VENDORiQ: Microsoft Build 2025 – How Microsoft’s New Services Could Drive Azure Consumption and Future Costs

Why it Matters:

The volume and nature of the announcements at Build 2025 highlight the vendor’s strategy to position itself as the central platform for AI consumption. The introduction of over 50 AI tools and features points to an expanded ecosystem designed to encourage developers to build on Microsoft’s platforms. This could translate to increased usage of – and therefore increased spend on – Azure (for AI services), GitHub (for AI-assisted development), and Microsoft 365 (for AI-enhanced productivity with Copilot). The emphasis on ‘AI agents’ and the ‘agentic web’ signifies a potential shift in how users interact with software, as outlined by IBRS in The Future of End-User Computing: The Biggest Change Since the Mouse is Upon Us.

All of this is expected to lead to demands for enhanced computational resources, both in the cloud and at the edge, as well as more sophisticated data management strategies to support these agent-driven environments. The expansion of Azure regions in Southeast Asia also supports this consumption strategy by providing regional infrastructure to facilitate AI deployments and data residency requirements, potentially lowering latency for users in those markets. 

Who’s Impacted?

• CIOs and CTOs: Recognise that as Microsoft expands its portfolio of new capabilities, it will aim to increase revenue through higher consumption. In short, as organisations leverage Microsoft’s new services, fees will continue to expand. Explaining why fees to Microsoft are growing to senior non-technical executives, especially the CFO – demands adopting new ICT Financial Operating models.
• Development Team Leads: They must evaluate new AI tools and frameworks for integration into software development lifecycles and skill development for their teams.
• Enterprise Architects: These professionals will need to determine how new AI agent capabilities integrate with existing enterprise systems and data architecture. 
• Data Scientists and AI Engineers: The expanded AI tools, particularly Copilot Tuning and multi-agent orchestration, offer new avenues for model training, deployment, and operationalisation.
• Business Unit Leaders: Consider how AI agents can automate or enhance specific business processes, potentially impacting efficiency and return on investment (ROI).

Next Steps

• Assess existing data infrastructure for its readiness to support increased AI processing and new data interaction patterns.
• Examine the cost implications associated with increased consumption of AI services and expanded cloud infrastructure.