consolidating the in‑chat assistant experience under its own services. By closing the Business API as a distribution channel for rival consumer LLMs, WhatsApp effectively reserves in‑app assistant real estate for Meta’s own AI products while allowing narrow, predictable business bots to continue. That alignment raises natural competition concerns and is one of the reasons regulators in Europe launched a formal investigation. This competitive interpretation is supported by multiple outlets, though motives internal to Meta are not disclosed and remain, in part, speculative. Note on interpretation: Meta’s motives combine engineering, safety, privacy and business strategy. While technical strain and moderation are plausible drivers (and are the company’s stated reasons), any claim that the move is exclusively anti‑competitive should be treated as an informed but unverified interpretation.

The regulatory response: competition authorities move quickly​

European regulators have taken this policy change seriously. The European Commission opened an antitrust investigation into Meta’s WhatsApp AI restrictions, asking whether Meta’s policy could unfairly foreclose rival AI providers while allowing Meta AI to remain accessible in‑app. The probe covers the EEA (excluding Italy, which has separate proceedings) and examines whether Meta’s conduct could harm competition in the emerging AI marketplace. Reuters and other international outlets reported the investigation, and European competition officials framed it as necessary to prevent potential dominance abuses. Italy’s competition authority has also been scrutinizing Meta’s moves; national authorities in Europe have already acted to evaluate interim measures because the stakes involve the shape of competition for an entire class of AI services on a dominant messaging platform. These regulatory developments make the policy shift more than a product decision — it is now the subject of legal and political review.

Immediate consequences for users and businesses​

For everyday users (consumers, students, freelancers)​

  • Chat contacts that pointed to ChatGPT, Copilot or similar assistants via WhatsApp will stop responding after January 15, 2026. Vendors have issued migration instructions and recommended alternatives. Microsoft specifically told users to move to the Copilot web and mobile apps and to export chats if they want to retain records because the WhatsApp integration did not authenticate sessions to Copilot accounts. OpenAI likewise encourages account linking to preserve history inside ChatGPT’s ecosystem.
  • Users who relied on WhatsApp versions of these assistants for quick drafting, study help, or day‑to‑day problem solving should prepare to transition to the vendors’ native apps (ChatGPT app, Copilot app), the web, or other messaging platforms that remain supported. Export or link conversations before the deadline if preservation is important.

For small businesses and customer‑service teams​

  • Companies using AI as part of transactional flows (e.g., booking confirmations, delivery updates, triage bots) can continue to use AI through the Business API so long as AI remains ancillary to a defined business function. The policy explicitly aims to preserve those use cases. Businesses that used WhatsApp as the front end for consumer‑facing assistants must rearchitect: options include moving to authenticated web apps, integrating AI into business‑owned apps, or limiting bot behaviors to the permitted transactional scope.
  • Enterprises that built deep automation around open‑ended chat will face nontrivial migration work: replacing the front end, ensuring authentication, re‑wiring analytics and compliance (data retention and deletion), and retraining support staff. The policy’s short enforcement window compresses timelines and increases the risk of rushed migrations.

Technical detail: why conversations won’t port automatically​

A key friction point is authenticity and portability. Many WhatsApp chatbot integrations used the simple contact model: users message a phone number and receive replies, but sessions were not tied to vendor account credentials. Because those sessions were unauthenticated, vendors cannot automatically lift WhatsApp threads into their own server‑side conversation histories or account systems. Microsoft explicitly warns that Copilot WhatsApp chats are unauthenticated and therefore cannot be migrated automatically; users who want to keep them must export threads using WhatsApp’s export tools. OpenAI’s account‑linking option for 1‑800‑ChatGPT is designed to attach future and (if linked before the deadline) prior WhatsApp conversations to a ChatGPT account — but that is an opt‑in path and still requires action by the user. Practical takeaway: assume there is no seamless technical migration for most WhatsApp LLM conversations. Export important threads now or link accounts where vendors provide that option.

What to do now — a concise migration checklist​

  1. Export: Use WhatsApp’s built‑in chat export tools on any conversation you want to save as a local record. This is the single most important immediate step for users who need continuity.
  2. Link accounts: If using ChatGPT’s WhatsApp integration and you want conversations to appear inside ChatGPT history, follow OpenAI’s account‑linking instructions before January 15, 2026.
  3. Install native apps: Download and sign in to vendor first‑party apps — ChatGPT, Copilot — and set up your profile so you retain access and obtain authenticated history going forward.
  4. Rebuild business flows: If your organisation used an open‑ended assistant on WhatsApp as the primary touchpoint, plan to migrate to an authenticated channel (web, private app, or permitted Business API workflows) and update privacy notices and data flows.
  5. Reassess risk and compliance: Revisit your data‑processing agreements, cross‑border transfer mechanisms, and retention policies now that the distribution channel will change. Legal and privacy teams should document migration plans.

How this reshapes the AI distribution landscape​

Meta’s policy closes a zero‑install distribution channel that many AI startups and services used to reach billions of users easily via a phone contact. That change matters for the following reasons:
  • Reduced serendipitous discovery: Finding an AI assistant by messaging a WhatsApp number was frictionless; vendors now must rely more on app stores, web search, and platform‑specific integrations. That increases distribution costs for startups.
  • Favors authenticated, account‑backed experiences: First‑party apps and web portals can offer persistent history, subscriptions, multimedia capabilities, and richer moderation controls. Vendors will invest more in authenticated user relationships.
  • Raises competition questions: The move effectively gives Meta’s own assistant privileged in‑app access while excluding rival consumer LLMs from the WhatsApp Business surface. That asymmetry triggered the EU’s antitrust inquiry and will likely push debates on where and how dominant platforms should be allowed to gatekeep emerging services.

