The battle between decentralized startups and Big Tech for the future of AI
Decentralized startups are positioning themselves more and more aggressively against the tech giants, and the strategy driving this movement involves a pretty bold combination of Artificial Intelligence and blockchain. The core goal is to redesign, from scratch, the way we think about and build infrastructure for so-called artificial general intelligence. This is not just about competing on features or price — it is about proposing a completely different architecture from the one that dominates the market today, controlled by a handful of corporations with practically unlimited resources.
Ben Goertzel, CEO of the ASI Alliance and SingularityNET, has been one of the most vocal figures in this debate. He emphasizes that for blockchains to reach the necessary scale, deep technical obstacles related to decentralization, scalability, and security will need to be overcome. Goertzel also stresses that decentralized AI needs to find concrete ways to compete with the large corporations currently dominating the sector.
The warning that raised a yellow flag in this discussion came from a place few people would have expected. Stripe, one of the largest financial services platforms on the planet, published its annual letter in February 2026, signed by cofounders Patrick and John Collison. In it, the two acknowledged quite directly that the current blockchain infrastructure is not ready to support what is coming. The focus of the warning is the technical limitations that prevent the full operation of agentic commerce at scale — the model in which Artificial Intelligence agents discover opportunities, make decisions, and execute transactions in a completely autonomous way, with zero human intervention in the process.
The analogy the Collisons brought up in the letter is especially helpful for understanding the scale of the problem. According to them, the current state of blockchain looks a lot like the internet in the 90s — a technology full of potential but still held back by engineering bottlenecks that need to be solved before mass adoption becomes viable. The barriers are not conceptual or theoretical. They are practical challenges around scalability and cost predictability that, if left unaddressed, could stall all the progress promised by agentic commerce and decentralized artificial intelligence. The Stripe founders classify these limitations not as permanent roadblocks but as engineering challenges that need to be solved before the economy can advance to the so-called Level 5 of fully autonomous commerce.
The challenge of scaling to billions of transactions per second
To put the size of this problem in perspective, we are talking about infrastructure that needs to be capable of processing somewhere between 1 million and 1 billion transactions per second 🤯. That number is not rhetorical exaggeration. In the Stripe report, the founders identified two main technical bottlenecks that prevent blockchains from serving as the rails for agentic commerce: cost predictability and transaction processing capacity.
When millions of AI agents start operating simultaneously on decentralized networks — negotiating resources, purchasing services, and closing contracts with each other — the volume of operations explodes in a way that no existing blockchain can absorb without compromising speed, cost, or security. This is a type of demand that simply did not exist a few years ago, and it now presents itself as the biggest technical bottleneck in the sector.
The most popular blockchain networks today, even those considered high-performance, still operate in the range of thousands or, at most, tens of thousands of transactions per second. The gap between that capacity and what agentic commerce demands is enormous. Solving this equation is not just a matter of increasing raw processing power. It involves rethinking consensus protocols, redesigning communication layers between network nodes, optimizing on-chain data storage, and creating fee pricing mechanisms that are predictable enough for Artificial Intelligence agents to plan their operations without unpleasant surprises along the way.
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Stripe itself is betting big on this transition. The company recently acquired Bridge, a stablecoin platform, and launched the Agentic Commerce Suite. These moves were designed to help businesses prepare for this shift while blockchain technology matures under the hood.
And this is exactly where the argument from decentralized startups gains traction. The thesis these projects defend is that trying to solve the scalability problem within monolithic, centralized architectures is an approach doomed to hit increasingly difficult limits. Instead of building a single massive system controlled by one company, the proposal is to create ecosystems made up of multiple interconnected networks, each optimized for a specific type of task, operating in a coordinated way and open to any participant.
Ben Goertzel and the vision for a truly open AI
Goertzel considered the Stripe prediction entirely plausible. He pointed out that conventional digital financial transactions, during peak hours, already reach the millions — and that is when they are mostly generated by humans through intermediaries. The shift to agentic commerce changes the scale by orders of magnitude.
Instead of a single person initiating an action, you have an entire team of agents operating autonomously, Goertzel explained. Instead of one entity, you have a whole squad generating transactions. This exponential multiplication of operations is what makes the need for new architectures so urgent.
For Goertzel, reaching the scale Stripe envisions requires overcoming fundamental obstacles that go beyond raw speed. You need to balance decentralization, scalability, and security — the famous blockchain trilemma. On top of that, agents cannot be confined to a single network. It is necessary to manage massive volumes of information generated by autonomous squads, enable direct peer-to-peer settlements, and implement what Goertzel calls advanced decentralized identity.
The solution, in his view, is not a single monolithic network but rather a system of specialized networks — something like a modern highway with dedicated lanes for buses, express traffic, and heavy freight. By separating traffic, we avoid congestion, Goertzel observed. That is exactly the kind of scalable architecture we need for agentic commerce: a network of shards, where each part does one thing well and interacts seamlessly with the rest.
SingularityNET, along with other projects that make up the ASI Alliance, is working on architectures that allow different Artificial Intelligence models to interact with each other in a decentralized way, using blockchain as a coordination and record-keeping layer. The idea is that instead of depending on a single AI provider for every task, agents can access an open network of specialized services, choosing and combining capabilities as needed. This model creates a dynamic marketplace where competition is driven by quality of service, not by control over the infrastructure.
