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Microsoft is putting $2.5 billion into a new business to help companies use generative AI on a large scale. The Microsoft Frontier Company will bring together AI engineers, consultants, and partners to work directly with customers, helping them turn experimental AI projects into reliable tools that deliver real business results.
For IT leaders, this move is a good reason to review how ready their organization is for AI, check their data governance and integration, and think about working with Microsoft or its partners for support with large-scale AI projects.
Key takeaways
- Microsoft Frontier Company will focus on enterprise AI engineering and deployment.
- More than 6,000 industry and engineering professionals are expected to support customers.
- Rodrigo Kede Lima will lead the new business as president.
- Microsoft says customer data and intellectual property will not be used to train models in ways that dilute competitive advantages.
The initiative reflects intensifying competition among Microsoft, AWS, and OpenAI to operationalize enterprise AI.
This announcement highlights that Microsoft believes the main challenge for businesses is using AI in real operations, not just accessing AI models. Companies already using Microsoft Fabric, Power BI, and Microsoft 365 Copilot need to connect their own data, workflows, and rules to AI systems that deliver reliable results. For example, a business could use Microsoft Fabric to gather customer records from different databases, combine them with supply chain data in Power BI, and then use Copilot to create real-time inventory forecasts and automate reports. Ensuring data security and access controls are in place protects sensitive information while teams gain valuable insights. These examples show the practical challenges IT leaders face when moving from testing AI to using it at scale.
A deployment-focused operating model
Microsoft Frontier Company (MFC) will have more than 6,000 industry and engineering experts working directly with customer teams. They will help design, set up, and continually improve AI systems, measuring success by business results rather than just technical progress.
Rodrigo Kede Lima will lead the company. He brings nearly 30 years of experience and has managed sales transformation for Microsoft in the Americas and Asia.
MFC will also work with consulting and technology partners such as Accenture, Capgemini, EY, KPMG, and PwC. These firms provide industry expertise, proven methods, and frameworks to help businesses accelerate AI projects and ensure solutions meet industry standards and best practices. Partnering with them helps companies address the organizational, data, and security challenges that can slow down AI initiatives.
Protecting enterprise intelligence
Microsoft talked about an enterprise intelligence layer that gives AI agents and Microsoft 365 Copilot context from a company’s work, data, expertise, and decision-making. This layer brings together real-time information while keeping each business’s unique data separate.
Microsoft said it will not use customer data or intellectual property to train models in ways that reduce a company’s competitive advantage. For IT leaders, this means governance, access controls, tracking, and monitoring are essential parts of any AI project, not just extras added later. Microsoft recommends best practices such as setting clear data classification rules, using role-based access controls, and keeping detailed records of data use. Using frameworks like Microsoft’s Responsible AI Standard or the AI Risk Management Framework (NIST) can help IT teams assign responsibilities, perform regular risk checks, and closely monitor how models behave. These steps help organizations build a secure, compliant, and responsible approach to AI.
A strong data foundation is also important. Spargent helps companies unify their data with Microsoft Fabric and offers managed analytics in Power BI. This approach gives leaders a clear path to prepare data for reporting, automation, and AI projects. Spargent’s focus on measurable results, such as faster reporting and ROI-driven delivery, aligns with Microsoft’s emphasis on business impact.
Competition intensifies around enterprise AI
Microsoft’s investment is part of a trend where tech companies are placing AI experts directly inside customer organizations. Amazon Web Services recently announced a $1 billion plan with Forward Deployed Engineering teams, and OpenAI launched a deployment business after acquiring the AI consulting firm Tomoro.
These strategies show that companies now need help using AI in real situations, not just accessing AI models. According to Deloitte research cited in the announcement, 92% of organizations surveyed are using or planning to use AI in their services, and many are bringing work back in-house to build skills and save money.
For business leaders, the main goal is to choose partners who can connect AI projects to secure data systems, track adoption, and demonstrate financial results. Success with AI should be measured by clear outcomes like faster project delivery, higher productivity, quicker automation, and cost savings or revenue growth from AI. Microsoft’s new business will succeed if it can deliver these improvements consistently, not just because it has a large engineering team.
What enterprises should evaluate next
Companies considering wider use of AI should focus on three key areas before moving beyond pilot projects:
- Data readiness: Is your business data unified, well-managed, and easy to access when needed?
- Operational controls: Are security, monitoring, compliance, and ownership clearly set up?
- Business value: Can your teams measure how much AI improves adoption, productivity, cost savings, or revenue?
For organizations using Microsoft tools, Fabric and Power BI can provide the data and analytics foundation needed to answer these questions. Having a clear plan and getting help from certified experts if your team is stretched can help ensure your AI investment leads to real business results.
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