Regional impact: why countries like Nigeria notice this more​

WhatsApp is a central communications hub in many countries across Africa, Latin America, South Asia and beyond. In markets where WhatsApp is the default messaging platform for everyday life, closing a low‑friction AI distribution path is highly visible and disruptive.
Local outlets reported immediate concern among students, freelancers and small businesses that used ChatGPT and Copilot inside WhatsApp for drafting, quick answers, and small‑business support. The Pulse Nigeria coverage distilled the local viewpoint: many Nigerians relied on in‑chat assistants for everything from study help to fast drafting, and the policy change therefore has immediate social and economic friction. Local reactions emphasise usability loss as much as a technical migration problem. Caveat: precise user‑level metrics (how many users accessed an assistant via WhatsApp in any specific country) are not publicly available in granular form, so the country‑level impact should be viewed through qualitative reporting and sector indicators rather than exact adoption numbers.

Risks, trade‑offs and unanswered questions​

  • Risk of fragmentation: For users, the split between in‑app assistants and vendor apps increases fragmentation — conversations, history, and feature sets will live in different places unless vendors build portability tools. That erodes the convenience that made WhatsApp a popular AI entry point.
  • Business disruption risk: Enterprises that built WhatsApp‑first experiences face real technical debt. Short enforcement windows increase the chance migrations are rushed, which can produce compliance gaps and edge‑case failures in customer journeys.
  • Regulatory escalation: The European Commission’s probe may extend beyond fact‑finding and could result in enforcement or remedies that change how tech platforms can tie first‑party AI services to dominant communications infrastructure. Outcomes are uncertain; regulators have not set an end date for the inquiry.
  • Platform discretion and ambiguity: The policy gives Meta broad discretion to interpret “primary functionality.” That ambiguity creates legal and operational uncertainty for developers trying to design compliant bots; appeals and enforcement will clarify boundaries over time. Until then, vendors must assume a conservative approach to what counts as permissible.
Note on unverifiable claims: public reporting attributes a mix of motives to Meta — operational load, moderation burden, privacy, and strategic competition. While each motive is plausible and supported by some public statements or circumstantial evidence, internal prioritisation at Meta is not publicly documented and should be treated as inferred rather than proven.

The near‑term outlook and scenarios​

  • Short term (next 3 months): Third‑party LLM contacts on WhatsApp will be phased out; vendors will push migration guides and encourage users to move to dedicated apps or web surfaces. Businesses will scramble to preserve transactional bots under the permitted carve‑outs.
  • Medium term (6–18 months): Expect a clearer regulatory stance from the EU investigation. Vendors will improve portability features (account linking, export/import tools), enterprise integrations will move toward authenticated APIs, and some consumer assistants may return in constrained, enterprise‑authenticated forms if allowed.
  • Strategic outcome: The balance between platform control and open distribution will be a contested policy area. If regulators find abuse of dominance, remedies could include forcing equal access or imposing interoperability rules; if not, dominant platforms will continue to shape which AI services can sit inside their messaging services. Either way, distribution channels for AI services will be materially different going forward.

Practical recommendations for WindowsForum readers​

  • Users: Export important chats now, link accounts where vendors offer that option, and install vendor desktop or mobile apps (Copilot on Windows, ChatGPT desktop/app). Avoid relying on ephemeral in‑chat assistants for mission‑critical workflows until you migrate to authenticated surfaces.
  • Developers and startups: Don’t build product reliance on zero‑auth, third‑party messaging contacts as your only distribution channel. Invest in authenticated user flows, account portability, and a multi‑channel strategy so a single platform policy change cannot disable your core product.
  • Businesses using WhatsApp: Validate that your bots are genuinely transactional and ancillary to a broader business workflow. If not, replatform to a compliant channel or prepare to run on approved Business API patterns that include authentication, consent, and clear data governance.

Conclusion​

WhatsApp’s October 2025 Business Solution update and the January 15, 2026 enforcement date mark a meaningful turning point in how conversational AI is distributed. The policy forces a migration from zero‑install, privacy‑ambiguous chat contacts to authenticated, vendor‑managed surfaces or tightly scoped business bots. That shift reduces some operational and safety headaches for WhatsApp but raises strategic, competitive, and regulatory issues that will unfold over the coming months.
For users and organisations, the rule change is less an end for ChatGPT or Copilot than a migration challenge: preserve what matters today, move to authenticated apps and web experiences, and design future AI deployments with clear consent, identity, and data portability in mind. The broader question — whether dominant platform owners should be able to privilege their own AI services inside messaging apps — is now in regulators’ hands and will help determine the balance of power between platforms and the growing ecosystem of AI providers.
Source: Pulse Nigeria ChatGPT and Copilot Will Stop Working on WhatsApp in January
 

Courtroom scene where interim measures in a tech case involve WhatsApp and Meta logos.
Meta will face a closed‑door hearing in Rome this week to contest a move by Italy’s antitrust regulator to temporarily block WhatsApp’s new contractual rule that, in the regulator’s view, would exclude competing AI chatbots from the messaging platform — a rapid escalation in a dispute that crystallises the collision between platform governance, competition law, and the economics of conversational AI.

Background​

What happened and why it matters​

In mid‑October 2025 WhatsApp updated the terms governing the WhatsApp Business Solution (commonly called the Business API), adding an “AI Providers” restriction that prevents providers of general‑purpose large language‑model assistants from using the Business API when those assistants are the primary functionality offered through the integration. WhatsApp set an enforcement date of January 15, 2026, prompting major AI vendors to announce migration plans and sparking concern among regulators.
The Italian Competition Authority (Autorità Garante della Concorrenza e del Mercato, AGCM) expanded an existing probe into Meta and opened a fast‑track procedure to consider interim measures because it believes the new terms — coupled with Meta’s growing deployment of Meta AI inside WhatsApp — could exclude competitors from an important discovery and distribution channel and may amount to an abuse of a dominant position under EU competition law. The AGCM formally recorded its decision to open precautionary proceedings on November 26, 2025.

