First major OpenAI AI study: Who really uses ChatGPT? – and for what purpose? A detailed analysis

Who actually uses ChatGPT? The 7 most important findings from the first major OpenAI study

Forget programming: What most people really use ChatGPT for will surprise you

Since its launch, ChatGPT has become a global phenomenon, reaching hundreds of millions of people weekly. But behind these impressive user numbers lies a crucial question of central importance to business, politics, and society: Who are these people really – and what exactly do they use this powerful language model for in everyday life? A new, comprehensive study by OpenAI, based on the analysis of 1.5 million anonymized conversation transcripts, now provides detailed and, in some cases, surprising answers for the first time.

The results overturn many common assumptions. Contrary to the stereotype of the tech-savvy male user, ChatGPT is now predominantly used by women. Usage has shifted dramatically from professional to private use, where the focus is no longer on complex programming tasks, but rather on practical everyday questions and text optimization. At the same time, the analysis reveals a growing global dynamic: while growth is slowing in Europe and North America, user numbers are exploding in Asia, Latin America, and Africa. This development has far-reaching consequences – not only for OpenAI, but also for the search engine giant Google, whose core business is being directly challenged by this new form of information retrieval.

This article analyzes the key findings of the study, highlights the demographic shifts, and explains what the true ChatGPT revolution means for all of us.

Why does the actual use of ChatGPT deserve closer examination?

Since its release in November 2022, ChatGPT has become a mass phenomenon, reaching around 700 million people weekly, according to OpenAI. For developers, companies, policymakers, and society, however, the sheer number of users is less important than understanding who actually uses the service, for what purposes, and in what situations. Only on this basis can meaningful business models, data protection regulations, and educational concepts be developed. A recently published, 62-page study by OpenAI now provides, for the first time, a detailed look at real conversation transcripts, thus offering a wealth of material for systematic analysis.

Context of the study

Under what circumstances was the investigation conducted and published?

The study was conducted between May 2024 and June 2025. It is based on approximately 1.5 million anonymized interview transcripts, which were automatically analyzed. OpenAI made the results available to the Washington Post to stimulate public debate. While the study has not yet undergone peer review, the scope and transparency of the data are remarkable, as previous findings were mostly based on smaller surveys or internal estimates. OpenAI aims to demonstrate through this disclosure that its model can be used responsibly and that it is willing to make research accessible before final scientific reviews are completed.

Methodology and data basis

How was the data collected, cleaned, and classified?

Data collection was performed server-side, with personal information removed or pseudonymized to protect privacy. OpenAI then used both rule-based filters and machine clustering to identify recurring conversation patterns. Topics were grouped based on keywords and semantic similarities. In total, the researchers identified fourteen main categories, the most common of which are described in detail in the report. The categorization into private and professional contexts was achieved by defining specific signal words—such as "report," "presentation," or "boss"—as indicators of work-related use. To minimize bias, regional data was normalized for population size, and varying internet penetration was taken into account.

Demographic key data

What fundamental demographic trends can be identified?

The study confirms that ChatGPT has now reached a global audience. Almost half of all conversations come from users between 18 and 25 years old. This age group demonstrates a high affinity for digital technology and appears to be experimenting particularly intensively with new tools. Also noteworthy is the proportion of users from low-income regions, which is growing faster than in wealthier countries. This could be because ChatGPT offers inexpensive information that is difficult to access elsewhere. While previous internal figures suggested a dominance of North American users, the new data indicates that Latin America, South Asia, and Southeast Asia are now leading in growth rates. Although Europe and North America remain large markets, relative growth there has slowed.

gender distribution

What role does the gender of the users play and how has the distribution changed?

One particularly surprising finding concerns the gender distribution. Immediately after its launch in 2022, first names statistically considered male dominated, accounting for approximately 80 percent. Today, the proportion of users with female first names is 52 percent. This means that ChatGPT is now predominantly used by women. Explanations range from a growing interest in everyday and educational applications to a shift in perception of the technology as reliable and helpful, rather than purely experimental. Whether this development will influence long-term preferences in the design of language models remains to be seen, but companies must prepare for a more diverse target group than previously anticipated.

