GPT-5 arrives in Microsoft 365 Copilot: what Lisa Crosbie’s video shows
In a new YouTube explainer, Lisa Crosbie [MVP] demonstrates GPT-5 inside Microsoft 365 Copilot, comparing it with the previous model. She shows side-by-side responses to both simple prompts and tasks that need deeper reasoning, emphasizing a clear performance gap. According to the video, GPT-5 delivers faster replies and more precise guidance across everyday scenarios. Moreover, it produces richer insights that aim to reduce follow-up prompts and manual clean-up.
How Copilot now chooses the right model for the job
The video highlights a new real-time router that lets Copilot pick the most suitable model for each prompt. For routine questions, it favors a high-throughput path to return quick, succinct answers. For complex or open-ended requests, it switches to a deeper reasoning mode that plans, gathers context, and checks its work before responding. This two-brain approach promises speed when it matters and patience when depth is required.
Practical impact: quick summaries versus careful analysis
Crosbie uses a marketing RFP example to illustrate the tradeoff between quick summaries and careful evaluation. Copilot rapidly compiles a list of responses from work data, offering immediate utility. Yet, when asked to assess and rank those proposals, GPT-5 takes more time to form a structured recommendation grounded in organizational context. The gain is clarity and actionability, though teams must balance waiting longer against the value of a more thoughtful answer.
Access, rollout, and what’s new in Copilot Studio
The blog details that licensed Microsoft 365 Copilot users can try the new model today, with a “Try GPT-5” session toggle and priority access. Users without a license will see staged availability in the coming weeks, receiving standard access as capacity expands. Additionally, Copilot Studio surfaces GPT-5 for building custom agents, enabling more ambitious workflows through tailored prompts and tools. However, organizations must weigh the benefits of advanced capabilities against governance, cost, and change-management demands.
Key considerations for teams and IT leaders
With higher capability comes responsibility: output may look confident, so verification steps remain essential. Model routing is largely invisible, which improves ease of use but may reduce transparency for users who want to know “what ran.” Therefore, clear guidance, prompt patterns, and data-access controls will help teams get consistent results while protecting sensitive information. In practice, leaders should set expectations about speed versus depth, monitor quality, and measure whether GPT-5 saves time across real tasks.