The legal frame: Article 102 TFEU and interim relief​

AGCM’s legal theory rests mainly on Article 102 of the Treaty on the Functioning of the European Union (TFEU), which prohibits firms in a dominant position from abusing that position to exclude rivals. The authority argues the October 15 contractual change and functional embedding of Meta’s own assistant in WhatsApp create switching costs and user habituation risks that could cause “serious and irreparable” harm to competition. To prevent such harm while the full investigation proceeds, AGCM invoked the domestic procedure for interim measures under Italian law. Interim measures are exceptional: regulators must demonstrate urgency, a prima facie case of infringement, and the prospect of irreparable harm. If adopted, an interim order would temporarily suspend enforcement of the disputed contractual clauses, preserving the pre‑existing status quo for third‑party AI providers on WhatsApp while the substantive probe continues.

Timeline of the dispute​

  • October 15, 2025 — WhatsApp updates Business Solution terms to add an “AI Providers” restriction and sets an enforcement date of January 15, 2026.
  • July–November 2025 — AGCM opens and broadens an investigation into Meta’s integration of AI into WhatsApp.
  • November 26, 2025 — AGCM opens precautionary proceedings to consider interim measures.
  • December 2025 — Meta scheduled to attend a closed‑door hearing in Rome to contest the AGCM’s interim measures procedure.
These dates matter because they show the regulator’s speed: within weeks of the contract change AGCM moved from investigation to seeking urgent, temporary relief — a sign that authorities perceive a risk of near‑term competitive harm.

The parties and what they say​

Meta / WhatsApp​

Meta has publicly defended the change, saying the Business API was never intended to host open‑ended LLM chat sessions and that allowing such usage at scale would strain infrastructure and moderation systems. WhatsApp argues the rule protects the integrity of a service designed for transactional, authenticated enterprise messaging rather than mass, unauthenticated LLM interactions. Meta stresses that standard enterprise uses — customer support, notifications and commerce messaging — remain unaffected.

AGCM​

AGCM frames the change as a potential exclusionary strategy that could consolidate distribution and data advantages in favour of Meta’s own assistant. The authority explicitly flagged the risk that users — especially in a market where switching costs are high and habits form quickly — could be steered toward Meta AI, undermining contestability in the nascent AI chatbot market. AGCM’s press materials and decision text underline concerns about market access and technical development being restricted by contract.

Third‑party AI providers​

Major third‑party assistants that were available in‑thread on WhatsApp — notably Microsoft Copilot and OpenAI’s ChatGPT — announced plans to discontinue their WhatsApp integrations or redirect users to first‑party apps, citing non‑migratability of unauthenticated sessions and the need to protect account‑backed conversation histories. Smaller startups warned that losing WhatsApp as a low‑friction discovery channel would materially increase customer‑acquisition costs and jeopardise business models that relied on viral, in‑chat distribution.

Why regulators moved fast: the economics and risks​

Distribution matters in AI​

WhatsApp is one of the world’s largest messaging platforms. For conversational AI, being present where users already talk — in the same chat surface — reduces friction, increases trial rates, and accelerates signal collection that can be used to improve models. Denying access to that channel during early adoption can materially weaken rivals’ ability to build user bases, accumulate training data, and iterate. AGCM flagged those network and data effects as central to the urgency of interim relief.

Lock‑in and switching costs​

Conversational AI creates contextual history and personalization over time. Users who begin using an assistant inside WhatsApp might get habituated to its convenience; migrating to a competing assistant requires explicit re‑authentication and friction that reduces switching. Regulators see this behavioural inertia as a pathway to rapid, perhaps irreversible, market concentration — just the sort of harm interim measures are designed to prevent.

Safety and infrastructure claims are plausible — but not dispositive​

Meta’s operational arguments are not fanciful. Handling unauthenticated, open‑ended LLM dialogues at scale within a messaging API designed for enterprise notifications plausibly increases moderation burdens and raises reliability concerns. That said, the technical burdens can sometimes be mitigated by narrower, less‑restrictive measures: rate limiting, dedicated LLM tiers, quota systems, templated responses, or authenticated session requirements. Regulators will scrutinise whether Meta’s chosen contractual route was the least restrictive way to address genuine operational risks.

Legal strengths and weak points for each side​

AGCM’s strengths​

  • Recent EU case law has made refusals to grant access to platform features more actionable, especially where the platform was built for third‑party use. This strengthens the regulator’s legal footing.
  • The authority can point to concrete, short‑term harms — loss of distribution, startup displacement, and user lock‑in — that justify urgent interim relief.

AGCM’s challenges​

  • The regulator must prove urgency and a prima facie infringement quickly. That is a high bar for interim relief.
  • If Meta can demonstrate credible, less‑restrictive technical alternatives that achieve the same safety goals, the necessity argument for a full reversal weakens.

Meta’s strengths​

  • Operational legitimacy: platform operators often have a defensible interest in prescribing how infrastructure is used, especially where abuse or severe service degradation is plausible. Meta’s system‑integrity argument resonates with engineering realities.
  • Remedies that impose technical constraints can be engineered without wholesale reopening of the Business API if a regulator seeks to preserve safety while ensuring contestability.

Meta’s exposure​

  • The timing and design of the contractual change — coincident with a broader push to surface Meta AI across WhatsApp — can be read as strategic foreclosure. That narrative is politically and legally potent.

Practical impact on businesses, users and startups​

  • Millions of WhatsApp users in Italy and across Europe face service disruption if third‑party assistants are cut off and vendors migrate users to native apps. AGCM estimates WhatsApp serves tens of millions in Italy alone, underlining the material scope.
  • Enterprises using AI assistants for customer support need to audit flows: if a third‑party assistant is the primary interface, the Business API change could force re‑architecting to authenticated, account‑backed experiences or shifting to alternative platforms.
  • Startups that relied on WhatsApp as a discovery and acquisition funnel face higher costs and structural risk; some may fail to survive the migration.

Technical options that could have reduced conflict​

Regulators will evaluate whether Meta had less‑restrictive, proportionate technical solutions available. Viable alternatives to an outright exclusionary clause include:
  • Rate limiting and quotas for LLM interactions to protect API stability.
  • A dedicated LLM traffic tier with separate SLAs and pricing.
  • Mandatory authentication and account linking before chat history is tied to a model — enabling portability and recovery of histories.
  • Template‑based moderation filters or sandboxed LLM endpoints for sensitive categories.
  • Transparent, audit‑friendly logs and data‑use commitments for conversational content used in model training.
These remedies would preserve safety while reducing the competitive foreclosure effect that AGCM highlighted. Whether such options were operationally feasible or economically attractive to Meta will matter in the hearing.

