Near AI Infrastructure Is Expanding While Markets Look the Other Way
NEAR Protocol has long been a divisive buy-and-hold story for crypto investors. For the vast majority, it can be summarized by a single number: $1.19. The token price that NEAR's native token is trading at in late March 2026, having careened from its cycle highs as trading chat teems with a now-familiar refrain of bearish noise.
Lost in this price-obsessed chorus is that NEAR has, almost imperceptibly, quietly built out one of crypto's most powerful near AI infrastructure stacks, a buildout that's redefined, under the hood, what the protocol is at its core. The question of what is NEAR Protocol in purely blockchain terms, a Layer 1 chain with Nightshade sharding and a developer-friendly software stack, is an answer that hasn't been true for over a year. That's because the protocol has been pouring engineering capital into AI agent architectures, on-chain inference, and decentralized data pipelines. The market hasn't seen fit to price any of it in.
The Quiet Pivot Nobody Watched
NEAR's evolution into an AI backbone has been gradual, and below the near news cycle for the most part. While meme coins and ETF flows were the defining stories of the broader crypto ecosystem all throughout 2025, Near Protocol and related developer teams were working away in the background on a multi-agent AI assistant framework, an intent-based transaction layer that's ML model-driven, and tools for bootstrapping autonomous AI agents on-chain.
The thinking behind the approach is simple. Layer 1 blockchains are commodities. Ethereum, Solana, and a dozen other chains are competing over the same DeFi and NFT activity with a fast-converging feature set. "Just the fastest chain" is no longer a long-term competitive strategy. So instead, the protocol has repositioned itself as infrastructure for AI-native apps, a category that barely existed two years ago.
This has come in stages. The chain-abstraction layer that launched in mid-2024 introduced account aggregation across blockchains. This meant users no longer needed separate NEAR wallet addresses on each network. That feature in and of itself wasn't AI. It was frictionless interoperability for software agents that need to move between chains with zero human involvement. And that's an AI problem.
And then there were the AI assistant integrations, tools that let developers build agents capable of carrying out multi-step blockchain transactions via natural language prompts. These aren't chatbots. They're autonomous programs that can manage portfolios, place trades, and interact with DeFi protocols. The infrastructure to support them is where NEAR has been pouring its engineering budget.
What the Near AI Stack Actually Does
Strip away the marketing speak and the NEAR AI stack can be divided into three distinct layers based on function.
The first layer is a decentralized inference network. AI models can compute over a distributed network of nodes, instead of being hosted centrally (AWS, Google Cloud, etc.). It's an important distinction because AI inference (running a model you've already trained to generate output) is an expensive and centralized process. NEAR's solution is to decentralize that cost across its network while also removing centralized points of failure.
The second layer is an agent framework. This is a suite of developer tools and APIs that gives AI agents the ability to own assets, sign transactions, and autonomously interact with smart contracts. Each agent also gets their own on-chain identity that comes with a wallet and transaction history. Agents are already in use: several DeFi protocols on the Near network are using agents for liquidity automation.
The final layer is a data marketplace. AI models need data to be trained and NEAR has built the underlying infrastructure to buy and sell datasets on-chain with provable provenance. It's a first iteration product, but a real use case. Finding data to train on is a massive bottleneck in AI development: where is your data coming from? Do you actually have the rights to use it?
NEAR is less vertically integrated than some other blockchain-AI projects (RLC coin and iExec, for example, facilitate a decentralized cloud computing marketplace), or protocols with a more specific focus on a GPU marketplace. NEAR is instead angling to own the stack from data all the way to inference to agent execution (seeking to solve all the pieces of the AI pipeline). Whether or not that ambition will match its execution is a different question entirely.
Developer Numbers Tell a Different Story Than Near Price
NEAR is a great example of a token that's been uncoupled from developer activity. Near price is down ~75% from 2024 highs, and a number of key on-chain developer activity signals are higher on the Near network. Monthly active developers have been rising on NEAR up until late 2025/early 2026 while the network's market cap has collapsed, now sitting at $1.65 billion.
This isn't a phenomenon exclusive to NEAR. Ethereum had a version of this around its 2018-2019 bear market where the price cratered and the developer activity around it was setting the stage for the DeFi explosion the following year. The example isn't exactly analogous (Ethereum had significant network effects already baked in), but it's a known signal in crypto markets that when prices fall, the traders will run, but the builders will stay.
