Compliance Equals Competitiveness: The Profound Impact of the Implementation Opinions on Agents on AI + Biometric Enterprises
I. One Document, Two Signals
On May 8, 2026, the Cyberspace Administration of China (CAC), the National Development and Reform Commission (NDRC), and the Ministry of Industry and Information Technology (MIIT) jointly issued the Implementation Opinions on Regulated Application and Innovative Development of Agents (hereinafter referred to as the "Implementation Opinions"). This is no ordinary industry regulatory document — jointly signed by three ministries and commissions, with 38 measures directly targeting "agents", the cutting-edge form of the current AI industry, the signal is clear enough: the regulatory focus of China's AI industry is shifting from large models themselves to agent application layers.
For enterprises in the AI + biometric recognition track, the significance of this document is particularly special.
First, looking at the market side. Xinhua News Agency disclosed in January 2026 that China's AI core industry scale is expected to exceed 1.2 trillion yuan in 2026, a year-on-year increase of nearly 30%. IDC predicts that the market size of security agent-related applications in China will reach $1.6 billion in 2028. Data from Mordor Intelligence shows that multi-agent systems already account for 53.3% of the AI market, with a growth rate as high as 42.14%. Meanwhile, research from Research Nester indicates that the global biometric market was valued at $59.65 billion in 2025 and is expected to grow to $322.94 billion by 2035, with a compound annual growth rate of nearly 19%.
Then, looking at the regulatory side. Before the implementation of the Implementation Opinions, the biometric field already had a basic regulatory framework consisting of the Personal Information Protection Law, the Data Security Law, the Cybersecurity Law, and the Measures for the Security Administration of Facial Recognition Technology Application which officially came into force in 2024. The issuance of the Implementation Opinions marks the extension of regulatory tentacles from static data protection to dynamic agent behaviors — all agents that invoke biometric recognition capabilities will face new compliance reviews.
The market is expanding rapidly, and regulation is tightening simultaneously. This is the dual reality that every AI + biometric enterprise must address at the same time.
II. The Policy Logic Behind the Joint Signature of Three Ministries and Commissions
Why was the Implementation Opinions jointly signed by three ministries and commissions? This in itself is a signal worth interpreting.
The CAC leads content security and data governance; the NDRC is responsible for industrial policies and market access; the MIIT focuses on technical standards and industrial ecosystems. The joint issuance by the three ministries and commissions means that the regulatory logic for agents has crossed a single dimension, forming a new pattern of three-dimensional collaborative governance of "security + industry + standards".
The core logic of the 38 measures can be summarized in one sentence: encourage innovation but not allow disorderly expansion; support applications but must draw clear security boundaries.
Specifically, the Implementation Opinions has designed institutional arrangements at the technical, industrial, and security levels respectively:
Technical level: Promote an open ecosystem, support model capability interoperability and API interconnection, but require clear security responsibilities for each node in the supply chain;
Industrial level: Focus on promoting agent applications in sensitive fields such as public security, finance, and healthcare, but adopt a classified and graded access mechanism;
Security level: Introduce a third-party compliance evaluation system, promote mutual recognition of certification results across platforms, and establish a recall mechanism.
These three levels of institutional design jointly point to the evolution direction of the industrial ecosystem: compliance capability will become the core threshold for agent enterprises to enter high-value scenarios.
III. Filing, Testing, and Recall: Compliance Challenges at the Engineering Level
Article 11 of the Implementation Opinions clearly proposes "classified and graded governance", requiring agents in sensitive fields to fulfill three core obligations: filing, testing, and recall. What do these three words mean when translated into engineering practice?
Filing: Not Just Filling Forms, but Systematic "Explainability" Preparation
The essential requirement of filing is that enterprises can clearly explain to regulatory authorities: what your agent is doing, why it is doing it, and who is responsible if something goes wrong.
This poses a particularly prominent challenge for biometric agents. Traditional deep learning algorithms are "black boxes" — the model draws recognition conclusions but cannot explain the decision path to the outside. Filing reviews will force enterprises to provide documents such as algorithm transparency reports, data flow descriptions, and risk boundary definitions. For algorithms that cannot explain their own decision logic, filing will become a substantive obstacle.
Testing: The Implementation Pressure of the Third-Party Evaluation System
Article 12 requires the introduction of third-party compliance evaluations and the promotion of mutual recognition of certification results. For biometric agents, the core testing indicators will cover: recognition accuracy and rejection rate, data non-exit verification (localized deployment review), robustness against adversarial attacks, and algorithm version traceability. Enterprises need to embed "testability" into the technical architecture at the product design stage, rather than making temporary remedies before testing.
Recall: Handling "Product Defects" in the Agent Era
The recall mechanism introduced in Article 11 is one of the most forward-looking institutional designs of this Implementation Opinions. When an agent is found to have security defects or compliance issues after deployment, enterprises need to have the technical capabilities for rapid recall, version rollback, and risk isolation.
This puts forward higher requirements for biometric devices with hardware-solidified deployment — firmware version management, remote security update channels, and defect tracking mechanisms must be planned simultaneously at the hardware design stage.
Article 9 further requires enterprises to establish security management ledgers for model access, API calls, and extension tools involved in the supply chain. This means that agent integrators that invoke third-party biometric capabilities will bear joint and several liabilities for the compliance status of upstream capability providers. Supply chain security management will become a mandatory consideration in procurement decisions.