What to expect at the hearing — and next steps​

The closed‑door hearing in Rome will focus on whether AGCM can establish the urgency and prima facie case required for interim measures. Meta, AGCM investigators, and rival chatbot services are expected to present technical evidence, expert testimony and business impact statements. If AGCM imposes interim relief, enforcement of the contested clause would be suspended, preserving third‑party integrations while the substantive probe continues. If AGCM declines interim relief, the January 15, 2026 enforcement timetable remains live and vendors will have to execute migration plans. Likely procedural outcomes include:
  1. AGCM grants interim measures, freezing enforcement and giving rivals breathing space.
  2. AGCM denies interim relief, allowing Meta’s enforcement schedule to proceed while the substantive investigation runs.
  3. AGCM issues a limited, engineering‑focused directive (e.g., requiring non‑discriminatory access terms or technical APIs for competitors).
    Each path has major strategic consequences for Meta and the wider conversational‑AI ecosystem.

Broader regulatory ripple effects​

This case will be watched closely across Europe and beyond as a precedent on platform gatekeeping in the age of generative AI. It intersects with multiple regulatory regimes:
  • EU competition law and Article 102 TFEU.
  • Ongoing EU policy work on platform gatekeepers and the Digital Markets Act, which addresses structural obligations for dominant platforms.
  • Data‑protection and AI‑transparency rules, where transfer of conversational data into model training raises privacy and consent questions.
A strong enforcement action by Italy could encourage other national enforcers or the European Commission to pursue parallel remedies; conversely, a narrow technical fix would signal regulators are willing to accommodate safety trade‑offs through engineering solutions rather than structural remedies.

Recommendations for enterprise IT leaders and developers​

Practical, prioritized steps for organisations that rely on WhatsApp for customer engagement:
  1. Map all WhatsApp integrations and identify where third‑party general‑purpose assistants are the primary interface.
  2. Export any mission‑critical chat histories and customer records that may not migrate automatically if integrations end.
  3. Build contingency plans: evaluate migration targets (first‑party apps, web clients, alternative messaging platforms, or authenticated account channels).
  4. Test Meta AI and rival assistants for parity on key workflows to assess functional gaps and business impact.
  5. Budget for engineering work to re‑architect conversational flows to authenticated, account‑backed sessions where portability and durability matter.
These steps reduce exposure to abrupt cutoffs and preserve the ability to shift channels if platform rules change.

Risks and caveats — what is not yet certain​

  • The AGCM’s legal assessment that WhatsApp is dominant in the relevant market is fact‑intensive and contestable. Market definition can swing outcomes.
  • Whether Meta’s operational constraints genuinely required an exclusionary clause or could have been addressed technically remains disputed and will hinge on engineering evidence presented at the hearing.
  • Any discussion of potential fines or structural remedies at this stage is speculative; those outcomes would require a finding of infringement after the full administrative process. Readers should treat predictions about fines or business‑critical remedies as contingent on procedural developments.

The strategic stakes: platform power, data and distribution​

At its core this dispute is about how much control dominant platforms should retain over distribution and the data that flows across them. If a platform operator can lawfully carve out a major distribution channel for its own model, the commercial consequences for rivals are profound. Conversely, if regulators can force a dominant platform to maintain open channels for third‑party assistants, that outcome will shape where conversational AI lives — in broad distribution surfaces or in vertically integrated, authenticated apps. Either scenario reconfigures competitive dynamics in machine intelligence, user data flows, and product distribution.

Conclusion​

The Rome hearing is more than a procedural pause; it is an early, decisive test of how competition law will govern platform behaviour in the AI era. AGCM’s expedited approach reflects a view that the early distribution phase for conversational AI is especially sensitive to exclusionary conduct. Meta’s response will seek to translate genuine operational constraints into legally defensible platform policy. The outcome will determine not only whether ChatGPT, Copilot and similar assistants can remain in‑thread on WhatsApp in Italy in the near term, but also whether regulators are prepared to routinely use interim measures to preserve contestability in nascent AI markets. This clash unites engineering trade‑offs with high‑stakes regulatory judgement: where one side frames the issue as safety and system integrity, the other frames it as strategic foreclosure. The hearing in Rome — and the decisions that follow — will signal whether Europe will prioritise open distribution to nurture competitive AI ecosystems or accept platform‑level consolidation justified by operational imperatives.
Source: MLex Meta to face Italian antitrust enforcer in interim measures hearing | MLex | Specialist news and analysis on legal risk and regulation
 

Meta will appear at a closed‑door hearing in Rome this week to contest the Italian antitrust authority’s move to seek interim measures that would effectively freeze WhatsApp’s new policy restricting third‑party AI chatbots — a fast‑moving enforcement action that crystallises how competition law, platform governance and the economics of generative AI collide.

A futuristic Italian courtroom with holographic screens displaying a blue infinity logo and two lawyers.Background​

WhatsApp updated its Business Solution (commonly called the Business API) on 15 October 2025 to add an “AI Providers” restriction that, in practical terms, bars developers of general‑purpose large language model assistants from using the Business API where those assistants constitute the primary functionality of the integration. The update set an enforcement date of 15 January 2026 for affected integrations. The Italian Competition Authority (Autorità Garante della Concorrenza e del Mercato, AGCM) has interpreted the change as potentially exclusionary and, on 26 November 2025, opened precautionary proceedings to consider interim measures under domestic competition law. The AGCM’s press note frames the concern sharply: the regulator believes the October contractual change coupled with Meta’s increasing embedding of its own assistant inside WhatsApp could limit production, market access or technical developments in the nascent AI chatbot market and may amount to an abuse of a dominant position under Article 102 TFEU. The authority says such behaviour risks causing “serious and irreparable” harm through rapid user habituation and switching costs. This administrative escalation has practical consequences. Several major assistants that were available in‑thread on WhatsApp — notably Microsoft Copilot and OpenAI’s ChatGPT integrations — signalled plans to discontinue those in‑app experiences and to migrate users to first‑party apps and authenticated surfaces, citing the new Business API language and the non‑migratability of unauthenticated session histories. The prospect of an abrupt cutoff has prompted the Italian regulator to seek an urgent, temporary order to preserve the status quo while a full probe proceeds.

