The global AI race has caught fire this year, with emerging players challenging the dominance of established models and shifting the balance of influence. In China, Z.ai, a startup valued at roughly $3 billion, is building its presence through partnerships with Huawei and Alibaba Cloud to scale its GLM-4.5 model. In the U.S., OpenAI continues to lead with GPT-5 setting new benchmarks, announcing recently a major computing deal with AMD for up to 6 gigawatts of GPUs and warrants for 160 million shares, highlighting the next phase of AI infrastructure expansion.
Headlines frame this as geopolitical; China versus the United States, East versus West, but this misses the real battle: who will be the first to create a sustainable model prioritizing data and intellectual property ownership? It’s about who can preserve the fundamental rights to data and IP for the individuals who validate, create, and interact with AI systems. This is where the future of AI will be decided.
The True Stakes of Data and IP Ownership
AI models thrive on your data – everything from your digital conversations, to your creative work and your personal information. But who owns this data? The current Web2-dominant system has dramatically shifted the balance of power in favor of big players. When you interact with mainstream AI tools, your data becomes their asset, your IP becomes their training material, and your privacy becomes their commodity.
And this isn’t just a technical or business issue: it’s a human rights issue. As AI becomes increasingly integrated into our daily lives, we must maintain control of our digital footprints. Leveraging the innovations offered through decentralized technologies allows users to retain control over their data and IP. Imagine a world where you can monetize your knowledge in perpetuity without being replaced by an AI you trained. It’s in stark contrast to the current model, where your data enriches corporations while potentially making your skills obsolete.
AI’s Current Pain Points are Due to Web2’s Limitations
Tech giants like Google, Amazon, and OpenAI have undeniably played a crucial role in advancing AI. They’ve built sophisticated models, scaled operations, and brought AI’s potential mainstream. They’ve reshaped industries and expanded our understanding of what’s possible. We saw that recently, when OpenAI had to beg users to slow their usage of ChatGPT to create Studio Ghibli-style images because GPUs couldn’t keep up with the demand.
However, this dominance comes at the cost of losing collective control of AI’s trajectory – they own the data, dictate the narratives, and create near-insurmountable barriers to entry for emerging players. This centralization of power stifles competition and limits innovation in order to serve corporate interests over broader user needs.
The reversal we saw earlier this year of U.S. export controls on Nvidia’s H20 AI chips to China, followed by a massive 300,000-unit order, also highlights the volatility of centralized control and policy swing. Nvidia’s stock has risen ~37% in 2025, bolstered by this policy change and strategic partnerships with Alibaba, which is simultaneously investing roughly$53.4B in AI infrastructure and launching its own Qwen3-Max model with over 1 trillion parameters. Market access can shift overnight due to lobbying or political change, underscoring the need for systems not dependent on a few gatekeepers.
Decentralized AI Offers a Paradigm Shift in Innovation
Conversations around AI shouldn’t just be about which jobs might be replaced. It should be about who profits from AI’s productivity. Under centralized ownership, a small group reaps the rewards while many are left with limited access or control. The benefits of AI should be distributed equitably among everyone who contributes to its development and use.
Decentralized AI reimagines development, ownership, and value. Contributors, developers, annotators, users – anyone involved in the AI process – retain ownership of their creations and can monetize contributions. That ethos is increasingly resonating with investors and users, as U.S. retail capital rotates away from mega-cap AI names toward smaller, more open communities and platforms. This trend goes beyond culture and should be foundational to a sustainable ecosystem.
The Race for Competition vs Collaboration
Forward-thinking organizations should recognize companies like DeepSeek as potential collaborators, not competitors. Chinese firms have doubled down on cross-company partnerships and model-sharing initiatives, building momentum for a cooperative ecosystem even under export-tight restrictions. By focusing on shared resources rather than cutthroat competition, there’s greater potential for creating quality AI models without the massive investment that was once thought necessary.
This shift is already affecting investor sentiment and valuation models across the industry. In fact, DeepSeek and other competitive models are already integrated into larger AI suites, demonstrating how competitors can become collaborators in this new ecosystem.
The Future of AI Offers Challenges and Opportunities
While we celebrate AI’s technical progress, its current trajectory is constrained by centralization: closed-source systems limit transparency, corporate control shapes priorities, and users are left vulnerable to pricing and policy shifts. Global tension between centralized and open development continues, with China calling for inclusive AI governance at and the release of its Global AI Governance Action Plan at the World Artificial Intelligence Conference, contrasting sharply with the U.S.’s domestic-first, deregulated approach.
Meanwhile, Meta and OpenAI continue to push out frontier models with minimal global oversight, fueling backlash from open-source advocates.The question is no longer whether AI will transform society, but who gets to shape that transformation.
Moving Together Towards Human-Centered AI
As the AI arms race accelerates, political rivalry is secondary to the more fundamental conversation we should focus on: protecting human rights in the digital age. By emphasizing decentralization, data ownership, and equitable distribution of AI’s productivity benefits, we can ensure that its future serves everyone rather than concentrating power in the hands of a few corporations.
The true battle isn’t about who builds the most powerful models, but about who builds the most equitable and sustainable AI ecosystem. The real winner won’t be determined by who creates the smartest algorithm, but by who establishes the fairest system: one where individuals retain ownership of their data, receive fair compensation for their contributions, and maintain their privacy and autonomy in an increasingly AI-driven world.
