What Good Is AI On Blockchain If No One Can Use It Easily In Practice

Forbes

a day ago

The interaction of Artificial intelligence (AI) and Blockchain are emerging. (Photo Illustration by ... More Budrul Chukrut/SOPA Images/LightRocket via Getty Images)
An increasing number of blockchains is actively seeking to integrate AI capabilities, but this 'AI on blockchain' growth is accompanied by significant challenges, most notably the issue of "chain silos", which fragment the sector and can hold back the full realization and utility of Decentralized AI (DeAI) potential. Afterall, if there's no widely available use case scenario, how do we continue the narrative and innovation of the currently already-overhyped DeAI sector?
Take blockchain-native autonomous AI agents as an example, while a precise census of AI agents on the blockchain is elusive, the available data strongly suggests a rapidly growing and dynamic landscape. The number is likely in the hundreds to potentially thousands when considering individual deployed agents across various platforms and projects. All these AI agents reside in a scattered landscape of chains. It's like when computers could not communicate with other computers before the World Wide Web was invented, as a result, the full potential of computers could not be unleashed.
While centralized AI suffers from data silos controlled by corporations, DeAI risks creating new silos at the blockchain level if interoperability is not prioritized, blocking DeAI's full potential.
This fragmentation is not merely about data residing on different ledgers. It extends to the unique protocols, smart contract languages, virtual machine environments, consensus mechanisms, and overall operational logic of each distinct blockchain.
For example, a DeAI application built to leverage the specific features of Ethereum and its EVM may not be able to natively interact with or utilize AI models deployed on a non-EVM chain like Solana without resorting to complex and potentially insecure bridging solutions. Similarly, AI agents trained within one chain's environment may find it difficult to operate effectively elsewhere. This leads to scenarios where separate databases or non-communicating tools on different chains effectively become isolated islands of DeAI activity.
Fragmentation issues, similar to those seen in decentralized identity systems or healthcare electronic health records due to platform incompatibilities, can limit the scalability and impact of DeAI solutions.
The DeAI community's vision extends beyond isolated applications on single blockchains. Building "Super AI Applications" is becoming a key mission for many.
Imagine it as an all-encompassing platform or a network of integrated services that accommodates diverse AI functionalities – such as sophisticated data analysis, distributed model training, autonomous agent deployment, and complex decision making – across different, often varied and disparate blockchain environments. Such an application would not be confined to the resources or limitations of a single chain.
On one hand, specialized Layer 1 blockchains like Bittensor, and Gensyn are being engineered from the ground up with DeAI specific requirements in mind. These platforms aim to provide optimized environments for tasks like high-volume data processing, intensive computation, or unique AI model incentive mechanisms, based on the premise that general-purpose L1s may not be ideally suited for the distinct demands of DeAI.
On the other hand, many prominent DeAI Apps and protocols, such as Ocean Protocol and SingularityNET, initially launched on established, general-purpose L1s like Ethereum and are now pursuing multichain strategies.
Then a key debate arose: Commit to a specialized L1 for potentially superior tailored performance but a smaller initial ecosystem, or build on/across established L1s/L2s to tap into broader reach but with possible limitations in AI specific optimizations?
Inevitably, successful DeAI platforms will increasingly rely on reliable and functional cross-chain capabilities to access wider markets, liquidity, and data sources, regardless of their foundational architecture, thereby avoiding the very 'silo-zation' they aim to overcome.
Realizing the Super AI APP vision is charged with significant challenges though.
Despite these challenges, industry players are proactively exploring solutions and standardization for DeAI Super Applications to cross chain, including leaders like BSC and Solana, although this is still at an infant stage. In the meantime, innovations in protocols, platforms, and conceptual frameworks are also taking shape to construct a more interconnected DeAI ecosystem which can potentially become real utility for even novice internet users. This trend is inevitable, driven by the enormous potential underneath AI and blockchain's synergistic benefits. The inherent characteristics of blockchain can address some of AI's most pressing challenges, while AI can unlock new functionalities and efficiencies for decentralized systems, such as network optimization and intelligent resource allocation, or automated security auditing, and more. For the benefits and advantages of AI on blockchain over centralized AI, I've discussed in my previous articles:
How To Solve Data Collection Challenges For Your Business's AI Needs
DeepSeek's Lesson: The Future Of AI Is Decentralized And Open-Source
Top 5 Decentralized Data Collection Providers In 2025 For AI Business