Why Italy moved fast: legal tools and urgency​

The legal framework​

The AGCM’s precautionary move rests on a well‑worn EU competition axis: Article 102 TFEU prohibits firms in a dominant position from abusing that dominance to exclude rivals. Italian law provides a domestic mechanism for interim measures (Section 14‑bis of Law 287/1990) to prevent irreparable harm while the administrative fact‑finding continues. To obtain interim relief, the authority must show urgency, a prima facie case of infringement, and the prospect of serious and irreparable harm that cannot be rectified later.

Why the AGCM sees urgency​

Two practical features make the AGCM’s rush credible. First, messaging platforms are powerful distribution surfaces; in‑thread assistants enjoy near‑zero friction because they meet users where they already communicate. Cutting off access at an early adoption stage can cripple challengers’ ability to build user bases and collect usage signals. Second, Meta has been surface‑level integrating Meta AI throughout WhatsApp, increasing the risk that users will quickly migrate to a default assistant that is natively discoverable inside the app. Regulators argue these dynamics can produce rapid, hard‑to‑reverse lock‑in — the very kind of harm interim measures are designed to prevent.

What exactly changed in WhatsApp’s terms​

  • The Business Solution terms introduced on 15 October 2025 define “AI Providers” to include creators and operators of large language models, generative platforms and general‑purpose assistants.
  • The terms prohibit those providers from using the Business API when the assistant is the primary (rather than incidental) functionality delivered through that integration.
  • Meta retains discretion to determine whether a given integration falls within the prohibition.
  • The rule’s practical enforcement date was set for 15 January 2026, creating a narrow window for vendors and enterprises to respond.
These are contract changes rather than code alterations — but the line between contractual governance and structural foreclosure is exactly what competition authorities scrutinise when the platform operator is dominant in a channel that rivals rely on for distribution.

Who’s affected — real‑world impact​

Consumers and end users​

Millions of WhatsApp users who tried assistants in‑thread stand to lose an effortless way to access third‑party AI. Where interactions were unauthenticated (no account linkage), conversation histories typically cannot be ported to a rival app, meaning users could permanently lose conversational context if an integration is cut off. The AGCM has noted the material scope of the platform — WhatsApp serves tens of millions of users in Italy, a magnitude that feeds the regulator’s urgency analysis.

Large AI vendors​

Major providers signalled pre‑emptive migration plans once WhatsApp published the new terms. Microsoft warned Copilot users that in‑thread, unauthenticated sessions would not migrate and advised exporting history; OpenAI has taken similar steps for ChatGPT integrations. These moves are costly operationally and harmful strategically: firms must rebuild context and user flows on first‑party surfaces where discovery is harder.

Startups and SMBs​

Smaller startups that used WhatsApp as a low‑friction acquisition funnel face higher customer acquisition costs and possible existential risk. Many relied on viral sharing and the chat surface to reach users; losing that channel could blunt growth and increase the capital required to sustain product iteration. Enterprise customers that built support flows around third‑party assistants must audit and potentially rearchitect.

The arguments on each side​

Meta’s defence (public posture)​

  • WhatsApp’s Business API was designed for transactional, authenticated enterprise messaging (customer support, notifications, commerce), not for open‑ended LLM sessions at scale.
  • Allowing unauthenticated, high‑volume LLM interactions could overload infrastructure and create unsustainable moderation burdens.
  • The policy change protects the API’s enterprise purpose and system reliability while leaving standard enterprise uses unaffected.

AGCM and challengers’ theory​

  • The close timing between the contractual change and Meta’s own deployment of Meta AI inside WhatsApp suggests a strategic foreclosure designed to privilege Meta’s assistant and exclude rivals from a powerful discovery surface.
  • The discretion given to Meta to classify “primary” functionality raises concerns about discriminatory enforcement.
  • Cutting third‑party access during the early uptake phase could cause serious and irreparable harm to competition and to consumers’ ability to choose.
Both sides advance plausible narratives: Meta’s systems argument is operationally credible, while AGCM’s competition concern tracks established EU priorities on gatekeeper conduct.

Technical and regulatory trade‑offs: engineering fixes vs structural rules​

Regulators will weigh whether the alleged competitive harm could be mitigated by less‑restrictive technical measures rather than by removing the clause entirely. Possible alternatives that could preserve safety while maintaining contestability include:
  • Rate limiting and quotas for LLM interactions to protect capacity.
  • A separate LLM traffic tier with differentiated SLAs and pricing.
  • Mandatory authentication/account linking before conversation histories are attached to models — enabling portability.
  • Sandboxed endpoints and template‑based moderation to limit risky content without broad exclusion.
  • Transparent logging and data‑use commitments for conversational content used in model training.
These options are not panaceas. They require engineering investment, raise privacy trade‑offs, and may not fully address Meta’s stated moderation and stability concerns. Regulators will need convincing technical evidence to conclude whether those mitigations were feasible and proportionate.

The hearing in Rome: what to expect​

The closed‑door session scheduled for this week is procedural but consequential. AGCM investigators, Meta representatives and rival chatbot services will present factual and technical evidence aimed at the three threshold tests for interim measures: urgency, prima facie case, and irreparable harm.
Possible outcomes include:
  • AGCM grants interim measures — enforcement of the "AI Providers" prohibition would be suspended for the duration of the order, preserving third‑party integrations while the substantive investigation proceeds.
  • AGCM denies interim relief — Meta’s January 15, 2026 timetable stands and vendors must implement migration plans.
  • AGCM issues a narrow, engineering‑focused directive — e.g., require non‑discriminatory access terms, or mandate technical hooks for third‑party assistants under specified safety conditions.
The AGCM must balance immediate market effects against the costs and feasibility of alternative remedies. Even a partial interim order (for example limited to Italian users or to specific classes of integrations) would have outsized strategic impact.

