By Blumefield | July 13, 2026. The fight over the enterprise AI agent standard has stopped pretending to be a friendly research exercise. The biggest names in enterprise software have drawn a line, and the coalition behind the Agentic Resource Discovery specification, better known as ARD, has hardened into something that looks a lot like a bloc. This AI agent standard now carries the weight of Google, Microsoft, Salesforce, Nvidia, Databricks, Cisco, GitHub, Hugging Face, ServiceNow and Snowflake. Two names are conspicuously absent from that roll call, and everyone in the room knows exactly who they are.
A line drawn through the agent economy
The absentees are Anthropic and OpenAI, the two labs that have spent the last eighteen months convincing the market that they own the future of agentic computing. The contest over the next AI agent standard is no longer a quiet technical debate about JSON manifests. It has become the opening move in a fight over who controls the plumbing of the autonomous enterprise, and the incumbents have decided they would rather write the rules than rent them.
For a category that barely existed two years ago, the stakes have escalated with startling speed. Whoever defines how software agents find, evaluate and connect to one another effectively sets the terms on which every future workflow gets built. That is why a draft specification most executives could not describe in a sentence has become one of the most consequential documents in enterprise technology.
What Agentic Resource Discovery actually does
At its core the ARD proposal answers a deceptively simple question. When an autonomous agent needs to complete a task, how does it discover which tools and other agents exist, decide which one to use, and confirm that connecting to them is safe? Today the answer is almost always bespoke engineering. Every autonomous workflow is hand wired, which is precisely the friction that has kept enterprise deployments slow and expensive.
The AI agent standard tackles this with two primitives. The first is a static file, an ai-catalog.json manifest, that an organisation publishes at a well known path on its own domain. The second is a registry API that crawls those manifests, indexes them, and returns ranked matches to a natural language query. An agent handling a procurement request could describe what it is trying to accomplish and let the registry surface the approval system, the budget tool and the vendor database, with no developer hardcoding a single connection. The specification, published under an Apache 2.0 licence and currently sitting at a v0.9 draft, builds on the AI Catalog data model developed inside the Linux Foundation. You can read the working draft on the project's public repository.
The design is deliberately federated. No single company owns the registry, and each enterprise keeps control of what it exposes and to whom. That architecture matters, because it lets rivals adopt a shared AI agent standard without handing a competitor the keys to their customer relationships. Microsoft, which co-authored the spec, framed it as a discovery layer rather than a walled garden in its own developer briefing, and the coalition has been careful to describe ARD as complementary to existing protocols rather than a replacement for them.
The two names missing from the list
The politics are more revealing than the plumbing. ARD is explicitly positioned to sit alongside Anthropic's Model Context Protocol, the connective tissue that quietly became the default way to wire agents to tools after its launch in late 2024. You can find the MCP documentation on Anthropic's protocol site, and its ubiquity is precisely the problem the incumbents are trying to route around. When one lab's standard becomes the water the whole industry swims in, the companies that sell the applications underneath start to feel like tenants.
That is the subtext of the absence. Anthropic and OpenAI built their enterprise strategies around a chatbot at the centre of the workflow, the model as the front door through which everything passes. ARD encodes a different worldview, one where agents operate autonomously inside existing software ecosystems and the conversational interface stops being the bottleneck. In that world the value accrues to whoever owns the catalog of capabilities, and the members of this coalition already own the applications most enterprises actually run.
None of the participants will say out loud that the goal is containment, and technically they are telling the truth when they call ARD complementary. But standards are rarely neutral. A discovery layer that favours integration with Google Workspace, Microsoft 365 and Salesforce is a discovery layer that keeps those subscriptions growing, and a lab selling a general purpose model has every reason to worry about being relegated to a commodity slot inside someone else's catalog.
Why a discovery layer is worth fighting over
To understand why an obscure manifest format has drawn this much firepower, follow the money through the stack. The models themselves are commoditising fast, with capable systems now available at a fraction of last year's prices. The durable margins in agentic computing will not sit in the model layer at all. They will sit in orchestration, in the connective infrastructure that decides which agent does what and gets paid for the privilege of being the default.
Whoever controls the AI agent standard for discovery controls the on ramp. If ARD becomes the mechanism through which enterprise agents find their tools, then any product that fails to publish a compatible manifest risks becoming invisible to automated workflows, present in theory but unreachable in practice. That is an enormous lever, and it explains why companies that compete ferociously in every other market were willing to co sign the same document. They would each rather share a standard they collectively influence than submit to one a rival dictates.
There is a defensive logic here too. For the past two years the incumbent software vendors have lived with a nagging fear that autonomous agents would hollow out their franchises, turning decades of accumulated product surface into interchangeable back ends behind a chat window. Backing a common AI agent standard is how they reassert relevance. By making their platforms the easiest things for any agent to discover and trust, they turn the agent wave from an existential threat into a distribution channel that flows through their own catalogs.
The standards war has only just begun
The comfortable framing is that all of this can coexist. ARD handles discovery, MCP handles tool connections, Google's own Agent2Agent protocol handles agent to agent messaging, and the Linux Foundation stitches the governance together so nobody has to choose. For now that layered story mostly holds, and the coalition is right that the protocols are technically compatible. But interoperability on paper has a way of curdling into competition in practice once real revenue is at stake.
The likelier outcome is a period of overlapping, jostling standards in which adoption, not elegance, decides the winner. The coalition backing this AI agent standard has distribution on its side, since its members already sit inside the software estates of nearly every large enterprise on earth. Anthropic and OpenAI have momentum and developer affection, which has toppled incumbents before. What comes next will be decided less in specification documents than in procurement meetings, where CIOs quietly pick which manifest their agents will speak. Readers tracking how this shakes out can follow our continuing coverage at Blumefield, where we will keep mapping the fault lines of the agent economy as they widen. For a market this young, the surprising thing is not that a standards war has broken out. It is that the battle lines were drawn this fast, and this openly, by companies that usually prefer to fight in the dark. Keep watching Blumefield for what happens when the paper truce finally breaks.