The concentration of power in AI and the decentralized counterattack
The high-intensity race for supremacy in Artificial Intelligence is driving a massive consolidation of power. Unlike the decentralized nature of blockchain, the AI sector is becoming something of an oligarchy dominated by tech giants investing billions in proprietary infrastructure. This concentration of influence has raised serious questions about whether corporate control will override the public interest.
Even so, a resilient ecosystem of startups is launching a tactical counter-offensive. Using agility, niche specialization, and open-source collaboration, these smaller companies are betting that architectural diversity and ethical transparency will manage to break through the monolithic status quo.
Goertzel is pretty straightforward when talking about this landscape: SingularityNET and its partners do not come close to the size of companies like Google or Microsoft. But he says they are reaching a scale that allows them to compete more effectively, getting closer to the level needed to make decentralized AI the dominant form of artificial intelligence on the planet. One of the secret ingredients, according to him, is the power of diversity. Being decentralized allows you to bring together people, communities, AI algorithms, and datasets from all over the world, in contrast to the monolithic approaches taken by large centralized entities.
Goertzel added that this strategic diversity becomes particularly powerful in the current state of the industry, where many leading researchers are realizing that simply building bigger and bigger LLMs will not lead to artificial general intelligence. This is something we understood from the beginning, he stated, and it has guided the Hyperon approach to AGI and superintelligence developed by the team.
To demonstrate this belief in a cosmopolitan approach in practice, SingularityNET, in partnership with the AGI Society, organized this year’s AGI-26 conference, an event dedicated to exploring different interpretations and pathways toward artificial general intelligence.
Open governance as a pillar of the future of AI
Another important aspect of this decentralized approach is resilience. Monolithic systems, no matter how robust they are, have single points of failure. If the company that controls the network decides to change its policies, raise prices, or simply goes down, every agent and service that depends on it is affected. In a distributed architecture, that risk is diluted. No single participant has enough power to compromise the operation of the system as a whole. For agentic commerce, where AI agents need to operate continuously and reliably, this characteristic is not a luxury — it is a fundamental requirement.
Goertzel also shared his vision for how those involved in the sector can minimize the risk of AI being controlled by just a few entities or governments. In his view, open, decentralized, and democratic methodologies are needed across the entire artificial intelligence chain: from deploying and running AI systems at scale, to fair data sourcing, teaching broad human values to AI systems, and making collective decisions about their development.
In Goertzel’s view, combining open-source code with decentralized infrastructure and governance ensures that AI remains transparent, widely accessible, and highly beneficial for humanity and other sentient beings. This approach might sound idealistic to anyone who follows the tech market closely, but it gains momentum when you look at the growing concerns around algorithmic bias, misuse of personal data, and the lack of transparency in decisions made by proprietary Artificial Intelligence models.
What lies ahead for the decentralized ecosystem
The landscape taking shape for the coming years is one of intense technical experimentation. The decentralized startups on the front lines of this movement know that talk alone is not enough. They need to deliver solutions that actually work in practice, with low latency, predictable costs, and real scalability. Projects like the ASI Alliance, along with initiatives in Layer 2, advanced sharding, and new consensus protocols, are testing different paths to achieve the necessary performance. There is no single definitive answer yet, but the amount of research and development being invested in this direction signals that we are at a turning point.
Stripe’s acknowledgment that blockchain needs to evolve is, by itself, a significant signal. When a company of that size publicly validates that the technology has limitations — but that those limitations are engineering problems, not conceptual ones — it acts as a catalyst to attract more investment, more talent, and more attention to the problem. The comparison to the internet of the 90s is not just poetic. It carries a practical implication: whoever solves the infrastructure bottlenecks now will be positioned to capture a massive share of the value that agentic commerce will generate over the coming decades 🚀.
At the end of the day, the race between centralized and decentralized models of Artificial Intelligence is not just a technical contest. It is a battle over how the next generation of the internet will work, who will have access to its benefits, and who will hold power over its decisions. The decentralized startups betting on the combination of AI and blockchain to scale their operations are, at their core, proposing a different model for the future. There is still a lot of engineering work ahead, many scalability challenges to overcome, and plenty of proof to deliver. But the fact that this conversation is already happening at the highest levels — involving everyone from billionaire fintech founders to artificial intelligence pioneers — shows that the topic has moved beyond speculation and become an urgent priority.
Frequently asked questions
- What is agentic commerce?
Agentic commerce is the ability of AI agents to discover opportunities, make decisions, and execute transactions independently, without human intervention. - What are the main blockchain challenges for AI transactions?
The challenges include cost predictability and the need to process between 1 million and 1 billion transactions per second. - How is Stripe preparing for the future of agentic commerce?
Stripe acquired the stablecoin platform Bridge and launched the Agentic Commerce Suite to help businesses adapt to this transformation. - What is the significance of the AGI-26 conference?
AGI-26 brings together researchers and professionals to explore different approaches toward artificial general intelligence, promoting decentralized methodologies that benefit humanity. - What is the Hyperon approach mentioned by Goertzel?
Hyperon is the approach developed by Goertzel’s team to achieve AGI and superintelligence, based on the premise that simply scaling up LLMs is not enough to reach general intelligence.