Wider EU and global implications​

This dispute is a bellwether for how competition authorities will treat platform governance decisions in the AI era. The European Commission has already opened a separate formal probe into Meta’s WhatsApp AI policy (excluding Italy, which is running parallel proceedings), signalling multi‑front scrutiny across EU enforcement channels. National authorities elsewhere will watch whether Italy’s expedited approach yields an interim suspension or a narrowly tailored technical remedy — either outcome will influence where conversational AI lives going forward (open distribution surfaces vs vertically integrated, authenticated apps). Beyond competition law, the case intersects with data protection, transparency obligations for AI systems and the evolving Digital Markets Act (DMA) gatekeeper regime. Remedies must therefore navigate not only Article 102 TFEU but also GDPR compliance, AI regulation debates and the DMA’s emerging obligations on interoperability and non‑discriminatory access.

Risks and blind spots in AGCM’s case​

  • Market definition is fact‑intensive: demonstrating WhatsApp’s dominance in a legally relevant market is contestable and can sway outcomes.
  • Operational evidence matters: regulators must rebut Meta’s claims about moderation burdens and infrastructure constraints with credible engineering data or show that less‑restrictive alternatives were available.
  • Remedial complexity: even a successful finding of abuse does not yield a single obvious fix — technical, behavioral and structural remedies each have trade‑offs.
  • Cross‑jurisdiction friction: Meta faces concurrent inquiries and DMA obligations, complicating compliance and appeals.
Where evidence is thin (for example precise capacity and moderation cost figures), regulators risk over‑reaching or granting remedies that are either politically popular but technically ineffective, or technically valid but poorly enforceable.

Practical guidance for WindowsForum readers — IT leaders, platform engineers and product managers​

Enterprises and developers who depend on WhatsApp for customer engagement should prepare now. The attention of competition authorities does not eliminate operational risk; it only affects timing. The steps below offer a defensible, prioritized playbook.
  • Map dependencies. Identify every integration that exposes AI assistants via WhatsApp. Document whether sessions are authenticated and whether conversation histories can be migrated.
  • Export critical histories. For user‑facing assistants operating unauthenticated threads, provide migration guidance and export tools so customers can preserve context before any cutoff.
  • Build portable UX flows. Re‑architect critical experiences to support account linking, cross‑device continuity and web or native app fallbacks. This reduces single‑platform dependence.
  • Engage legal and compliance early. If your business model relies on third‑party distribution surfaces, obtain regulatory and privacy counsel to assess risks under competition and data‑protection laws.
  • Test fallback channels. Identify and trial alternative distribution channels (SMS, authenticated web chat, official in‑app commerce integrations) and measure conversion economics.
  • Prepare technical evidence. If you are a vendor arguing that a restrictive policy is unnecessary, compile logs, capacity metrics and moderation workload data that demonstrate the viability of less‑restrictive mitigations.
These steps preserve continuity for users and reduce exposure to sudden platform policy shifts.

Strategic consequences for the broader AI ecosystem​

  • If regulators force open access or non‑discriminatory terms, conversational AI could remain distributed across multiple surfaces, preserving a competitive fringe of innovation but raising safety and moderation demands for platforms.
  • If platforms are allowed to lawfully reserve distribution for their own assistants, competitive dynamics will favour vertically integrated incumbents and push challengers toward authenticated, account‑centric distribution models — a strategic shift that raises barriers to entry.
Either outcome reshapes where models collect signals and how personalization is delivered — with implications for advertising, data governance and consumer choice.

Critical appraisal: strengths, weaknesses, and what to watch​

Strengths of AGCM’s position​

  • Timeliness and precedent: EU case law and prior refusals‑to‑deal rulings make platform access denials ripe for scrutiny where exclusion risks market contestability. AGCM’s expedited approach leverages those legal lines effectively.
  • Concrete harm theory: The complaint links contractual change to measurable distribution loss for rivals and higher switching costs for consumers — a familiar and persuasive antitrust narrative.

Weaknesses and open questions​

  • Technical plausibility of Meta’s defence: Meta’s argument that the Business API was not designed for open‑ended LLM sessions is credible on its face — regulators will need strong technical counter‑evidence to show that less‑restrictive measures were feasible.
  • Remedy design challenge: Even if the AGCM wins an interim order, designing enforceable, proportional measures that balance safety and contestability is operationally complex.

What to watch next​

  • Whether AGCM imposes broad interim measures, a tailored directive, or no suspension at all after the Rome hearing.
  • How the European Commission’s separate probe meshes with national proceedings — coordinated enforcement could amplify remedies.
  • The technical record Meta and rivals present — detailed capacity and moderation metrics will play a decisive role.

Conclusion​

The Rome hearing is more than a procedural step — it is an early test of how competition law will regulate gatekeepers’ control over distribution in the AI era. The AGCM’s move to seek interim relief underscores the regulator’s assessment that the early adoption phase of conversational AI is particularly fragile and that platform rules can rewire ecosystems quickly.
For enterprises and developers, the pragmatic lesson is immediate: reduce single‑platform dependence by making conversational experiences portable, authenticated and resilient. For policymakers, the case highlights the hard choices regulators face when balancing consumer safety, platform stability and competitive contestability.
The outcome of this interim hearing will determine whether third‑party assistants keep a crucial distribution channel open while courts consider the merits — or whether incumbents can use contractual governance to reshape where AI assistants live and who benefits from early–stage network effects.
Source: MLex Meta to face Italian antitrust enforcer in interim measures hearing | MLex | Specialist news and analysis on legal risk and regulation
 

Meta will start feeding people’s conversations with Meta AI into the same recommendation systems that decide which reels, posts, and ads appear in users’ feeds — a change Meta says goes into effect on December 16, 2025.

