Half of Gen AI users want the technology open-sourced — Here’s why

Artificial intelligence development and deployment increasingly relies on open-source software, with organizations embracing open solutions for both cost efficiency and transparency according to new research from the Linux Foundation.

Key findings from the research: The Linux Foundation’s comprehensive survey of 316 AI professionals reveals widespread adoption of generative AI, with significant emphasis on open-source infrastructure.

• 94% of organizations currently use generative AI, with 42% reporting high or very high adoption rates
• On average, 41% of organizations’ AI code infrastructure is open source, rising to 47% among high adopters
• 71% of respondents indicate that open source positively influences their decision-making processes

Cost considerations and efficiency: Organizations are turning to open-source generative AI solutions primarily due to significant cost savings and reduced vendor dependence.

• 46% of organizations cite cost efficiency as their primary motivation for choosing open-source AI solutions
• Tools like LangChain and LlamaIndex enable AI model development at a fraction of proprietary solution costs
• For context, BloombergGPT, a 50-billion parameter finance LLM, cost approximately $3 million to build

Technical implementation trends: Cloud native technologies are playing an increasingly crucial role in deploying generative AI applications at scale.

• 50% of organizations utilize Kubernetes to host some or all of their AI inferencing workloads
• Basic AI development relies heavily on open-source frameworks like PyTorch and TensorFlow
• Organizations are increasingly integrating cloud native solutions for scalable AI deployments

Transparency and compliance considerations: Trust and regulatory compliance emerge as critical factors driving open-source AI adoption.

• 52% of respondents prioritize transparency and source code access when choosing AI solutions
• Organizations value the ability to verify model behavior and identify potential biases
• Licensing complexities present challenges, with some AI models claiming to be open source while using non-standard licenses

Future outlook and industry sentiment: The research indicates strong momentum toward increased open-source AI adoption and development.

• 73% of organizations plan to increase their use of open-source AI tools within two years
• 82% believe open-source AI is crucial for ensuring a positive AI future
• 83% agree that increasing openness in AI development is essential for fostering trust and innovation

Strategic implications: While open source continues to shape the future of AI development, organizations must carefully navigate licensing complexities and regulatory requirements while leveraging these tools to maintain competitive advantage in an rapidly evolving technological landscape.