The MACH Alliance, a global not‑for‑profit advocacy group, has remained focused on its mission to guide brands toward transformative, open, and best-of-breed solutions that will drive the next era of business evolution.

Now, as agentic AI reshapes business, the Alliance’s role has evolved to focus on unlocking trusted, agent-to-agent ecosystems that drive innovation and collaboration. As the trusted authority on the “how,” the MACH Alliance enables this transformation through open, connected and composable architectures, bridging vision with real-world implementation.

Read on for details on the Alliance’s repositioning.

WHAT: The Alliance is refreshing its positioning to align MACH with the demands of an AI-centric technology landscape. Key focus areas include:

  • Establishing MACH as the foundation for AI-ready enterprise architecture.
  • Driving interoperability through new certifications and governance standards (MCP, A2A, AI-Connected Certification, Open Data Model).
  • Launching proof-driven innovation with programs like the MACH AI Exchange and FutureMACH.
  • Publishing practical tools, reference architectures and business transformation guides.
  • Aiming to make agent-to-agent ecosystems a reality--trusted, open and scalable across vendor and enterprise boundaries.

WHY: AI is already reshaping how enterprises operate, from decision-making to customer interaction, and its impact is accelerating. But its true value will only emerge through connected, open and interoperable ecosystems, not isolated tools. Reasons include:

  • Data and systems agility: It’s crucial for generative AI and agents to function across silos.
  • Real-time interaction patterns: Agentic systems require real-time trust, governance, and negotiation, which can be enabled by MACH standards.
  • Composable ecosystems: No single player can build the future of AI ecosystems. MACH provides the connective tissue.
  • Historical validation: Enterprises well along in their MACH journey are twice as likely to successfully deploy AI, with 77% achieving success compared to just 36% for those new to MACH.