July 24, 2026
In the 1980s, early open source software pioneers challenged the prevailing belief that software would only advance if companies maintained tight control over their code. This movement pushed for a transparent ecosystem where developers around the world could study, modify, and improve software. Software developed by the open source community now powers most of the Internet and underlies the systems used by the world’s largest technology companies as well as the U.S. military and federal agencies for scientific research, cybersecurity, and other critical functions. Open source hasn’t just reduced software costs; It created a common foundation of knowledge upon which generations of American engineers and entrepreneurs built their institutional sovereignty.
The United States now faces a similar decision with artificial intelligence. Our AI leadership will not be measured by a single AI frontier model, but by whether the United States is building a strong, open ecosystem that penetrates all sectors. This is essential to creating opportunities for innovation and prosperity across the country. It requires expanding access to AI, fostering competition, robust application layers, and giving Americans greater control over the technology they rely on. Open weight models – AI models that anyone can download, review, modify and run on their own infrastructure – are an important part of this foundation, making advanced AI more accessible, adaptable and widely available.
Open weights expand access to the AI economy. Startups, established companies, universities and public institutions can build on advanced models without training one from scratch or paying marginal model prices for each task. Open weights allow each organization to assign the right model at the right cost to the right task, reserving frontier scaling capabilities for real frontier problems and allowing efficient, specialized models to be deployed anywhere else. This discipline will make AI economically sustainable by expanding its use to billions of everyday tasks. America is winning the AI era by spreading it into the workflows of factories, hospitals, farms, classrooms and high street stores.
Open weights also increase competition, and competition ensures that the benefits of AI are shared broadly rather than concentrated in a few hands. By allowing many organizations to build, customize, and deploy advanced models, open weights create rivalry not only between model developers, but also between cloud chips, applications, and services. This competition drives innovation, reduces costs, and spreads the benefits of AI broadly throughout our economy.
Open weights also give customers better control. When companies invest in AI, they want to be sure that they are not locked into a single provider or losing the knowledge and skills they have built over time. Open weighting models help ensure this security by allowing companies to control their own data, evaluate and adapt models to their own needs, and deploy them wherever their business needs require. And as organizations create value with AI, open weights enable them to own that value through self-improving models, specialized skills, and accumulated knowledge that advance American sovereignty and prosperity.
Of course, open weights carry real and significant risks. Once released, weights are beyond the control of the original developer and modified versions are difficult to trace or reverse. However, the right response to this risk is not to ban open weights. In a world where cybersecurity attackers leverage advanced AI, defenders need access to models with comparable capabilities so they can detect, simulate and respond to emerging threats. Open models expand defense capability, increase transparency, and enable discovery and remediation of vulnerabilities across many teams.
In fact, openness could be one of the most important paths to AI security. Relying solely on closed models is not inherently safe: they can be breached, misused, or fail in ways that are not apparent to outsiders. And concentrating advanced AI capabilities behind a small number of closed models increases this risk. This leads to a small number of single points of failure, weakens competition and leaves critical technologies in the hands of a few providers. Open weight models, on the other hand, allow a broad community of researchers and developers to study their behavior, identify vulnerabilities, develop protection measures, and improve them over time. Just as open source software has shown that transparency can be safer than obscurity, AI safety may depend on giving more people the opportunity to test and strengthen the models society relies on. It enables rigorous benchmarking and evaluation, red teaming, and protections tied to actual and proven harm, rather than assuming closed systems are safer by default.
A strong AI ecosystem is not a given. There is an important opportunity for politicians to act. These include expanding access to computers for start-ups and researchers, investing in shared training resources (datasets, tools, assessment frameworks) and maintaining the frontier plural by avoiding premature restrictions on open models that stifle competition or drive innovation abroad. These measures must also consider how strong application layers can expand the confident use of AI across the economy.
When designing this ecosystem, policymakers should be careful not to confuse legitimate model development techniques with misappropriation. Distillation, or the practice of using the results of one model to train or improve another, is a widely used technique for model improvement, evaluation, and validation. It reflects a long tradition of learning, building, and improving existing technologies, a tradition that has helped drive innovation since the advent of the open source software movement. In contrast, unlawful attempts to extract value from closed models raise legitimate concerns. These concerns should be addressed through targeted legal and commercial frameworks, rather than wholesale restrictions on techniques that play an important role in AI innovation.
The age of AI can be an age of prosperity. With the right decisions, open-weight AI can expand opportunity, increase competition, expand America’s technology leadership, mitigate risk, and ensure that the benefits of this extraordinary technology are widespread throughout our economy. This future is worth building, and the United States should lead the way in building it.
American Innovators Network ● Andreessen Horowitz ● Arcee AI ● Arena ● Black Forest Labs ● Box ● CrowdStrike ● Dell Technologies ● Emergence Capital ● Hugging Face ● IBM ● The Linux Foundation ● Mariana Minerals ● Meta ● Microsoft ● Mistral ● Mozilla ● NVIDIA ● Palantir ● Perplexity ● Reflection ● Replit ● ServiceNow ● Telnyx ● Y Combinator
https://www.microsoft.com/en-us/corporate-responsibility/topics/open-weight/
