Microsoft Copilot: Unveiling AI's Human Rhythms and Existential Role
F. Scott Fitzgerald's observation about the "real dark night of the soul" often striking at three in the morning finds a modern echo in the digital realm. Microsoft's latest Copilot usage analysis reveals that this nocturnal tendency for existential contemplation persists in the age of artificial intelligence, with conversations around religion and philosophy peaking during early morning hours. This comprehensive report, published on December 10, 2025, by the Microsoft AI (MAI) research team, delves into 37.5 million anonymized conversations, uncovering surprisingly human patterns in how users engage with AI.
Model Capabilities & Ethics
Model Architecture
Microsoft Copilot is a generative artificial intelligence chatbot developed by Microsoft AI. It is built upon OpenAI's GPT-4 and GPT-5 series of large language models, which are foundational to its capabilities. Specifically, Copilot utilizes the Microsoft Prometheus model, which incorporates an Orchestrator component to iteratively generate search queries. This system combines the Bing search index and results with OpenAI's GPT-4, GPT-4 Turbo, and GPT-4o large language models, fine-tuned using both supervised and reinforcement learning techniques. For Microsoft 365 Copilot, the architecture integrates with Microsoft Graph, an API that evaluates context and available Microsoft 365 user data before modifying and sending user prompts to the language model. After receiving the output from the large language model, Microsoft Graph performs additional context-specific processing before delivering the response to Microsoft 365 applications to generate content. In early 2025, Microsoft began routing Copilot requests to GPT-5 as the standard model across most surfaces, replacing earlier versions like GPT-4o and GPT-4.1.
Training Data
The core of Microsoft Copilot's capabilities stems from its large language models (LLMs), which leverage extensive training on diverse datasets to understand and generate human-like text. Microsoft has announced plans to use customer data from Copilot, Bing, and Microsoft Start (MSN) to further train its generative AI models, aiming for greater breadth and diversity in training data to create more inclusive and relevant products. This process involves learning from aggregated user ratings and incorporating colloquial expressions and local references from Copilot conversations. Users who prefer not to have their data used for AI training have an opt-out option, and Microsoft has stated its commitment to privacy obligations, including the removal of identifying information and the exclusion of data from the European Economic Area (EEA) for this specific training purpose. For Microsoft 365 Copilot, user-provided prompts and Copilot's responses are not used for training the underlying AI models. However, user engagement data, such as session duration and feedback, is collected with explicit consent and adheres to Microsoft's privacy policies.
Ethical Considerations
Microsoft has established a comprehensive Responsible AI Standard Framework to guide the ethical development and deployment of its AI systems, including Copilot. This framework is built on six key principles: Fairness, Reliability and Safety, Privacy and Security, Inclusiveness, Transparency, and Accountability. Copilot is designed to respect existing access management and protections, ensuring that it only accesses resources for which a user has permissions. User-provided prompts and Copilot's responses are not used to train the underlying AI models, and user engagement data is collected with explicit consent. Organizations using Copilot are encouraged to implement appropriate data governance measures to prevent unauthorized access and data breaches. Transparency in AI decision-making is crucial, requiring clear communication about how AI tools are used and ensuring employees understand AI's role in their work processes. Microsoft also emphasizes the importance of human oversight to prevent over-reliance on AI suggestions, fostering a culture where AI assists rather than replaces human critical thinking and judgment. Regular testing and review of Copilot's responses are advised to vet results before implementation, and users are encouraged to report any unexpected or offensive content.
User Interaction Patterns
The analysis of 37.5 million de-identified Copilot conversations from January to September 2025 reveals distinct usage patterns influenced by time of day and device type. Late at night, particularly in the early morning hours, conversations around religion and philosophy show a notable increase, suggesting users turn to Copilot for existential clarity during quiet moments. Conversely, travel-related discussions tend to peak during typical commuting times, indicating practical planning while users are in transit. Health-related topics consistently rank as the most common conversation type on mobile devices throughout 2025, regardless of the time of day or month. This suggests that users view their smartphones as personal companions for sensitive topics like wellness tracking, health tips, and daily routine management. Data from August 2025 highlighted a clear cyclical pattern between programming and gaming topics; programming conversations surged on weekdays, while gaming queries dominated weekends. Furthermore, in the lead-up to Valentine's Day in February, Microsoft observed a rise in conversations related to relationships and personal development. Overall, the study indicates a broadening of Copilot's usage beyond early technical adopters, with an increase in topics not directly related to technical matters, such as culture and history. This dual dynamic portrays Copilot as a "colleague" on desktop for work-related tasks and a "confidant" in the pocket for personal guidance and introspection.
Model Performance Benchmarks
While traditional machine learning benchmarks often focus on accuracy and F1 scores, Microsoft's Copilot performance is also evaluated through user engagement, adoption rates, and the speed of its underlying models. The integration of advanced large language models significantly impacts its operational performance.
| Metric | Value/Description |
|---|---|
| Default LLM | GPT-5 (since early 2025) |
| Tokens-per-second (tps) Output (GPT-5) | ~79 tps in independent testing |
| Time-to-First-Token (TTFT) (GPT-5) | Marginally higher than GPT-4.1 in some API routes |
| GPT-4.1 Usage | Still used in specific Power Platform and AI Builder tasks for faster TTFT in short-form outputs |
| Active Users (across Windows, app, website) | 33 million |
| Downloads (since launch) | 36 million |
| Copilot Dashboard Benchmarks | Internal comparisons (manager types, regions, job functions) and external comparisons (against similar companies, top 10%/25% overall) for active users, adoption by app, and returning user percentage. |
Expert Verdict
The latest usage analysis of Microsoft Copilot underscores a profound shift in how artificial intelligence is integrating into the fabric of human existence. Far from being merely a productivity tool, Copilot is emerging as a versatile digital companion, adapting its role to the user's context, device, and even their emotional and intellectual needs. The observed patterns, from late-night philosophical inquiries to daily health management on mobile devices, highlight AI's capacity to address fundamental human curiosity and provide personalized guidance. This deep social integration signifies that users are increasingly weaving AI into their daily routines, treating it as both a professional colleague and a personal confidant. As AI continues to revolutionize various sectors, including software development, understanding these nuanced human-AI interactions is crucial for building truly humanistic and effective intelligent systems. The insights from this report will undoubtedly inform future developments, ensuring that AI evolves in ways that are not only technologically advanced but also deeply aligned with human rhythms and needs. For more on the broader implications of AI, consider exploring Autonomous AI: The Future of Intelligent Systems in 2026, and for its impact on development, see How AI is Revolutionizing Software Development: A Deep Dive.