Dear Singularitarians,

Ask yourselves this: are we moving into a world where AI empowers humanity, or one in which a handful of powerful corporations controls access to the most advanced technology in history? 

Naturally, the debate around AGI’s future is (and always has been) deeply divided.

Optimists envision a utopia where AI solves global crises, extends human lifespans, and democratizes knowledge.

Pessimists warn of an existential catastrophe, where AGI could either turn against humanity or be monopolized by corporate and governmental powers, leading to extreme inequality, mass surveillance, and the erosion of personal freedoms.

[Read more: The Tribalization of AGI Ethics]

Somewhere between these extremes lies the important question: who controls AI, and how do we ensure it benefits everyone rather than just a privileged few?

Today’s AI landscape is heavily guided by a handful of corporations that dominate the space, controlling the vast amounts of data and computational resources required to develop state-of-the-art AI models. 

AI is shaping everything from search engines to finance, healthcare, and governance, yet a select few determine how it develops, who benefits, and who gets left behind. The monopolization of AI raises ethical concerns, risks of surveillance, and the potential for a dystopian future where decision-making is dictated by corporate interests rather than human welfare.

Decentralization is the natural counterbalance to this trend, and blockchain technology provides the framework needed to distribute AI’s power more equitably. By removing the need for central authorities, decentralization ensures that AI development, access, and governance can be democratized.

Instead of being controlled by a single company’s internal policies, AI could be built on open, transparent, and trustless systems where ownership, computation, and data usage are fairly distributed.

AI’s Growing Monopolization and the Risks It Poses

The AI industry is becoming increasingly centralized because of the immense resources required to develop powerful models. Training the latest and greatest in AI systems demands high-performance GPUs and vast datasets. 

Big corporations control the cloud services necessary for large-scale training, leaving independent developers with little to no access. AI models today rely on data sourced from billions of users, but these users have no control over how their information is collected, stored, or monetized.

The recent release of DeepSeek’s open-source AI model was one step toward shifting the narrative — while bringing open source to AI and breaking the dominance of corporate-controlled systems. (Unlike proprietary models from OpenAI and Google, DeepSeek’s approach allows developers worldwide to access, audit, and enhance the technology, fostering greater transparency and innovation. A step in the right direction, at least.)

Data privacy has become an afterthought in the race for AI “supremacy.” With centralized entities holding the keys to the most valuable datasets, there is no guarantee that user information is handled ethically. AI monopolies also dictate access, meaning only those who can afford high-cost API access or enterprise contracts can use advanced models. This exclusion stifles smaller businesses, independent researchers, and open-source projects from competing on equal footing. More recently, there has been ongoing speculation that DeepSeek may have inappropriately used OpenAI data.

Beyond commercial concerns, monopolized AI threatens societal balance. Algorithmic biases embedded in AI models can disproportionately affect certain demographics, shaping narratives in search results, social media feeds, and automated decision-making systems. Without transparency, these biases remain hidden, reinforcing discrimination and misinformation.

If AI development is centralized and under the exclusive control of a few corporations, the world risks a future where economic, political, and social outcomes are dictated by profit-driven algorithms.

Blockchain’s Role in the Decentralized AI Puzzle

Blockchain’s decentralized architecture offers a way to challenge AI monopolization by shifting control away from single entities and distributing it across a network of participants.

The technology functions as a trustless system where data, transactions, and operations are immutable and transparent. When integrated with AI, blockchain can break the cycle of centralization in several ways.

Many different initiatives are seeking to foster an open, inclusive, and decentralized approach to AI development, such as the Artificial Superintelligence (ASI) Alliance.

Formed by SingularityNET, Fetch.ai, Ocean Protocol, and Cudos, the ASI Alliance is focused on decentralizing AI at every layer of the technology stack, from compute power to data access, from model training to AI services.

The ASI Alliance recognizes that AI monopolization is not just about control over models—it’s about control over infrastructure.

Compute power is centralized within the hands of cloud giants, making it nearly impossible for independent developers to compete. The ASI Alliance aims to change this by integrating decentralized compute networks, where AI models can be trained and run across distributed systems rather than corporate-owned data centers. CUDOS, member of the ASI Alliance, addresses the issue of centralized compute with a blockchain-based decentralized cloud computing platform designed to make computing more cost-efficient, scalable, and decentralized. 

Another potential bottleneck could be data, with major corporations hoarding vast datasets while smaller AI projects struggle with access. Blockchain-based marketplaces like Ocean Protocol provide a way to democratize data ownership, allowing users to control their own data and make it available for AI training without surrendering privacy. 

Blockchain offers a clear path toward decentralizing AI, and it does so in a variety of ways. The key lies in its fundamental properties—decentralization, transparency, and security. By eliminating centralized control, blockchain ensures that AI development and access are no longer dictated by a handful of powerful entities.

Blockchain can help create a decentralized infrastructure for AI model training and deployment.

Instead of AI models being trained and hosted on centralized cloud services like Amazon Web Services (AWS) or Google Cloud, blockchain-based networks distribute computing power across a decentralized network. This allows AI training and inference to take place without reliance on a few corporate-owned data centers.

Blockchain enhances data security.

Rather than data being harvested and controlled by corporations, blockchain-based solutions like Ocean Protocol allow individuals and organizations to share, sell, or restrict access to their data on their own terms. This shift eliminates the monopolistic grip companies have over datasets and ensures that AI models are trained on diverse, ethically sourced data.

Blockchain can allow for transparent governance.

AI models today are often described as “black boxes” because their decision-making processes remain opaque. Blockchain can record AI training steps and inference processes on an immutable ledger, providing verifiable proof of how models reach their conclusions.

This approach minimizes risks associated with bias, manipulation, or unethical AI use. In decentralized AI ecosystems, governance mechanisms could also be coded into smart contracts, ensuring that models are audited and updated in a transparent, community-driven manner rather than being controlled behind closed doors.

Is Balancing Centralized and Decentralized AI the Future?

Preventing an AI monopoly is not a challenge that can be solved by a single technology or approach—it requires a fundamental restructuring of how AI is built, accessed, and governed.

Blockchain is one piece of this puzzle, offering a way to decentralize data ownership, secure AI transactions, and create transparent governance structures. But blockchain alone is not enough.

The true battle against AI monopolization requires a decentralized infrastructure for compute power, open-source AI models, community-driven governance, and alternative AI marketplaces that can break the stranglehold of corporate-controlled ecosystems.

The future of AI does not have to be dictated by a few corporations with monopolistic power over data and compute. The technologies to decentralize AI exist today—what remains is the collective effort to integrate them, scale them, and fight against the entrenched interests that seek to maintain control.