Age structure and regional differences

How are usage rates distributed across age groups and continents?

The 18-to-25-year-old age group accounts for nearly 47 percent of all analyzed conversations. Users aged 45 and over make up around nine percent – ​​a figure that still represents a considerable volume, considering that this segment is often more hesitant to adopt new technologies. Regionally, Asia now slightly surpasses North America in terms of weekly active users. While Africa still records lower absolute numbers, its growth rates are the highest, supported by the increasing expansion of mobile broadband networks. Europe occupies a middle position: stable growth, but less dynamic than in emerging markets. This presents an organizational challenge for OpenAI in reflecting the linguistic and cultural diversity in its training.

Private versus professional use

Has the ratio between private and professional use shifted?

Initially, private and professional use were roughly equal. By June 2025, this picture had changed significantly: around 73 percent of all conversations concerned private matters. There are several reasons for this. First, ChatGPT is becoming more widespread among school pupils, students, and hobbyists who primarily ask everyday questions. Second, many companies have now issued internal guidelines for the use of generative AI, which shifts chats with sensitive content to internal, often unrecorded systems. Third, some companies offer their own fine-tuning instances with stricter data protection, meaning that publicly available usage figures no longer reflect the entire professional spectrum.

Practical tips and everyday support

What role does ChatGPT play in solving everyday problems?

The most prominent category within private use, at 28.3 percent, is obtaining practical tips. This includes things like cooking recipes, repair instructions, or study strategies for exams. Users appreciate the fast, interactive format, which a traditional search engine only offers to a limited extent. The emphasis is on interactivity: For example, someone wanting to know how to prepare a specific dish with available ingredients receives step-by-step suggestions and can ask follow-up questions. For educational institutions, this raises questions about plagiarism and original work, as students can have solutions explained to them by ChatGPT without having to go through the entire thought process themselves.

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Text production and text optimization

How relevant is ChatGPT for creating or editing texts?

Text production accounts for almost as much of the discussion as practical tips, representing 28.1 percent of all conversations. Within this category, 38 percent of requests involve revising or critiquing existing texts. Approximately 28 percent concern writing emails, blog posts, or social media posts, while 16 percent are translations. Especially in a professional context, the rapid creation of rough drafts can save time. At the same time, new questions arise regarding copyright and originality when AI-generated passages are incorporated unmarked into academic articles or journalistic pieces. For companies, this creates a tension: On the one hand, ChatGPT accelerates internal communication processes; on the other hand, its unreflective use carries the risk of confidential data being leaked.

Information search and competition to Google search

Does ChatGPT pose a serious threat to traditional search engines?

Information searches account for 21.3 percent of all chats in the study, ranking third. Users often formulate their questions in natural language and prefer coherent answers to a list of links. Particularly striking is that around two percent of all research-related chats ask about specific products with the intention to purchase. Google generates a large portion of its revenue through ads alongside search results; if queries are answered directly via ChatGPT, advertising revenue could come under pressure. Google is therefore experimenting with its own AI responses, while OpenAI is examining the integration of product links and advertising formats. For media companies and online retailers, this means they need to optimize their content more effectively for AI systems to remain visible.

Purchase-related search queries and advertising potential

How large is the commercial potential behind product-oriented chats?

Currently, 2.1 percent of search chats involve questions about products that can be purchased. While this may sound small, it equates to almost 380 million conversations across 18 billion weekly search queries. Even with a low conversion rate, significant sales opportunities remain. OpenAI is investigating various monetization models, such as affiliate links similar to those used by price comparison sites or context-based advertising. However, critics warn that paid results could compromise neutrality. Furthermore, transparency is needed to clearly distinguish between advertising and independent answers. User acceptance depends significantly on recommendations remaining transparent and not perceived as hidden promotion.

Psychological uses: feelings, relationships, and role-playing

To what extent is ChatGPT used as a conversation partner for emotional topics?