Meta AI concept: social icons and devices on a blue circuit background.Overview​

Meta’s October announcement confirmed a concrete shift: interactions with Meta AI — both text chats and voice conversations — will become a signal used to personalize content and advertising across Meta platforms beginning December 16, 2025. The company told users it would notify them via in‑app banners and email in early October, and emphasized that people can continue to adjust what they see through Ads Preferences and feed controls. This policy is tightly bound to two broader developments: Meta’s push to make AI a first‑party, cross‑platform feature inside Facebook, Instagram, WhatsApp and Messenger, and regulatory scrutiny of how platform owners use privileged distribution to advantage their own services. Both dynamics are already attracting attention from competition watchdogs in Europe and prompting practical migration advice for users and businesses that relied on third‑party assistants inside messaging apps.

Background: where this change came from​

Meta’s product push​

Meta has aggressively integrated its assistant, Meta AI, across multiple surfaces. The company reports more than 1 billion monthly users for its AI features and frames the new policy as an extension of the way the platform already personalizes feeds and ad auctions from standard activity signals (likes, follows, shares). Meta’s public blog explicitly says Meta AI interactions will be “another signal” used to improve recommendations.

Timeline and mechanics​

  • October 1, 2025 — Meta posted a public blog outlining that AI interactions would become a personalization signal and that user notifications would begin in early October.
  • October–December 2025 — Meta sent in‑product notifications and emails to account holders advising of the policy change. This notice window was intended to give users time to review and adjust controls before the change goes live.
  • December 16, 2025 — Policy goes into effect in Most Regions (regional exceptions apply for certain jurisdictions). Meta says interactions with Meta AI on WhatsApp are only used cross‑account if the user has added that WhatsApp account to an Accounts Center.

What’s explicitly covered​

Meta’s announcements and follow‑up reporting make two key points about scope:
  • Types of interaction: Both text exchanges and voice chats with Meta AI are explicitly named as signals for personalization. Meta emphasized that microphone access is only used when the user has granted permission and is actively using a voice feature.
  • Data domains: The change applies to interactions with Meta AI features, not to private one‑to‑one messages or DMs unless a user explicitly shares them with the AI. Meta and independent reporting clarified that private DMs are not being swept into training or recommendation pipelines as part of this update.

What Meta says users will get — and what they should watch for​

Meta’s framing: more relevant experiences​

Meta positions the change as a continuity of current personalization logic: if a user chats with Meta AI about hiking, the platform will treat that interaction similarly to liking a hiking page or posting a reel about trails, and will surface related groups, posts, or ads. Meta emphasizes user controls — Ads Preferences, feed controls, and Accounts Center linking — as ways users can limit cross‑account personalization.

Practical user implications​

  • If you use Meta AI to talk about interests or shopping plans, expect those topics to influence the content and ads you see. That influence can appear quickly because recommendation systems treat signals in near real time.
  • Voice interactions are treated as signals the same way as text. The presence of a microphone indicator and the requirement for explicit permission are procedural safeguards Meta highlights; they do not change that what you say to Meta AI becomes a personalization signal.
  • The policy will roll out with regional exceptions. Reporting identifies the EU, UK and South Korea as jurisdictions with carve‑outs or stricter rules that limit use of AI interactions for ad targeting. Users in those places may see different behavior.

Verification and cross‑checks​

The central claims in Meta’s announcement are corroborated by multiple independent outlets and by Meta’s own newsroom:
  • Meta’s official blog post published in early October states the personalization change and a December 16 effective date.
  • Major news outlets and trade press confirmed the same facts and added contextual reporting about regional exceptions and the timing of user notices.
  • Independent fact‑checkers and platform‑watch outlets pushed back on viral claims that this policy opens private DMs for AI training; those outlets report Meta denies such sweeping access and clarifies the scope to interactions with AI features.
WindowsForum analysis documents collected internally also flagged the linkage between this policy and Meta’s broader strategy to concentrate AI interactions inside its first‑party experiences, a change with potential competitive consequences.

How the change works technically (what to expect under the hood)​

Signals and models​

Recommendation systems at scale take many signals and weigh them in real time or near real time. Interactions with an assistant produce structured events that can be transformed into categorical signals (topics searched, intents expressed, items requested) and fed into ranking models alongside other engagement signals.
  • Short‑term inference: Live interactions may create short‑lived personalization adjustments (e.g., increase the ranking of hiking content after a session about trails).
  • Long‑term profiles: Repeated interactions on the same topics can update persistent interest embeddings that shape ad targeting and content surfacing.

Voice vs text​

Voice sessions introduce particular engineering concerns. Audio must be transcribed and mapped into textual intents; that transcription step creates intermediate data states where privacy controls and retention policies matter. Meta emphasizes that microphones are only active with permission and will display indicators, but the fact of transcription and mapping into topic signals is what matters for personalization.

Data flow and cross‑account linking​

Meta’s Accounts Center is a control point. Interactions tied to accounts within the same Accounts Center can be used across Meta Company Products for personalization; interactions on an unlinked WhatsApp account will not cross to Facebook/Instagram without explicit linking. This split is a technical and legal lever Meta uses to limit default cross‑account signal sharing.

Competition, market power and regulatory risk​

Why this matters to regulators​

Platform owners that control both distribution and the data flows that train personalization systems can structurally advantage their own features. Meta’s policy change intersects with a separate set of rules affecting the WhatsApp Business API and how third‑party assistants access millions of users via messaging channels.
Italy’s competition authority (AGCM) and the European Commission have already opened investigations into Meta’s integration of AI with WhatsApp and changes to Business Solution terms that limit third‑party chatbot access. Regulators argue those contractual terms could foreclose rivals and harm competition; the AGCM broadened an inquiry and has considered interim measures.

The practical competitive outcome​

By directing conversation traffic toward its own Meta AI — and by saying Meta AI interactions will feed ad and content personalization — Meta both enriches its first‑party signal set and reduces the incentive for users to rely on external assistants whose interactions won’t be folded into Meta’s targeting pipelines. That dynamic raises two principal concerns:
  • Tying and foreclosure: If WhatsApp or other surfaces preferentially route users to Meta AI, competitors lose low‑friction distribution. Regulators see this as potentially abusive for dominant platforms.
  • Data concentration: Centralizing assistant interactions inside Meta increases the company’s data advantages for ad personalization and recommendation quality, making it harder for rivals to compete on relevance and utility. Internal analysis at the community level has flagged this consolidation as a strategic move that will accelerate monetization of AI interactions.

