Details
Microsoft 365 Copilot brings transformative potential, empowering employees to access and analyze vast amounts of enterprise data within M365 applications. While this significantly boosts employee productivity, it also introduces new governance and security risks. In the rush to adopt Copilot, many organizations have overlooked essential data governance controls, leading to unintended exposure of sensitive information. Employees may unknowingly query confidential data, such as salary details, M&A plans, or even passwords—information they should not be able to access.
This webinar will guide you through best practices for safely integrating Microsoft 365 Copilot, by putting in place robust governance and security measures, preventing unauthorized access and ensuring that sensitive data remains protected.
Key Takeaways:
- Understanding the security implications of Microsoft 365 Copilot
- Evaluating your M365 environment’s readiness for Copilot
- Implementing a 6-step framework for automated M365 data security and governance
Speakers
Post-event summary
The webinar titled “Accelerate Microsoft 365 Copilot Adoption with Data Governance Controls,” hosted by EDM Council and Securiti, focused on safe adoption practices for AI copilots, such as Microsoft 365’s Copilot, and offered insights on managing data security and governance in SaaS environments. The webinar was led by experts in the industry:
- Jack Berkowitz, Chief Data Officer, Securiti
- Nikhil Girdhar, Sr. Director Product, Data+AI Security, Securiti
- Moderator: Jim Halcomb, Global Head of Research & Development, EDM Council
Speakers highlighted the critical need for organizations to strike a balance between productivity and data protection. Jack noted that while AI copilots offer transformative potential, “we need to think of this as an opportunity…to enable our team to maximize data sharing and help people find and trust data safely.”
The speakers emphasized data labeling as an essential method for controlling data exposure in AI copilots, which can prevent sensitive data from being mistakenly accessed or shared. Nikhil advised using an automated approach to classify data by sensitivity, age, and usage to address over-permissioning and other risks more effectively. He recommended data owners play an active role in managing access rights and maintaining data hygiene to ensure only relevant information is accessible.
Further, the panel explored best practices for enforcing compliance, such as using a common intelligence layer to apply consistent policies across data environments. Jim and Jack underscored the role of cultural change in fostering responsible data use, with Jack adding, “Engaging everyone in your company to have that discussion and be aware of that information is an important part of your AI strategy.”