Cardano Foundation CEO Frederik Gregaard said roughly 200 large companies in Germany are already live with agentic AI systems that rely on Cardano in the background, even if end users do not realize it. The remark, made during an April 16 interview on GBBC’s Markets on Chain series from the New York Stock Exchange, offers a notable glimpse into Cardano’s pitch as enterprise infrastructure for identity, accountability, and compliant AI-driven payments.
German Firms Quietly Run on Cardano AI Rails
Greagaard framed the adoption story less as a visible crypto rollout and more as embedded infrastructure. “We have about 200 companies in Germany who’s live on agendic AI, fairly large companies, and they don’t even know they’re using Cardano as a security layer, as a digital identity layer and as an accountability layer,” he said. For Cardano, that is the point: blockchain as backend plumbing rather than a consumer-facing product.
He tied that claim to a specific enterprise AI problem set. When agentic AI systems pull data from multiple databases, Gregaard said, the challenge is proving that an agent is what it claims to be, and that the data it uses is valid, without exposing sensitive information. In his words, the goal is “ensuring that the agentic AI is who they say they are, that they have the data they claim without disclosing it, because we want privacy.”
That architecture, he argued, supports a smoother user experience while preserving provenance and compliance. Gregaard described a future in which users can access booking, loyalty, and recommendation flows in one place, while the underlying system handles identity, permissions, and auditability. “What we’re doing here is we’re ensuring provenence of data, identity and collaboration all in a regulatory framework,” he said, positioning Cardano as a control layer for enterprise AI rather than simply a settlement network.
Cardano’s role, in his telling, also extends into machine-native payments. Gregaard said AI agents are already transacting with “regulatory compliant stable coins,” naming USDM as the instrument used for microtransactions tied to prompts. “The AIs are actually paying themselves,” he said. “There’s a microtransaction happening just to do the prompts.”
That payment rail is not just about settlement efficiency. Gregaard said the stablecoin layer helps enforce usage limits between systems with different computing power, preventing one participant from overwhelming another through unlimited prompts. In that model, the payment mechanism doubles as a security and incentive framework, an approach he described as a next-generation stablecoin use case beyond institutional fund flows.
The broader implication is that Cardano wants exposure to the AI stack through invisible infrastructure, not just token markets. Gregaard repeatedly returned to the idea that many users “might not know they use the blockchain,” arguing that adoption will come from utility embedded into existing systems. If that thesis holds, the German deployments he referenced could serve as a template for enterprise blockchain integration that is operationally important but largely abstracted from the end user.
Gregaard Ties AI Adoption to Identity Layers
A central part of Gregaard’s argument was that AI adoption will hinge on identity and accountability, especially as agents gain more autonomy. He pointed to examples in Switzerland where an agentic AI has already released an incorrect payment, raising a simple but difficult question: “Who is to blame?” For him, that is where blockchain-based identity infrastructure becomes commercially relevant.
He said Cardano has pushed governance fully on-chain as part of its security model, reducing reliance on founders or centralized control points. “We wrote a constitution together with the citizens of Cardano and we implemented that in smart contracts to really protect the network,” he said. Gregaard argued this matters in an AI-heavy environment because it removes single points of failure and makes the network harder to compromise through targeted attacks.
He also linked that security case to enterprise identity standards. Gregaard said Cardano has implemented interoperability with the legal entity identifier, or LEI, and pointed to the vLEI as “the first level quantum secure for corporations.” According to him, that has driven demand from traditional finance players that want an identity layer that is interoperable, distributed, and built for higher-grade security assumptions.
That same framework sits behind his more expansive claim about where blockchain is heading. “I’ve feverly believed that we’re going to head into a world that all of our systems are based on security with an underlying blockchain in plural. I think most people won’t know they’re operating on a blockchain. It becomes a standard in critical infrastructure,” he said. In his view, the driver is not ideology but resilience against AI-era attack surfaces.
Greagaard also argued that public, permissionless infrastructure will become more relevant as regulators and institutions get clearer tools for evaluating risk. He pointed to the recently released capital markets risk mitigation framework developed with GBBC as an attempt to create a common language for non-financial risks on public blockchains. That, he said, could help move institutions beyond private chains that have so far delivered limited added value.
On the US outlook, Gregaard said recent legislative momentum around stablecoins and market structure could accelerate non-financial blockchain use cases. He argued the next wave of adoption may come less from speculative trading than from identity, compliance, and machine-to-machine coordination. For Cardano, the message from New York was straightforward: the AI economy may already be using crypto rails, even when the branding is nowhere in sight.
Gregaard’s interview sketched a version of Cardano adoption that is quieter than the market usually notices: AI agents, enterprise identity rails, and compliant stablecoin micropayments operating behind familiar interfaces. Whether that footprint expands will likely depend on the same factors he emphasized throughout the conversation — regulatory clarity, interoperable identity standards, and the ability of public blockchain infrastructure to handle AI-era accountability demands.
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