The intersection of artificial intelligence and blockchain technology has moved from theoretical discussions to tangible infrastructure development, and NEAR Protocol is positioning itself at the center of this convergence. With NEAR trading at $5.37 on June 24, 2024 — up nearly 39% since the start of the year — and its total value locked tripling from $90.7 million to over $324 million in the first half of 2024, the protocol is demonstrating that AI-blockchain integration can drive real network growth.
The Synergy
The synergy between AI and blockchain is rooted in complementary capabilities. Artificial intelligence excels at pattern recognition, data processing, and autonomous decision-making, while blockchain provides the trustless infrastructure, transparent data provenance, and economic incentives that AI systems need to operate at scale without centralized gatekeepers. NEAR Protocol’s architecture is particularly well-suited for this intersection because of its sharded design, which allows the network to scale compute capacity as demand from AI workloads increases.
NEAR’s approach to AI integration is multifaceted. The protocol’s “chain abstraction” layer allows AI agents to interact with multiple blockchains through a single interface, removing the friction that has historically limited cross-chain AI operations. This means an AI agent can monitor markets on Ethereum, execute trades on Solana, and manage liquidity on NEAR — all without requiring separate infrastructure for each chain.
The protocol’s low transaction costs, averaging fractions of a cent, make it economically viable for AI agents to execute thousands of micro-transactions — a frequency that would be prohibitively expensive on networks with higher gas fees. This is essential for AI-driven applications like automated market making, real-time portfolio rebalancing, and high-frequency data analysis on-chain.
AI Use Cases in Web3
Several concrete AI use cases are emerging on NEAR and similar platforms. AI-powered autonomous agents are being developed to manage DeFi positions, automatically adjusting lending ratios, shifting liquidity between pools, and hedging positions based on market conditions. These agents require the reliable, low-cost execution environment that NEAR provides.
Decentralized AI model training represents another frontier. Projects like Bittensor, which was highlighted in a RAND Corporation policy primer published on June 24, 2024, are creating networks where participants contribute compute resources to train AI models and are rewarded with tokens. NEAR’s infrastructure can support the data availability and compute coordination layers that such networks require.
AI-driven content moderation and fraud detection in decentralized social platforms is also gaining traction. By running inference models on-chain or on NEAR’s compute layer, these applications can automatically flag malicious content or suspicious transactions without relying on centralized content moderation teams. This aligns with the Web3 ethos of decentralized governance while addressing the practical need for content quality and safety.
The emergence of DePIN (Decentralized Physical Infrastructure Networks) further strengthens the AI-blockchain connection. Projects building decentralized compute networks, sensor arrays, and wireless infrastructure generate massive datasets that AI models can process, with blockchain providing the incentive layer and data provenance guarantees.
Data Privacy Implications
The convergence of AI and blockchain raises significant data privacy questions that the industry must address proactively. AI models require vast amounts of data for training, and the transparent nature of blockchain creates tension between the need for data accessibility and user privacy. NEAR Protocol is exploring privacy-preserving computation techniques, including zero-knowledge proofs and secure multi-party computation, that could allow AI models to train on encrypted data without exposing individual user information.
The regulatory landscape around AI and data privacy is also evolving rapidly. The European Union’s AI Act, combined with GDPR data protection requirements, creates compliance obligations for any platform processing European users’ data with AI systems. Blockchain platforms that integrate AI must design their systems with these requirements in mind from the outset, rather than attempting to retrofit compliance after deployment.
NEAR’s approach to user accounts, which uses human-readable names instead of public addresses, provides a foundation for selective data disclosure. Users can choose what information to share with AI-powered applications while maintaining control over their core identity and financial data.
The Innovation Frontier
Looking ahead, the most transformative applications of AI on blockchain may be those that are not yet fully imagined. Autonomous AI agents that own and manage blockchain assets, negotiate contracts with other agents, and participate in governance decisions represent a fundamentally new paradigm for both AI and distributed systems. NEAR’s infrastructure is being designed to support these “AI-native” applications, with features like meta-transactions that allow agents to operate without needing to manage gas tokens directly.
The Flipside Crypto report published this week highlights NEAR’s impressive growth metrics: 231.8 million transactions in May 2024, a 162% increase from January, and quarterly new wallet creation surging from 966,000 in Q1 2023 to nearly 18.4 million in Q2 2024. These numbers suggest growing adoption that will only accelerate as AI-powered applications mature.
Cross-chain AI orchestration is another emerging frontier. As the blockchain ecosystem becomes increasingly multi-chain, AI agents that can seamlessly operate across networks will become essential infrastructure. NEAR’s chain abstraction and account aggregation features position it as a natural hub for these cross-chain AI operations.
Concluding Thoughts
The AI-blockchain convergence is not a passing trend but a structural shift in how both technologies evolve. NEAR Protocol’s combination of scalable infrastructure, low costs, and developer-friendly tooling makes it a compelling platform for builders at this intersection. The data from the first half of 2024 — surging TVL, transaction volumes, and user growth — suggests the market is beginning to recognize this potential. As AI capabilities continue to advance and blockchain infrastructure matures, the protocols that bridge these two technological revolutions most effectively will capture disproportionate value and developer mindshare.
Disclaimer: This article is for informational purposes only and does not constitute financial advice. Always conduct your own research before making investment decisions.
NEAR TVL tripling from 90M to 324M in six months is no joke. the sharded architecture actually handles AI workloads better than most L1s
TVL tripling means nothing without knowing how much is incentivized. show me organic demand then ill be impressed
Troy W has a point about incentivized TVL. that 324M number needs context on how much is from token emissions vs real usage
exact same thing happened with Solana in 2021. TVL looked massive but 70% was incentive farm dump loops. need sustained usage not emissions
Troy W. nailed it. the real metric is daily active addresses interacting with AI contracts, not raw TVL
chain abstraction is the real play here. NEAR letting users interact with multiple chains without managing bridges is huge for AI model deployment
chain abstraction for AI model deployment is the actual use case nobody talks about enough. cross-chain inference without bridge headaches
data_plumber cross-chain inference is huge but who pays for compute? the tokenomics of AI on-chain still feel unresolved to me
39% YTD gain while BTC is flat is telling. institutional money is clearly rotating into AI infra plays
^ and the 5.37 price point is still early. compare that to ETH or SOL and the upside for AI-related infrastructure tokens is clear