Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Microsoft’s Power Platform recently introduced an IP-based Firewall feature designed to restrict access to environments based on IP addresses.

Standing on stage at Microsoft Build, surrounded by innovators shaping the future in the era of AI Agents, I felt equal parts inspired and responsible. Inspired by the rapid momentum around AI, and responsible for raising a flag about something we don’t talk about enough - how we secure the very systems that are now acting on our behalf. This post isn’t a recap, rather a continuation, a chance to go deeper into the story I shared (and the one we’re still writing.)

As enterprises race to adopt AI Agents to drive productivity and innovation. We are excited to announce that Zenity and Microsoft Copilot Studio are joining efforts to enable full adoption of AI Agents. Together, Zenity and Microsoft Copilot Studio help organizations confidently build, deploy, and use AI Agents with built-in security and governance throughout the development and deployment process so they can accelerate adoption at scale.

In the ever-evolving landscape of AI, a new enabler has emerged that's quietly transforming how language models interact with the digital world: Model Context Protocol, or MCP. It may not be a household name yet, but if your organization is experimenting with AI agents, it's time to get acquainted. MCP is becoming the cornerstone of LLM integration - bridging the gap between isolated AI systems and the interconnected web of enterprise & client applications.

In the ever-evolving landscape of technology, the allure of AI tools and agents is undeniable. They promise enhanced productivity, innovative solutions, and a competitive edge. With more tools and platforms available that democratize the usage and creation of AI systems, there is a surge in AI tools that are being built, customized, and deployed for business operations. However, the gold rush for AI comes with significant risks that cannot be ignored.