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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesOrganizations are putting AI coding assistants inside the development tools and processes their engineers already use. Public examples describe help with code completion, unit tests, older code, unfamiliar languages, and repetitive work. The reports show different outcomes, but they do not establish a comparable set of exactly 36 deployments or prove that one company’s results will transfer to another.
How companies are using AI in software development
The documented deployments below center on GitHub Copilot, usually integrated with an existing IDE, source-control, or DevOps workflow rather than introduced as a separate development process. Organizations describe using it to draft or complete code, write and review code, generate unit tests, explore unfamiliar code or languages, and reduce routine work. The examples are customer stories and publisher summaries, so reported outcomes are attributed to the organizations and publishers that supplied them.
The title’s “36” should not be read as a verified, complete roster: the public sources cited here do not establish a canonical list of exactly 36 deployments. Microsoft’s customer-story roundup is a larger, changing collection. These are documented examples, not a count-certified survey.
Documented organizational deployments
Hitachi: coding and unit testing within existing frameworks
Hitachi adopted GitHub Copilot as part of an effort to promote internal AI use and improve system-development productivity. Microsoft’s 2025 customer story says Hitachi focused on coding and unit testing, integrated the tool into existing development frameworks, and formed a practitioner community to share knowledge. Hitachi began an internal evaluation in October 2023, recruiting around 200 participants for three to four months; it used a survey based on the SPACE framework and collected responses across six performance measures. Microsoft’s Hitachi customer story
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- Hitachi’s internal survey, as reported by Microsoft in 2025, found that 83% of users completed tasks faster.
- Hitachi reported average productivity gains of 10% to 20% in coding and unit testing, reaching 30% in some cases.
- In a separate validation application, Hitachi reported that combining Copilot with its Justware approach raised the code-generation rate from 78% to 99%. This is a specific validation-app result, not the broader survey finding.
These are Hitachi’s reported evaluation and survey findings, not an independent benchmark across companies.
HP: inline suggestions, chat, and work on older code
HP first trialed GitHub Copilot Business and then broadened use alongside GitHub Enterprise. Microsoft’s customer story describes developers using inline suggestions and chat in supported development environments and command-line interfaces, alongside Azure DevOps and Visual Studio. Reported tasks include writing and reviewing code, updating older code, and solving problems on new projects. Microsoft says several thousand HP developers were active daily, and characterizes productivity as increased without giving a standardized numerical result. Microsoft’s HP customer story
“To stay competitive, we knew we had to embrace AI, and from a developer’s perspective, we wanted to make that easier, giving our developers the tools and resources they need to create and collaborate efficiently, unlocking new value and new speed. GitHub Copilot was the answer.”
Rank #2
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- What You Get: Anker USB-C Hub (5-in-1, 4K HDMI), welcome guide, 18-month warranty, and our friendly customer service.
— Evan Scheessele, Senior Manager, Enterprise Digital Services, HP
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This is HP’s perspective in a Microsoft-hosted customer story, not an independently controlled evaluation.
Lumen Technologies: a pilot expanded to a global engineering group
Microsoft reports that Lumen piloted GitHub Copilot with nearly 600 engineers in Bangalore, India, then expanded the deployment to its global population of 2,400 engineers. The case describes use with Azure DevOps, Visual Studio, and Visual Studio Code. Lumen engineers used code suggestions and sought help with less familiar scripting languages, including Terraform, ARM, and Bicep. Managers described faster troubleshooting and more efficient onboarding; those outcomes are company-reported. Microsoft’s Lumen customer story
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“Autocomplete, in particular, saves developer time. It gives suggestions for multiple solutions with different code complexity, resolving issues that used to take half a day in less than an hour.”
— Nikita Rathore, Senior Software Engineering Manager, Lumen Technologies
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The time comparison is a manager’s account in the customer story, not a measured result reported for all engineers.
Rank #4
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Trimble: reducing repetitive work and context switching
GitHub’s customer story describes Trimble using Copilot to reduce repetitive work, fragmented knowledge, and context switching, including integration with GitHub Actions. Trimble reported saving 1,000 developer hours per day and an average of 30 minutes per developer per day. It also reported that output of web components changed from one per week to five per day. The accessed story does not show a publication date, so these figures should not be assigned a year. GitHub’s Trimble customer story
“We want to help developers reach that flow state. Copilot helps reduce the cognitive burden. If a developer is trying to remember how to do something and then the answer is right at their fingertips, that’s fantastic.”
— Jeff Doolittle, Distinguished Engineer and Principal Architect, Trimble
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These are company-reported figures in a vendor-published case story, not results from a controlled comparison with other organizations.
Microsoft’s roundup: Bancolombia, BNY, and LambdaTest
Microsoft’s July 2025 roundup summarizes additional software-development customer stories. It reports that Bancolombia saw a 30% increase in code generation, that more than 80% of BNY’s developer community relied on GitHub Copilot daily, and that LambdaTest integrated Copilot into its workflow and reported a 30% reduction in development time. The roundup also includes HP and Infosys among its software-development examples. These are concise publisher summaries, not equivalent to reviewing each organization’s underlying evaluation. Microsoft’s July 2025 customer-story roundup
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the Accenture study adds—and what it does not
GitHub’s May 13, 2024 report on research with Accenture describes a combination of a randomized controlled trial, DevOps telemetry, a company-wide adoption analysis, and a survey. The report says 90% of surveyed developers felt more fulfilled in their job when using Copilot, and 95% said they enjoyed coding more with its help. Those are survey responses, not productivity measurements from the randomized trial.
The same report says more than 80% of participants successfully adopted Copilot, and 67% used it at least five days per week; it separately gives an average use frequency of 3.4 days per week. These figures describe adoption and use among the Accenture participants, not general developer behavior. The report is published by GitHub, a Copilot vendor. GitHub’s report on the Accenture research
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How to compare the reported outcomes
The examples are useful for seeing implementation patterns, but their numbers should not be ranked as if they came from one common test. An internal survey, a customer-story estimate, a usage statistic, and a controlled trial measure different things. Before using a reported result to plan a rollout, ask:
- What work was assisted? Coding, unit testing, legacy-code updates, onboarding, or broader engineering tasks may produce different kinds of benefit.
- How was it rolled out? A pilot group is not the same population as a global engineering deployment.
- Where did it fit? IDE, source-control, command-line, and DevOps integrations affect how developers encounter and use the assistant.
- What evidence supports the claim? Distinguish a controlled trial or telemetry from survey responses, manager accounts, and vendor-hosted customer stories.
- What exactly was measured? Task completion speed, code generation, time saved, daily use, satisfaction, and productivity are not interchangeable outcomes.
Microsoft and GitHub publish several of these customer stories, and the organizations featured supply the reported claims. Treat them as attributed accounts of deployments, not independent proof of a universal productivity gain. The cited pages do not provide a standardized, same-method comparison across all the organizations.
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