AI’s potential for innovation comes with equal parts vulnerability. Complex models, opaque algorithms and large data sets make it difficult to fully understand and secure their AI systems. Smaller businesses are often most exposed to data privacy issues and unauthorized tool use, while larger enterprises face adversarial attacks, compliance pressures and supply chain risks.
Download the Guide
In another recent blog post, we talk about how to access Microsoft 365 Defender and Microsoft Purview Compliance Portals (formerly Office 365 Security and Compliance Center) and a set of admin roles used for securing and governing tenant data. In this post, we will cover the various admin roles and responsibilities of Microsoft 365, including the impact…
The first quarter of 2026 has made one thing abundantly clear: attackers are no longer “breaking in” — they’re logging in, redirecting, impersonating and exploiting trust at every layer of the digital ecosystem. From app store impersonation kits to nation state account hijacking to regulatory decisions that may unintentionally weaken home network security, Q1 has…
My colleague, Andrea Mondello, recently published two posts worth reading if you’re navigating AI adoption right now. One makes the case that data quality issues, not AI itself, are what’s holding organizations back. The other draws on lessons from enterprise AI deployments to help mid-market companies avoid the costly mistakes that larger organizations have already…
