Most business leaders I meet no longer need to be convinced that AI works. They’ve seen the pilots, the demos and the copilots. The question I hear in boardrooms now is different: How do we move from AI that impresses to AI that changes how the business actually runs?

That is the question Microsoft Frontier Company was built to answer, and to date, we have engaged on nearly 500 projects with over 200 customers across 28 countries.

Customers including 3M, Alaska Airlines, BMW, Core42, KT, Land O’Lakes, London Stock Exchange Group, Mastercard, McKesson, Northern Trust, Novo Nordisk, Publicis Groupe, Saint-Gobain, Siemens and Unilever are seeing real value from working side by side with our Forward Deployed Engineering teams.

More importantly, most customers where we have completed initial projects have returned for additional engagements, generating hundreds of follow-on projects. Customers don’t come back for engineers. They come back because the first engagement delivered something they could measure and they can see the next workflow worth redesigning.

The technology is ready. What slows AI down is everything around it. That means identifying where AI can deliver the greatest value, building in trust and governance, redesigning the operating models and helping people work in new ways. Technology and people have to move forward together.

What this looks like in practice

Unilever is collaborating with Microsoft engineers to bring AI into its factories. On the factory floor, intelligent technology helps teams boost efficiency and deliver superior products to customers. In Pondicherry factory — Unilever’s largest Home Care Liquids factory in South Asia and a 2026 World Economic Forum Lighthouse site — a digital twin built on NVIDIA Omniverse and hosted on Azure simulates a real factory environment with integrated live data. This helps anticipate issues before they occur, monitors performance in real time and guides operators through the fixes and recommendations.

3M is working with our engineers to help its Global Business Services team automate customer order management. The companies are building an AI agent-driven workflow to assist with credit checks, delinquency assessments and system updates, with human-in-the-loop controls and a custom monitoring dashboard for real-time visibility and approvals. The solution is expected to significantly reduce manual effort, improve speed and consistency and accelerate cash flow — freeing staff for higher-value work while enabling scalable, auditable operations.

Publicis Groupe is co-building with our engineers to bring AI into the heart of how it works and delivers for clients. Microsoft engineers work side by side with Publicis teams to design and build agentic processes grounded in Microsoft IQ, so agents work with the business context, data and knowledge behind Publicis’ work. These processes use reinforcement learning, drawing on real-world outcomes and human feedback to keep improving how the agents perform over time. The approach combines very fast engineering with hands-on knowledge transfer, helping Publicis build lasting AI capability. The work builds on Publicis’ rollout of Microsoft 365 Copilot to all 114,000 of its employees.

Northern Trust needed to accelerate onboarding to its Asset Servicing Front Office Solutions platform, a process that took about two and a half weeks per client. Our engineers worked alongside Northern Trust’s experts to build an AI-powered onboarding agent within the Excel and SharePoint tools analysts already use. The result: data preparation time fell 83%, from two and a half weeks to three days, with 96.5% first pass quality score in testing. Analysts remain in control while gaining more time for higher-value client service.

KT, one of South Korea’s largest telecommunications providers, wanted to help network operators identify and respond to problems faster. Our engineers worked from KT’s offices to co-build AIO-Net, a continuously learning AI agent platform informed by KT’s operating procedures and veteran network experts. It now detects network issues in two to three minutes, down from more than ten, while keeping people in control of decisions and actions.

Saint-Gobain, the 360-year-old construction materials company, is using AI to help reduce the carbon footprint of cement. Working alongside its researchers, Microsoft engineers used Microsoft Discovery to gather 62,000 patents and 44,000 research abstracts into a knowledge base in hours, work Saint-Gobain estimates would have taken researchers a year. In about six weeks, the team identified new hypotheses for cement additives that scientists are now testing in the lab.

Across all of these customers, the pattern is the same:

  1. Begin with the value, not the technology.
  2. Redesign the process, not just the task.
  3. Build in fast cycles with the customer’s teams.
  4. Put security, governance and cost management in place from day one, so scaling doesn’t stall.

This is how organizations move from isolated AI projects to sustainable transformation: by focusing on measurable outcomes, redesigning work and building the capabilities to keep improving over time.

New research from IDC underscores why this approach matters. While 66% of organizations report substantial or transformative results from AI, only 48% are scaling or seeing consistent value across their organizations. At the same time, 71% expect AI spending to increase by at least 10% in the next year, putting even greater pressure on businesses to demonstrate measurable returns. The challenge is no longer simply adopting AI. It is reimagining how work gets done and turning that transformation into lasting business impact.

We’re holding ourselves to the same standard

If we’re asking customers to redesign how they work around AI, we have to do the same. Microsoft Frontier Company was deliberately designed to be flat and fast, with one front door for customers, and as a reference for what an AI-native organization can look like. We are learning, adjusting and moving fast, the same way we ask our customers to.

The real measure of success

The gap between AI that impresses and AI that delivers won’t close on its own. It closes workflow by workflow, with people who understand the business sitting next to people who can build.

Our success will be measured by more than what we deliver. The real test is what our customers can do after we’ve worked together: run, govern and improve their own AI systems, on their terms, with their intelligence protected. Their success is the clearest measure of ours.

Learn more at www.microsoft.com/en-us/frontier-company.

Rodrigo Kede Lima is the President of Microsoft Frontier Company and leads the operating business of 6,000 industry and engineering experts focused on delivering Frontier Transformation through AI for customers around the world.

 

NOTE

IDC Infographic, sponsored by Microsoft, The Real Business Value of AI, IDC #US54985026-IG, November 2026

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