ChatGPT Is Now a Very Large Search Engine in the EU: Why Is Online Reputation Management Changing for Brands?

Updated: 3 September 2026 · Category: AI Search Reputation

ChatGPT Is Now a Very Large Search Engine in the EU: Why Is Online Reputation Management Changing for Brands?

On 31 August 2026, the European Commission designated ChatGPT as a Very Large Online Search Engine (VLOSE) under the DSA. This development shows regulatory recognition that users treat generative AI answers as a search layer when researching brands and people.

Contents

Short answer
Why does it matter?
What should companies do?
How should it be measured?
Sources
Frequently asked questions

Short Answer

On 31 August 2026, the European Commission designated ChatGPT as a Very Large Online Search Engine (VLOSE) under the Digital Services Act. The Commission’s designated-services list reports an average of 159.1 million monthly active users in the EU for ChatGPT. This does not mean ChatGPT could search for the first time that day; ChatGPT Search already existed. The change is its formal classification as a very large online search engine within the EU regulatory framework and the activation of VLOSE obligations.

Why Does It Matter?

Brand reputation has long been measured through Google results, news websites and social media mentions. With answer engines such as ChatGPT, users often receive a single synthesised answer about a brand instead of ten blue links. This shifts the visibility problem from ranking to answer composition.

OpenAI explains that ChatGPT can search the web when current information is needed and provide source links in its answers. The quality, currency and mutual consistency of the brand’s web sources therefore matter indirectly to AI-generated answers.

VLOSE designation does not mean brands can buy rankings in ChatGPT or that the DSA entitles them to specific answers. The main operational change is that AI search visibility is now taken seriously as a separate surface for measuring reputation.

The B10_CHATGPT_VLOSE_REPUTATION model connects traditional SERP monitoring and AI answer monitoring within one reputation intelligence framework.

What should companies do? ChatGPT / AI Search Reputation Review

Create a brand query set. Separate queries about the brand, products, executives, complaints, trustworthiness and comparisons.
Keep answer snapshots. Record the date, question, answer summary and sources used.
Examine source quality. Measure which official and third-party sources feature prominently in AI answers.
Correct misinformation at the source. Focus on the original web source spreading the error as well as the AI answer.
Keep owned content more up to date. Keep product, contact, policy and company information consistent and accessible.
Provide structured facts. Reduce conflicting data in pressrooms, FAQs, product pages and corporate statements.
Measure Google and AI results separately. Recognise that visibility may differ for the same query.
Set up escalation for high-risk answers. Prioritise answers involving fraud, security or legal allegations.

AI search monitoring is not deterministic: identical or similar queries may receive different source combinations at different times. A repeated test set is therefore needed, rather than drawing a firm visibility conclusion from a single screenshot.

Brand teams should distinguish appearing in an AI answer from appearing positively. Citation share may be high while the cited source is a negative complaint or an old news story.

Reputation monitoring in answer engines such as ChatGPT should record the test protocol. Store the exact query, language, date, product or model used, whether web search was enabled and citations alongside the same snapshot. Otherwise, changes between answers on different dates become hard to interpret. For dynamic topics such as current news, company executives, security incidents and product recalls, track answer freshness as a separate KPI.

The brand’s web assets have a role beyond SEO. Conflicting about-us, pressroom, product, contact and policy pages can make it harder for answer engines to form a reliable, current account of the company. Old executive names, closed office addresses or outdated product features persisting across pages may become visible through AI answer monitoring. AI reputation work is therefore also an audit of corporate information governance.

Proposed Measurement Model for B10

Control	KPI	Risk Signal
Presence	AI answer presence rate	Brand absent from the answer
Accuracy	Fact accuracy score	Incorrect information
Sources	Owned-source citation share	Weak visibility of official source
Sentiment	Answer risk score	Negative or misleading synthesis
Freshness	Outdated fact incidence	Outdated information
Consistency	Cross-engine consistency	Difference between AI and SERP

These are not an official ranking measure called “ChatGPT ranking”; they are reputation intelligence indicators B10 uses to compare brand visibility in answers.

Expert Assessment

The importance of the 31 August 2026 designation is the formal classification of ChatGPT as a VLOSE under the DSA, rather than the birth of ChatGPT Search that day. The 159.1 million users reported in the Commission’s list make that scale concrete.

For brand communications, this means managing both the accuracy of owned media and the third-party information ecosystem. AI answers can also draw on sources outside the brand’s control.

Digital Risk and Compliance Analysis

Using B10_CHATGPT_VLOSE_REPUTATION, B10 can turn brand query sets, answer snapshots, citation/source analysis and Google–AI comparisons into periodic reports.