In a significant shift, open source has emerged as the foundation of enterprise technology, with AI, cloud infrastructure, and devops projects leading the charge. According to GitHub data, open source projects have become the default choice for enterprises, with a 98% year-over-year increase in generative AI projects and a 92% rise in Jupyter Notebook usage.

This trend is not limited to AI alone. Open source infrastructure projects, such as Kubernetes, have seen massive adoption, with 71% of Fortune 100 companies using it as their primary container orchestration tool. Kubernetes has garnered 114,000 GitHub stars, more than 40,000 forks, and over 74,000 contributors from more than 7,800 companies. The project's success is a testament to the power of open source development, with nearly 2,000 open issues and daily commits in 2025.

Beyond Kubernetes, companies have flocked to open source infrastructure as code (IaC) and container tools to manage cloud deployments. HashiCorp Terraform has emerged as a de facto standard for IaC, with 45,000 stars and 9,800 forks. The rise of IaC usage overall is evident, with GitHub's data showing a 36% year-over-year growth in 2023. This aligns with a sharp uptick in developers using Terraform and similar tools to standardize cloud deployments.

The use of open source for containerization and pipeline automation has also exploded. GitHub's Octoverse notes that by 2023, 4.3 million repositories on GitHub were using Docker container files, including over one million public repos with Dockerfiles. In parallel, infrastructure automation via CI/CD pipelines and "everything as code" grew sharply. Developers are not only containerizing apps but also automating their release processes using tools like GitHub Actions, GitLab CI, and Argo workflows.

Machine learning and AI projects have experienced unprecedented growth in both usage and community size. Although established frameworks like TensorFlow and PyTorch remained extremely popular, the real story was the advent of generative AI and large language model projects in open source. In 2023 alone, the number of generative AI projects on GitHub jumped 248% year over year, while the count of individual contributors to these projects grew by 148%, according to GitHub data.

Standout projects like Hugging Face Transformers, LangChain, and AutoGPT have seen massive adoption, with Hugging Face Transformers becoming a central tool for natural language processing and model sharing. Newcomer projects saw some of the fastest star-growth ever recorded, with LangChain rocketing to over 100,000 stars within about a year and AutoGPT gaining more than 174,000 stars, putting it among GitHub's top projects virtually overnight.

The trend is clear: AI dominates open source growth. By 2023, GitHub noted that some open source generative AI projects were already among the top 10 most popular projects by contributor count. This is a remarkable shift, as historically, the top-contributed projects were often operating systems, databases, or dev tools. Now, AI projects—many started by individual developers or research labs—are rallying huge communities.

This AI boom wouldn't be possible without open source first laying the foundation in other categories. For example, deploying machine learning models at scale requires cloud infrastructure like Kubernetes operators for AI and MLOps pipelines, plus devops automation. Enterprises leveraging AI are simultaneously investing in those open platforms. In essence, AI hasn't replaced interest in cloud or devops projects, but instead has become their accelerant.

Data engineering projects, such as Apache Airflow and dbt, have also shown steady growth, addressing complex enterprise needs like processing millions of records or events. Although they don't get the same attention as generative AI projects, their adoption tends to be very deliberate, with more and more companies opting for open solutions over proprietary ETL/ELT or analytics tools due to benefits like flexibility and cost.

In conclusion, open source has become a fundamental business imperative, driving innovation and enterprise defaults in AI, cloud infrastructure, and devops. As AI goes open source early, enterprises must follow this strategic playbook to succeed. The numbers are clear: open source is no longer a nice-to-have, but a must-have for businesses that want to stay ahead of the curve.