Many organizations talk about using AI and automated processes, but their IT landscapes are not prepared for it. Fragmented systems, missing data classification and insufficient security structures slow down implementation. The gap between ambition and reality is widening – and increasingly becoming a barrier to productive AI adoption.
This discrepancy became clear at Microsoft Ignite 2025. Microsoft presented the “Frontier Firm” – a target picture of an organization where AI is deeply embedded into processes, data flows and security architectures. The model illustrates how (Agentic) AI automates tasks, orchestrates data flows and applies security mechanisms autonomously. It also highlights the infrastructural prerequisites organizations must meet to use (Agentic) AI productively at all.
For many companies, this still feels like a future vision – yet Ignite makes one thing clear: the expectations for an AI-ready infrastructure are rising now, not sometime later. Organizations that want to unlock the potential of (Agentic) AI need a consolidated foundation. The key question is: Which steps should companies prioritize today to make their infrastructure AI-ready?
Four action areas for an AI-enabled infrastructure
To deploy AI securely and efficiently, organizations need to intentionally evolve their infrastructure. Four action areas form the backbone of productive AI use:
Ensure secure access to AI
Technologies such as Windows 365 and Azure Virtual Desktop help close the scalability gaps that were difficult to address with classic endpoint management. They enable secure, flexible and location-independent access to AI-supported applications. Organizations should evaluate how these solutions can help provide employees with a protected entry point to modern AI tools.
Integrate existing technologies effectively
Many organizations are not fully leveraging the potential of their existing Microsoft licenses and tools. It is worth analyzing which capabilities – such as Teams Phone, Azure Virtual Desktop, Purview or Entra – can be activated and integrated more effectively to increase efficiency, security and AI readiness.
Accelerate cloud migration and modernize the infrastructure
Moving to cloud-based solutions is a key lever for flexibility, scalability and future readiness. Modern cloud infrastructures simplify the integration of new AI services and make it possible to use innovations such as Microsoft Copilot or Agentic AI productively. A practical example: migrating telephony to the cloud. Only then can call content be captured systematically and used for AI-supported insights.
Strengthen security, governance and data classification
With growing AI adoption, requirements for data protection, identity management and governance increase as well. Organizations should reassess and adapt their security concepts and implement solutions such as Microsoft Purview to protect data while making it usable for AI.
Conclusion: Infrastructure as the foundation for AI
AI is transforming the technological backbone of organizations. To deploy modern AI applications securely, at scale and productively, companies need a consolidated and powerful infrastructure. Microsoft Ignite 2025 made it clear how much these expectations are rising. Now is the time to evaluate and evolve your own infrastructure. Those who want to benefit from AI need a solid technological foundation. With a clear roadmap and the right guidance, achieving AI readiness becomes concrete and manageable.
Understanding the status quo and developing it further
Many organizations know they need to take action. At the same time, it is often unclear where they stand and which steps are required to achieve optimal AI readiness. A structured format can help clarify these questions. A targeted workshop enables an objective assessment of the status quo, identifies optimization and efficiency potentials and defines a clear roadmap for next steps.
Optimize infrastructure, reduce costs, enable AI
Campana & Schott helps you make your infrastructure ready for AI – with the InfraValue Workshop as a structured entry point into AI readiness.