The study shows that only 1.9 percent of conversations address feelings and relationships. Role-playing scenarios, in which the chatbot simulates a fictional character or a friend, for example, account for a mere 0.4 percent. This contradicts OpenAI's fears that ChatGPT is primarily used as a substitute for psychological counseling or partnership. Other studies, such as one from Brigham Young University, suggest that chatbots in the US are more frequently used to simulate romantic relationships. Apparently, usage patterns differ depending on the platform and cultural context. Nevertheless, ethical questions come to the fore when users develop emotional attachments to an AI that has no genuine feelings.

Comparison with other studies

How do the current findings fit into the existing state of research?

Previous studies were mostly based on surveys with a few thousand participants or on publicly available social media posts. These often revealed a male-dominated picture and a strong focus on programming and coding-related use cases. The OpenAI study contradicts both assumptions: women now use ChatGPT more than men, and classic programming questions only appear peripherally. Instead, everyday issues and text editing dominate. This result confirms the trend that generative AI is no longer a niche tool, but a multi-purpose instrument for broad segments of the population. However, OpenAI points out that server logs only capture those using the public service; internal company instances are excluded.

Impact on media companies and online retail

What are the consequences for traditional content providers and retailers?

When users access recipes, news digests, or product reviews directly from ChatGPT, the number of clicks on original websites decreases. Media companies must therefore develop strategies to offer their content as structured input for AI models to secure visibility and compensation. One approach is licensing articles to model operators. Online retailers, in turn, can benefit when product recommendations are generated as responses that seamlessly guide users to purchase. However, this creates competition for top placements in AI responses, similar to today's search engine optimization. Companies must provide data on availability, price, and delivery time in a machine-readable format to be considered in real time.

Implications for Google

What risks and opportunities does the search engine market leader face?

Google generates over $55 billion annually from search ads. Should a significant portion of product-specific queries migrate to ChatGPT, this business could shrink. Google is responding by integrating generative answers into its own search results and exploring ways to ensure advertisers still maintain visibility. Simultaneously, the company is investing in Project Gemini, its own large-scale language model. In the long term, the search experience could evolve from a list of links to a dialogic conversation, where AI systems aggregate information from the web. Google must ensure that creators are fairly compensated and that answers remain reliable in order to maintain user trust.

Limitations of the study

What methodological limitations does OpenAI itself mention?

First, the analysis has not yet been peer-reviewed, meaning it lacks external validation. Second, the sample only includes users who have consented to their data sharing; certain professional groups or regions may be underrepresented. Third, all data comes from a fixed timeframe, so short-term trends—such as news events—can influence the results. Fourth, it remains unclear how conversations with multiple topics were categorized if they cannot be clearly assigned to a single class. OpenAI acknowledges that the proportions may shift depending on the classification method. Nevertheless, the company considers the study an important contribution to an informed discussion.

Scaling AI regionally: Strategies for growth and diversity

What developments can be foreseen based on these findings?

OpenAI is likely to push commercial use by specifically expanding its text and translation services, as these areas generate demand and can be easily integrated into workflows. At the same time, it will need to increase regional diversity to support growth in emerging markets. Low-bandwidth models that run on less powerful devices are to be expected. In addition, there is a trend toward multimodal systems that seamlessly process images, audio, and code. The question of whether and how advertising formats are integrated depends on whether users accept paid recommendations. Finally, regulation will play a key role: data protection authorities are already calling for clearer guidelines on data use, and copyright experts are insisting on licensing models for training data.

Private rather than professional use: How people really use ChatGPT

What are the key findings of the study?

First, ChatGPT has made the leap from a tech-savvy niche application to a widely used everyday tool in less than three years. Second, there is a surprising dominance of female users, which contradicts common prejudices about technology use. Third, the focus is shifting from professional to private matters, with practical tips and text editing dominating. Fourth, Google is facing real competition, as users increasingly access information through dialogue. Fifth, the commercial value of product-related queries remains high, even though their share is still small. Sixth, psychological substitute relationships are currently a marginal phenomenon, but ethical questions remain. Seventh, the study has methodological limitations but provides valuable insights for research and industry. Overall, everything indicates that generative AI is being integrated into existing systems: it is seamlessly weaving itself into everyday processes, while technology providers, regulators, and society grapple with frameworks that enable innovation and mitigate risks.

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