Artificial intelligence is quickly moving from a background role to center stage in nearly all industries, running tasks from managing social media accounts and trading stocks to guiding autonomous vehicles. Yet as these AI agents take on greater responsibilities, one major issue looms: trust.
Consider handing over sensitive health records to a medical AI assistant or trusting an autonomous financial agent to trade life savings. How does the submitter know the data remains confidential? How can they trust that this agent won’t be hacked or manipulated? With traditional AI infrastructure, these questions remain tricky to answer convincingly.
No matter how intelligent, AI is only as trustworthy as the infrastructure it runs on. AI agents mostly rely on centralized servers. However, centralized infrastructure can become a single point of failure and is vulnerable to data breaches and manipulation. The future of AI needs an infrastructure that inherently guarantees trust.
Confidential computing to the rescue
Imagine a secure vault — solid, impenetrable, accessible only by the owner. Inside this vault, the owner can safely store and process the most sensitive documents. Confidential computing is the digital equivalent that uses secure hardware environments known as Trusted Execution Environments (TEEs). Essentially, TEEs lock data and computations inside an isolated, encrypted enclave that nobody (not even the cloud provider) can access.
This concept isn’t new, but until recently, implementing TEEs at scale was challenging. That changed when Intel introduced Trusted Domain Extensions (TDX) in 2021, creating fully isolated virtual machines designed for privacy-preserving AI workloads. But hardware alone doesn’t solve the entire puzzle. Trust also demands transparency and verifiability.
This is where decentralized blockchain infrastructure enters the equation. By pairing confidential computing with blockchain, every computation and decision an AI agent makes can be verified without exposing sensitive data. It’s like having a secure vault with a transparent and tamper-proof logbook recording each access and every action taken inside.
A trusted foundation for autonomous agents
One project working on building a trust layer for AI is iExec, a Web3 infrastructure platform specializing in confidential and decentralized computing. Having anticipated the critical role that trusted infrastructure would play in AI’s future, iExec began developing confidential computing tools as early as 2019.
Building on that foundation, iExec is now deploying its infrastructure to support fully confidential AI agents — autonomous software that independently executes tasks and decisions without compromising user data or operational integrity.
A notable real-world example of this effort is the integration between iExec and elizaOS, a widely adopted open-source framework for building autonomous AI agents. Boasting over 15,000 GitHub stars and 500 contributors, elizaOS has become a prominent AI agent framework, enabling developers to create sophisticated AI-driven software easily.
https://t.co/ATU5fmh0R6
— iExec RLC (@iEx_ec) May 26, 2025
iExec has combined elizaOS with Intel TDX technology to build fully confidential AI agents. Recently, the team deployed an AI-powered agent on X that can autonomously post content and engage with users according to detailed instructions within a secure TEE enclave.
Simplifying private AI
Deploying confidential apps once felt like building an engine from scratch. With iExec’s iApp Generator, it becomes a one-command job: choose a template, hit deploy, and your AI runs securely — no hardware or encryption headaches. In minutes, anyone can tap privacy-preserving compute power.
Trust meets profitability
Ensuring privacy and trust is essential, but building economically sustainable AI projects is equally critical. Creating an innovative AI service that impeccably protects user data but has no clear revenue path is like building a high-speed train with no passengers — technologically impressive but practically useless.
How do we build trust in AI? pic.twitter.com/vl6gGDMQuc
— iExec RLC (@iEx_ec) May 15, 2025
Recognizing this, iExec integrates monetization directly into its decentralized platform. Through the platform’s native token, RLC (RLC), developers can monetize AI models, data sets and the logic behind their AI agents.
Each confidential task an AI agent performs generates onchain records through iExec’s proof-of-contribution (PoCo) mechanism, transparently logging and rewarding the contributors to each computation.
This embedded monetization layer means developers are building scalable businesses around their AI creations. Data providers and model creators can confidently monetize their intellectual property without losing control over sensitive information.
Scaling for the AI era
To meet growing demand from developers and enterprise users, iExec recently completed a platform-wide upgrade. This overhaul delivers a 10x throughput increase, enabling significantly more complex and high-volume confidential computations.
The back-end architecture has been optimized for faster data processing, improved resilience and seamless scaling. Security foundations were also enhanced, integrating advanced attestation frameworks that ensure every execution is cryptographically verified.
A broader decentralized AI ecosystem
The potential of decentralized confidential AI doesn’t end with infrastructure and monetization. To fully realize an open AI ecosystem, collaboration is key. iExec recently became part of AI Unbundled, a strategic alliance of major Web3 and AI companies, including Aethir, Synesis One, Seedify and Ultiverse, committed to decentralizing every aspect of AI.
Within this alliance, iExec provides the critical privacy and trust layer, ensuring secure and confidential execution of AI agents, models and data sets. The collaboration forms a compelling alternative to the centralized and opaque AI offerings of Big Tech companies.
The future of AI is trusted by default
The rise of autonomous AI agents will transform every industry, from finance and healthcare to entertainment and governance. Yet trust remains the most significant challenge and opportunity in AI.
iExec’s confidential computing platform, easy-to-use development tools, integrated monetization model and strategic partnerships represent a foundational shift toward trustworthy, accountable and profitable AI applications.
Ultimately, the future of AI hinges on trustworthiness. As AI becomes deeply embedded into daily life, the infrastructure powering it must prioritize user privacy, security and economic sustainability by design.
By providing a secure and transparent infrastructure, iExec aims to actively shape the future, ensuring that as autonomous AI agents become an integral part of our lives, and they can be genuinely trusted.
Learn more about iExec
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