Nvidia started off 2026 with a $65 billion Q4 revenue forecast, signaling a shift in the AI landscape. The company, known as the backbone of global AI infrastructure, suggests that AI demand is on the rise rather than plateauing. Productivity is increasing at a faster rate than anticipated, and the narrative of the “AI bubble” is slowly fading away.
AI is not slowing down; it is becoming more autonomous, operational, and deeply integrated into the real economy. As these systems expand, the need for a reliable infrastructure becomes unavoidable. Crypto and blockchain are increasingly serving as the foundation for these systems, offering fast settlement, programmable value, verifiable execution, and continuous coordination.
As AI becomes more autonomous, crypto grows alongside it, positioning autonomous AI as a key driver of the next phase of economic growth for AI. To gain insights into where this transformation is headed in 2026, Blockster interviewed Thomas Mayfield, Head of Decentralized Trust and Identity Solutions at the Cardano Foundation, whose work intersects with AI, digital identity, and decentralized infrastructure.
Mayfield envisions 2026 as the turning point where AI transitions from being a support system to an authoritative entity. Agentic systems will be entrusted to make decisions on behalf of users within predefined parameters and constraints, surpassing human-based interactions in terms of security and fraud prevention.
This shift represents a fundamental change in how individuals interact with software. Instead of manually approving every action, users will define their intent, permissions, and limits once, allowing autonomous agents to operate within those boundaries continuously. This streamlined process accelerates execution, reduces friction, and enables systems to scale without constant human intervention.
However, enabling delegation at this level requires more than just advanced models; it necessitates verifiable execution, identity verification, and trust frameworks that operate independently of centralized intermediaries. This is where decentralized identity and on-chain verification transition from optional tools to essential infrastructure.
While major tech companies debate standards and interoperability, Mayfield anticipates that governments will take the lead in adopting decentralized identity technology. He predicts that government services will be the first large-scale adopters of decentralized identity through National ID schemes, with these systems eventually integrating with corporate identity frameworks and extending into supply chain infrastructure like Digital Product Passports.
This shift challenges the conventional assumption in Web3 that startups drive decentralized identity adoption in institutions. Instead, national infrastructure is expected to push identity frameworks into enterprises, logistics, and global trade, primarily driven by compliance rather than experimentation.
Regulatory pressures are already shaping the landscape, with upcoming EU regulations on supply chain and data expected to drive enterprise demand for verifiable identity and data attribution. Mayfield foresees these requirements transitioning from planning to enforcement in 2026, compelling enterprises to adopt technologies that support cross-domain secure attribution.
Addressing the balance between interoperability, ease-of-use, privacy concerns, self-sovereign controls, and security will be a key challenge for providers operating in this space.
Digital Product Passports, often viewed as potential surveillance tools, can be designed to prioritize privacy through a self-sovereign approach. Effective DPP systems rely on a combination of off-chain and on-chain data repositories to ensure secure data handling and verification while preventing abuse and surveillance.
The ultimate goal is to achieve selective proof without compromising privacy. This delicate balance between transparency and privacy can only be achieved through the use of cryptography, decentralized identity, and programmable access controls.
With AI systems gaining delegated authority, trust becomes a crucial element of the infrastructure. Autonomous agents can only operate at scale if identity, execution, and accountability are verifiable by default. This paradigm shift in AI, as highlighted by Mayfield, signifies a move from using AI as tools to authorizing AI agents to act on our behalf.
As we look ahead to 2026, where agentic systems are trusted to act, it is evident that AI creates the demand for autonomy, cryptography provides verifiable trust, and decentralized identity enables coordination without centralized control.
If 2025 was about proving the functionality of agentic systems, 2026 is poised to be the year they earn the trust to act autonomously.
