This week, Google released a family of open AI models, Gemma 3, that quickly garnered praise for their impressive efficiency. But as a number of developers lamented on X, Gemma 3s license makes commercial use of the models a risky proposition.Its not a problem unique to Gemma 3. Companies like Meta also apply custom, non-standard licensing terms to their openly available models, and the terms present legal challenges for companies. Some firms, especially smaller operations, worry that Google and others could pull the rug on their business by asserting the more onerous clauses.The restrictive and inconsistent licensing of so-called open AI models is creating significant uncertainty, particularly for commercial adoption, Nick Vidal, head of community at the Open Source Initiative, along-running institutionaiming to define and steward all things open source, told TechCrunch. While these models are marketed as open, the actual terms impose various legal and practical hurdles that deter businesses from integrating them into their products or services.Open model developers have their reasons for releasing models under proprietary licenses as opposed to industry-standard options like Apache and MIT. AI startup Cohere, for example, has been clear about its intent to support scientific but not commercial work on top of its models. But Gemma and Metas Llamalicensesin particular have restrictionsthat limit the ways companies can use the models without fear of legal reprisal.Meta, for instance, prohibits developers from using the output or results of Llama 3 models to improve any model besides Llama 3 or derivative works. It also prevents companies with over 700 million monthly active users from deploying Llama models without first obtaining a special, additional license.Gemmas license is generally less burdensome. But it does grant Google the right to restrict (remotely or otherwise) usage of Gemma that Google believes is in violation of the companys prohibited use policy or applicable laws and regulations.These terms dont just apply to the original Llama and Gemma models. Models based on Llama or Gemma must also adhere to the Llama and Gemma licenses, respectively. In Gemmas case, that includes models trained on synthetic data generated by Gemma.Florian Brand, a research assistant at the German Research Center for Artificial Intelligence, believes that despite what tech giant execs would have you believe licenses like Gemma and Llamas cannot reasonably be called open source.Most companies have a set of approved licenses, such as Apache 2.0, so any customlicenseis a lot of trouble and money, Brand told TechCrunch. Small companies without legal teams or money for lawyers will stick to models with standard licenses. Brand noted that AI model developers with custom licenses, like Google, havent aggressively enforced their terms yet. However, the threat is often enough to deter adoption, he added.These restrictions have an impact on the AI ecosystem even on AI researchers like me, said Brand.Han-Chung Lee, director of machine learning at Moodys, agrees that custom licenses such as those attached to Gemma and Llama make the models not usable in many commercial scenarios. So does Eric Tramel, a staff applied scientist at AI startup Gretel.Model-specific licenses make specific carve-outs for model derivatives and distillation, which causes concern about clawbacks, Tramel said. Imagine a business that is specifically producing model fine-tunes for their customers. Whatlicenseshould a Gemma-data fine-tune of Llama have? What would the impact be for all oftheirdownstream customers?The scenario that deployers most fear, Tramel said, is that the models are a trojan horse of sorts. A model foundry can put out [open] models, wait to see what business cases develop using those models, and then strong-arm their way into successful verticals by either extortion or lawfare, he said. For example, Gemma 3, by all appearances, seems like a solid release and one that could have a broad impact. But the market cant adopt it because of itslicensestructure. So, businesses will likely stick with perhaps weaker and less reliable Apache 2.0 models.To be clear, certain models have achieved widespread distribution in spite of their restrictive licenses. Llama, for example, has been downloaded hundreds of millions of times and built into products from major corporations, including Spotify.But they could be even more successful if they were permissively licensed, according to Yacine Jernite, head of machine learning and society at AI startup Hugging Face. Jernite called on providers like Google to move to open license frameworks and collaborate more directly with users on broadly accepted terms.Given the lack of consensus on these terms and the fact that many of the underlying assumptions havent yet been tested in courts, it all serves primarily as a declaration of intent from those actors, Jernite said. [But if certain clauses] are interpreted too broadly, a lot of good work will find itself on uncertain legal ground, which is particularly scary for organizations building successful commercial products.Vidal said that theres an urgent need for AI models companies can freely integrate, modify, and share without fearing suddenlicensechanges or legal ambiguity. The current landscape of AI model licensing is riddled with confusion, restrictive terms, and misleading claims of openness, Vidal said. Instead of redefining open to suit corporate interests, the AI industry should align with established open source principles to create a truly open ecosystem.