In recent years, the development of AI has been evident to everyone. AI has evolved from rule-based programs to self-learning neural networks. In the 2010s, Siri could answer questions, self-driving cars could recognize road conditions, and recommendation algorithms could predict our preferences.

But all of this is still just a tool. They rely on input and cannot act autonomously. It is in this environment that agent AI emerges.

As OpenAI CEO Sam Altman said, "AI safety is much more important than most people realize." Elon Musk has also warned, "The threat of AI to humanity exceeds that of nuclear weapons."



Thousands of AI agents will be spread across the network, collaborating, trading, modeling, and governing, building a new world driven by intelligence.

These warnings herald the arrival of a new era — truly autonomous and secure AI entities.

But whether this world can exist depends not on how strong AI is, but on — can we trust them? This is the vision of the Agentic World.



In the future Web3 world filled with AI agents (Agentic World), security, privacy, identity verification, verifiability, and data sovereignty become the most critical infrastructure requirements. Fully Homomorphic Encryption (FHE) is becoming the most promising underlying technology in this revolution of the encrypted world.

From healthcare to DeFi, the application scenarios of FHE + AI are already visible.

1. Healthcare sector

In the healthcare industry, AI is widely used in automated document processing, virtual care assistants, predictive analytics, and medical research. FHE technology makes it possible to perform calculations without decrypting patient data, thereby protecting patient privacy and ensuring data security. For example, healthcare providers can use FHE to analyze encrypted electronic health records (EHRs), enabling secure processing and analysis of patient data.

Agents deployed in different hospitals can share encrypted data and collaborate on modeling without exposing any case plaintext, leading to more accurate diagnostic models.



2. Decentralized Finance (DeFi)

In the DeFi sector, FHE allows direct calculations on encrypted data, enabling users to participate in financial activities without exposing their asset information. This not only enhances user privacy but also improves the overall security and credibility of the system.

AI Agents can access encrypted on-chain transaction behaviors to generate credit ratings, risk analyses, or investment recommendations without knowing who you are, how much assets you have, or what you traded.



3. The gaming industry

AI is used in game design to create realistic non-player characters (NPCs), optimize game mechanics, and analyze player behavior. FHE technology can ensure that player data remains encrypted during analysis, preventing data leaks while enhancing the gaming experience.

Players' behaviors, preferences, and asset records are managed by Agents, using FHE encrypted calculations to prevent platform abuse and enable cross-platform migration.

And the common foundation behind these capabilities is: your data is always yours, and the Agent can only access it in encrypted form "within the limits you allow."


🔐 Practical scenarios of FHE in the crypto space


1️⃣ Collaborative computing between smart contracts and AI

Traditional smart contracts, while "automatically trustworthy," also mean a lack of data privacy due to their transparency. When AI Agents participate in on-chain automatic trading, clearing, and liquidity allocation, the data they handle (user behavior, on-chain fund distribution, strategy preferences, etc.) can expose Alpha if not encrypted.

FHE allows smart contracts and AI to perform reasoning and execution directly on encrypted data, completing transaction judgments, strategy switches, and risk assessments without decryption. This is revolutionary for scenarios like high-frequency strategies, oracle protection, and DAO governance suggestions.


2️⃣ Private computing in DeFi

One of the biggest concerns for DeFi users is privacy exposure: wallet addresses linked to asset status, transaction behavior, collateral records, and liquidity provision records. This data can not only be scraped but may also be exploited by MEV algorithms.

With the introduction of FHE, users can participate directly in encrypted lending, derivatives trading, aggregation routing, etc., without disclosing personal preferences or asset distributions.

Combining FHE with DeFi protocols allows for on-chain encrypted calculation of APY, automatic reinvestment of earnings, or running AI to dynamically allocate positions, making DeFi smarter and more privacy-native.


3️⃣ Applications of AI agents in DEX, contracts, and blockchain games

As Agents increasingly appear in trading scenarios, FHE can be used to build a "privacy-enhanced on-chain Agent factory" — each Agent is an executable entity capable of encrypted computation:

  • Execute contract operations on your behalf (limit orders, take profit and stop loss)

  • Participate in strategy DAO (vote based on the logic you set)

  • Control characters in blockchain games (but do not disclose your preferences and strategies)

The core trust basis of such Agents comes from FHE + decentralized verification mechanisms, ensuring their behavior operates "within the limits you authorize."


🧬 Final question: Would you let AI use your wallet data?

The answer is, you are willing, but the premise is:

  • Revocable authorization (I can lock it after the Agent no longer accesses it)

  • Immutable usage records (what the Agent used and when)

  • Traceable behavior audits (I can verify every step of the Agent)

FHE is the key technology in this answer.#MindNetwork全同态加密FHE重塑AI未来