{"id":24953,"date":"2026-07-30T08:45:00","date_gmt":"2026-07-30T15:45:00","guid":{"rendered":"https:\/\/www.microsoft.com\/insidetrack\/blog\/?p=24953"},"modified":"2026-07-29T15:44:06","modified_gmt":"2026-07-29T22:44:06","slug":"making-ai-testing-work-at-scale-at-microsoft-with-enterprise-test-platform","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/insidetrack\/blog\/making-ai-testing-work-at-scale-at-microsoft-with-enterprise-test-platform\/","title":{"rendered":"Making AI testing work at scale at Microsoft with Enterprise Test Platform"},"content":{"rendered":"\n

Every IT team knows the feeling: A project is on track, and then testing becomes the wall everything stacks up against. Slow cycles, fragmented tools, and manual validation are some of the most persistent bottlenecks in enterprise technology.<\/p>\n\n\n\n

AI tools for testing are everywhere, but for most organizations, they’re still experiments, not infrastructure.<\/p>\n\n\n\n

When our Commerce Platforms team, which owns the company\u2019s core commerce and financial platform services, found itself staring down a critical SAP migration with a hard deadline, they decided it was time to try a different approach.<\/p>\n\n\n\n

They wanted to know if enterprise-grade AI testing was actually achievable.<\/p>\n\n\n\n

A growing challenge<\/h2>\n\n\n\n

Behind the scenes, we run much of our global business on SAP. From finance and supply chain management to HR and procurement, SAP serves as a critical enterprise platform across the company.<\/p>\n\n\n\n

Testing across our 40-plus SAP service lines had long relied on third-party tools. Our licensed infrastructure had finite capacity and required manual test-case authoring. And the vendor we were working with wasn\u2019t able to move as quickly as we wanted.<\/p>\n\n\n\n

As a result, costs compounded in every direction. Reliance on third-party testing tools to automate SAP regression testing came with high licensing costs, infrastructure requirements, and operational complexity. Together, those tools cost us about $500,000 a year to maintain. With only 80 third-party tool licenses spread across more than 40 service lines, teams were perpetually competing for capacity.<\/p>\n\n\n\n

Additionally, security vulnerabilities and compliance findings in third-party testing tools became an ongoing liability. Vendor remediation timelines stretched to 9 or 10 months, far beyond our requirements.<\/p>\n\n\n\n

Then came the deadline that forced us to act.<\/p>\n\n\n\n

One of the first major tests came from the Global Trade Services (GTS) system, which handles customs and invoice generation processes required to move products across international borders. As part of our broader SAP modernization effort, GTS had to migrate from SAP ERP Central Component to SAP Business Suite 4 HANA before a December 2025 deadline or shipments would stop. The team had 10 months. The traditional testing approach wouldn\u2019t get us there.<\/p>\n\n\n\n

The time had come to explore AI as a solution for a testing model that was becoming unsustainable. With an ambitious goal, and the GTS team\u2019s blessing, we developed Enterprise Test Platform, an AI-driven testing solution.<\/p>\n\n\n\n

Building with an incremental approach<\/h2>\n\n\n\n

Our team started narrow. Rather than replacing their third-party testing platform overnight, they focused first on test-case authoring. It was a practical starting point: Teams already had years of business process documentation, but turning that knowledge into structured, executable test cases still required significant manual effort. <\/p>\n\n\n\n

\"A<\/figure>\n\n\n\n
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\u201cWe realized that enterprise teams already had the documentation AI needs. Once we saw that AI could convert that knowledge into reliable, structured test cases, it changed the trajectory of the entire project.\u201d<\/p>\nNeeraj Tripathi, principal program manager, Commerce Platforms team<\/cite><\/blockquote>\n\n\n\n

Process documentation, API references, business requirement documents, and functional flows were already there, scattered across systems. The missing piece was converting that existing knowledge into structured, executable test assets.<\/p>\n\n\n\n

\u201cWe realized that enterprise teams already had the documentation AI needs,\u201d says Neeraj Tripathi, a principal program manager on the Commerce Platforms team. \u201cOnce we saw that AI could convert that knowledge into reliable, structured test cases, it changed the trajectory of the entire project.\u201d<\/p>\n\n\n\n

Early results exceeded expectations. That momentum gave the team confidence to expand beyond test-case authoring to eventually encompass execution, validation, orchestration, and reporting, consolidating fragmented testing capabilities into a unified first-party platform.<\/p>\n\n\n\n

Making a dramatic impact<\/h2>\n\n\n\n

The GTS migration became the proof point. The team ran three full mock drills using the Enterprise Test Platform throughout, and the numbers tell the story of a team learning in real time.<\/p>\n\n\n\n

\"A<\/figure>\n\n\n\n
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\u201cThe migration of delta was completed in 11 minutes. We have set an industry benchmark with this project.\u201d<\/p>\nPriyanka Alva, program manager lead, Global Trade Services<\/cite><\/blockquote>\n\n\n\n

In the first mock drill, the system cutover alone took 144 hours. In the second, it was 36 hours. In the third, 11 hours. Finally, the GTS system went live on SAP S4 Migration on Azure in six hours, with SAP Support flying a team in from overseas to be on site.<\/p>\n\n\n\n

\u201cThe migration of delta was completed in 11 minutes,\u201d Alva says. \u201cWe have set an industry benchmark with this project.\u201d<\/p>\n\n\n\n

The in-house migration tool and Enterprise Test Platform contributed directly. Weekly regression testing that previously consumed three full days dropped to under an hour. Alva\u2019s team achieved 57% automation across the full migration effort, a result that came during the first pilot, while the tool was still being actively developed in parallel. The go-live produced zero post-launch defects.<\/p>\n\n\n\n

\"A
Weekly regression testing that previously consumed three full days dropped to about one hour.<\/figcaption><\/figure>\n\n\n\n

Since then, the Enterprise Test Platform has been used for other service lines. The broader organizational results are just as striking:<\/p>\n\n\n\n