What's different here is the type of developer showing up. Traditional metrics for blockchain developer activity center on smart contract deployments and dApp launches. A notable portion of new development activity on NEAR is aimed at AI agent tooling, model deployment scripts, and inference node operation. These developers aren't building the next DEX or lending protocol. They're building software that will use the blockchain as a coordination layer for AI systems. The $283 million in 24-hour trading volume as of late March is enough to show that the token isn't illiquid, but merely undervalued relative to its technical buildout, or overvalued relative to present adoption, depending on what metrics you weigh more heavily.
Why Standard Blockchain Metrics Miss the Picture
Most NEAR Protocol price prediction outlooks are focused on the usual metrics: TVL, trade volume, active addresses. These proxies appear to track DeFi activity reasonably well. They ignore AI infrastructure use completely. When an AI agent makes a portfolio rebalance on NEAR, transactions get created. They look like any other DeFi activity to on-chain data scrapers. Computation taking place in an inference process running on NEAR's distributed validator nodes doesn't get counted into TVL figures. Marketplace data transactions have very low dollar volume but represent a whole new category of blockchain utility.
The disconnect means that many of the conventional NEAR Protocol price prediction outlooks (the majority of which were published last year and thus expected relatively little growth) are underestimating the coming AI infrastructure buildout. One near price prediction from Cryptopolitan pegs the peak price to $5.566 in 2029 and $9.301 in 2032. Both estimates are built from historical price performance and adoption curves. If the AI stack can realize real-world utility, they're lowballs. If not, Near token is back to competing on the same Layer 1 vectors that it's already losing on to Solana and Ethereum.
Three Bets NEAR Is Making on AI's Future
Really all this comes down to is 3 big bets that the NEAR team is making on how AI and blockchain are going to interact over the next 3-5 years.
AI agents need on-chain identities. Verifiable identities, transaction histories, asset custody, etc. become non-negotiable as more and more advanced autonomous software systems come to control economic activity. These things can be partially replicated on traditional databases, but the immutability and composability property is extremely hard to reproduce in a purely centralized context. The bet is that NEAR, with its chain-abstraction layer, becomes the de facto choice for agent identities spanning multiple blockchains.
AI inference will decentralize. Today nearly all AI compute takes place on centralized infrastructure. As it's used more pervasively across the financial stack, NEAR is betting market demand for censorship-resistant distributed inference will increase. That's been the thesis that iExec and Golem have been chasing, but NEAR is folding it into a broader stack vs. offering it as a stand-alone service. Ethena price, affected by the same downtrend, is a good example of how DeFi-specific innovations can create their own demand curves independent of the wider market. NEAR's AI stack may be able to do the same.
Data provenance will be a regulatory requirement. Governments are already starting to grapple with how to regulate AI training data. It's very likely verifiable data lineage will be required of model developers at some point in the near future. NEAR's data marketplace is early to this space, but would be well positioned to service that need if and when it materializes.
Each of these bets has massive execution risk. Decentralized inference networks are slower and more expensive than centralized ones. Agent frameworks are in their research stage. Data marketplaces haven't found product-market fit in crypto anywhere yet.
What the Market Isn't Pricing
This isn't an argument that NEAR is "sure" to be one of the big winners from this AI infrastructure buildout. It's that the market is currently making zero allowance for that possibility whatsoever. At $1.19, with a $1.65 billion market cap, the NEAR token is priced almost entirely as a struggling Layer 1 blockchain. The largest slice of the protocol's current engineering production, the AI infrastructure buildout, is being valued at an effective market cap of close to zero dollars.
Short-term traders are up against negative market sentiment as well as macro headwinds from geopolitical events. Listing on Robinhood in March 2025 opened the token up to over 23 million funded accounts, but hasn't created sustained buying pressure. Longer-term holders have a different calculus. If just one of NEAR's 3 AI bets works out, the protocol's TAM is multiple times bigger than the current share of Layer 1 blockchain activity that's deflating its market price.
The developer data suggest the buildout is being taken seriously. The price isn't. It's that divergence, between construction and pricing, that's the contrarian reason to care about near AI infrastructure today, even if the chart goes the other way from here.
