The Open Source Initiative has released the first Open Source AI Definition after two years of development. It requires developers to provide complete source code for AI systems, including specifications for data processing and training, but doesn't mandate the release of training data. The definition aims to make AI benefits accessible to all, though some experts believe the lack of open training data requirements may limit its practical value for commercial use. The OSI views this as a starting point, expecting the definition to evolve over time.

**For AI-focused companies:** You'll need to reassess your intellectual property strategy. Open-sourcing your AI systems' code could erode competitive advantages but might accelerate innovation and improve your systems through community contributions. **For all businesses:** Expect a shift in AI procurement. You'll have more transparency when evaluating AI solutions, potentially reducing vendor lock-in. However, without access to training data, you may still face challenges in fully understanding or customizing these systems. Consider allocating resources to review and potentially contribute to open-source AI projects, as this could become a valuable way to influence the direction of AI development in your industry.

**For the AI industry:** Prepare for a potential bifurcation between open and closed-source AI systems. This definition might spark a 'race to the middle' where companies strive to be as open as possible while maintaining commercial viability. You may see the emergence of new business models centered around open-source AI, similar to Red Hat's approach with Linux. **For regulators:** Anticipate increased pressure to mandate some level of AI transparency. The OSI's definition could serve as a blueprint for future AI regulations, potentially impacting your compliance requirements. Stay vigilant and proactive in understanding these developments to avoid being caught off-guard by rapid regulatory changes in the AI space.