As AI transitions from experimental deployment to enterprise-critical infrastructure, CIOs and IT leaders are being asked to guide their organizations through a rapidly evolving technology landscape. One of the most significant trends is the rise of AI agents — systems capable of making decisions and performing complex, multi-step tasks with minimal human oversight. Recent data shows that 72% of IT professionals report their organization is actively using AI agents, with another 21% stating they are planning to implement agentic AI systems within the next 24 months.
But as promising as these systems are, they face an all too familiar roadblock: integration. AI agents, like many emerging technologies before them, often operate in isolation from the core systems where business data and operational logic live. Without standardized integration, these agents are difficult to scale, expensive to maintain and limited in business impact. Gartner even predicts that through 2026, organizations will abandon 60% of AI projects due to a lack of AI-ready data.
Enter the model context protocol (MCP) — an open, vendor-agnostic standard that enables secure, two-way connections between AI agents and enterprise systems. For IT leaders, MCP is more than a technical innovation; it’s a strategic shift in how IT infrastructure can support intelligent, autonomous operations.