Privacy analysis: the tradeoffs and red flags​

What Meta promises​

Meta says it will not scan private messages for AI training as part of this policy; the change applies to interactions with Meta AI features. The company also lists sensitive categories (religion, health, sexual orientation, political views, etc. that it says it will not use for ad targeting even if surfaced in AI conversations. Meta points to Ads Preferences and feed controls as the main user tools to manage personalization.

Why many users will still be uneasy​

  • Implicit retention: Even temporary retention of voice or chat transcripts to convert into topical signals raises questions about retention windows, anonymization, and security. Voice inputs are especially sensitive because they can contain location cues, ambient context, or personally identifiable information. Meta’s statements about permission and indicators are necessary but not sufficient to address retention and reuse concerns.
  • Opaque pipelines: Users are being told that AI interactions will be used to tailor ads, but the system does not make explicit how long signals persist, how they are de‑identified, or whether they are ever used to train underlying models versus only driving real‑time personalization. Those differences matter both for privacy and for regulatory compliance.
  • Ambiguous opt‑outs: Meta points to existing controls but the language is vague on whether users can opt out of having AI interactions used for ad personalization specifically, or only of seeing certain ads. Practical opt‑out mechanisms and clear UX will be critical to avoid regulatory and public backlash.

What independent checks say​

Fact‑checking and platform‑watch reporting have pushed back on viral claims that Meta will scan all private DMs; Meta and other outlets deny that. Still, watchdogs urge caution because systemic changes that aggregate many small signals can produce inferences about people even when individual messages are not directly used for training. This inference risk is a less visible but powerful privacy exposure.

Strengths and the business case (Meta’s perspective)​

  • Improved relevance: AI interactions are richer signals of intent than passive metrics; using them can make recommendations and ads more timely and accurate. Meta argues that this will improve user experience by reducing irrelevant content.
  • Monetization opportunity: Turning conversational AI into a source of signals strengthens ad targeting and creates new inventory/placement opportunities inside AI experiences and daily briefs. Internal analysis flagged this as a major commercial incentive for Meta.
  • Product coherence: Consolidating assistant usage inside first‑party surfaces reduces fragmentation and can improve moderation, safety, and product support. Meta frames its action as an operational necessity to manage scale.

Weaknesses, risks and likely pushback​

  • Regulatory exposure: Antitrust and competition probes in Italy and at the EU level are active and may produce interim measures, fines, or structural remedies if regulators find the policy unlawfully forecloses rivals.
  • User trust erosion: Even if Meta limits use of certain sensitive categories for ad targeting, ordinary users may find the idea of assistant conversations feeding ads disturbing, especially for voice interactions. Poor UX around controls will magnify mistrust.
  • Moderation and safety: Summarizing or surfacing social content using AI increases content‑moderation complexity. Automated summaries can unintentionally amplify misinformation or toxic posts, and using AI signals to prioritize content can create feedback loops that reinforce extreme or manipulative content.

Actionable guidance for Windows users and community members​

  • Review notifications and emails from Meta now. Meta says it began notifications in October and the update takes effect December 16, 2025. If you received an email, follow the links in the in‑product notices to check your settings.
  • Audit how you interact with Meta AI. If you care about limiting personalization, avoid using Meta AI to probe sensitive interests you wouldn’t want reflected in feed recommendations or ads.
  • Use Ads Preferences and feed controls proactively. Meta points to these as the main user controls; invest a few minutes to set explicit ad topics you want to exclude and to toggle content preferences.
  • For WhatsApp users who used third‑party assistants (Copilot, ChatGPT) inside WhatsApp: export any important chat transcripts before platform policy changes around Business APIs force migrations. Several provider notices recommend migrating to account‑backed experiences for portability.
  • If you’re a business: re‑examine any workflows depending on third‑party assistants inside the WhatsApp Business API and prepare re‑platforming plans. Regulatory uncertainty may change distribution rules suddenly.

What to watch next​

  • Whether Meta provides a clear opt‑out specifically for AI‑derived personalization beyond generic ad controls; clarity here will materially affect public reaction.
  • How Italy’s AGCM and the European Commission resolve probes into WhatsApp Business Solution terms and Meta’s AI integrations — interim measures could force changes to distribution or data‑sharing rules.
  • Evidence of differential behavior across regions: Meta’s regional exceptions for the EU, UK and South Korea will create a patchwork of experiences; auditability and transparency of regional behavior should be scrutinized.

Conclusion: pragmatic benefits, real tradeoffs​

Meta’s decision to fold Meta AI interactions into the same personalization pipelines that shape what users see is a logical extension of modern recommender design — richer intent signals generally produce more relevant recommendations. From a product and monetization perspective, the change is defensible and predictable: platforms monetize attention, and better signals improve ad performance. Yet the move also crystallizes the modern tension between utility and control. Users who value convenience will likely appreciate stronger personalization, while users who prioritize privacy and compartmentalization will see an erosion of the implicit boundary between private queries and targeted advertising. Regulatory attention in Europe, and practical fallout for third‑party assistants inside messaging platforms, means this is not merely a design decision but a structural moment for how AI, data, and platform power interact.
For Windows enthusiasts and power users, the immediate path is straightforward: review the notices Meta sends, lock down Ads Preferences where appropriate, export any chat history you consider important, and prefer authenticated, account‑backed assistants if portability and auditability matter. The broader lesson is structural: when platforms control distribution, they can convert product features into strategic data advantages — and regulators and users alike are increasingly alert to the consequences.
Source: VICE Meta Is Going to Start Using Your Interactions to Train Its AI
 

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Copilot on WhatsApp Ends January 15, 2026: Export Chats and Migrate to Microsoft Surfaces
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Copilot Leaves WhatsApp by Jan 15, 2026: What It Means for AI in Messaging
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