IV. Analysis of Sensitive Fields: Risk Grading of Biometric Recognition
Article 31 of the Implementation Opinions lists public security as a key area for agent promotion. Combined with the scenario classification logic of the current Measures for the Security Administration of Facial Recognition Technology Application (2024), we have conducted a risk level analysis of biometric agent
| Application Scenario |
Risk Level |
Urgency of Compliance Requirements |
| Public Security (Border Inspection / Policing / Community Control) |
High Risk |
Immediate filing, mandatory third-party testing |
| Financial Identity Verification (Account Opening / Large Transactions) |
Medium-High Risk |
Complete compliance evaluation during the 2026 pilot period |
| Medical Identity Recognition (Electronic Medical Records / Drug Management) |
Medium-High Risk |
Localized data deployment is a mandatory requirement |
| Enterprise Access Control / Attendance |
Medium Risk |
Data retention specifications and employee informed consent |
| Commercial Retail (Facial Payment / Passenger Flow Analysis) |
Medium Risk |
Scenario description and user authorization mechanism |
| Smart Home (Personal Device Unlocking) |
Low Risk |
Compliance with privacy policies is sufficient |
Core Judgment: For all biometric agents involving public security, finance, and healthcare, the 2026 pilot period is the substantive compliance window, and enterprises should not wait for mandatory law enforcement to respond.
V. Compliance Timeline: Windows and Pressures in Three Stages
CCID Consulting's three-stage forecast for the agent industry provides a clear time coordinate for enterprises:
2026 — Pilot Explosion Period (Market Growth Rate Exceeds 60%)
This is the window period with the highest regulatory tolerance and the richest pilot dividends. Leading enterprises should complete the construction of internal compliance systems during this stage, actively participate in pilot projects, and accumulate certification qualifications. Enterprises that miss this window will face the high cost of passive compliance in the next stage.
2027 — Standard Improvement Period
Industry standards and regulatory details will be gradually implemented. A third-party evaluation institution system will be formed, and certification costs and cycles will stabilize. At this stage, enterprises with complete compliance files will have significant advantages in bidding, especially in government procurement and central SOE projects.
2028 — Large-Scale Popularization Period (Agent Enterprise Penetration Rate Exceeds 70%)
The $1.6 billion security agent market predicted by IDC will be concentratedly released at this stage. By then, enterprises that have not completed compliance certification will be substantially excluded from high-value scenarios.
Time Tip for Enterprise Management: The second half of 2026 is the optimal time node to start compliance evaluation preparations. Waiting for "standards to stabilize before taking action" in 2027 is a costly misjudgment.
VI. Homsh's Compliance Confidence
Facing the above compliance requirements, Homsh's product system is not a temporary response, but naturally conforms to the core logic of the Implementation Opinions at the technical architecture level.
Explainability: The Structural Advantage of the Phaselirs™ Algorithm
The Phaselirs™ iris recognition algorithm independently developed by Homsh is based on the phase encoding principle and achieves a recognition accuracy of one in a billion. Unlike deep learning black box models, the decision path of the phase encoding method is traceable, quantifiable, and explainable to third parties — which is exactly the core requirement of filing reviews for algorithm transparency. In compliance evaluations, "explainability" will become a key differentiating indicator for algorithm manufacturers.
Data Security: The Architectural Moat of Localized Deployment
Homsh's systems adopt a fully localized deployment mode, where biometric data is not uploaded to the cloud and never leaves the device. This architectural design naturally meets the mandatory requirements for data non-exit in sensitive fields, while greatly reducing supply chain security risks — because there is no cloud API call link, the supply chain security management ledger is significantly simplified.
Hardware Security Boundary: The Qianxin FPGA Platform
The Qianxin FPGA platform solidifies the Phaselirs™ algorithm into the chip, forming a hardware-level security boundary. The algorithm runs inside the chip and cannot be tampered with or extracted by external programs. This design not only meets the technical requirements of the recall mechanism but also provides a verifiable hardware root of trust for third-party testing.
Standard Participation: The Discourse Power of Rule Makers
Homsh continues to participate in the formulation of national and industry standards. Standard participation not only means early perception of regulatory trends but also proactive alignment of product design with regulatory expectations — a compliance advantage that no latecomer can replicate in the short term.
VII. Five Action Recommendations for Procurers and Integrators
1.Incorporate "Supply Chain Compliance" into the Procurement Scoring System
In accordance with Article 9 of the Implementation Opinions, integrators bear joint and several liabilities for the compliance status of upstream capability providers. Procurement contracts should clearly require suppliers to provide algorithm filing certificates and data flow descriptions, and stipulate the division of responsibilities in case of compliance failure.
2.Prioritize Localized Deployment Solutions
In sensitive scenarios (security, healthcare, finance), cloud-based biometric API solutions will face increasingly strict data cross-border and non-exit reviews. Localized deployment solutions have long-term advantages in compliance costs and should be written into technical solution review standards as a priority option.
3.Require Suppliers to Provide Algorithm Explainability Documents
During the technical review stage, require candidate suppliers to provide algorithm decision path descriptions and third-party evaluation reports. Suppliers that cannot provide explainability documents will face serious compliance risks after the standard improvement period in 2027.
4.Launch Compliance Pre-Assessment Within 2026
Collaborate with equipment suppliers and system integrators to conduct a compliance gap analysis of existing biometric systems within 2026, clarify the list of filing materials, the correspondence of testing standards, and the technical requirements of the recall mechanism, to prepare for the official evaluation in 2027.
5.Establish Version Management and Defect Response Mechanisms
Start establishing hardware firmware version ledgers, algorithm model version records, and security update push channels now. This is not only a technical prerequisite for the recall mechanism but also a mandatory inspection item for third-party evaluations in 2027.
Conclusion: Compliance Is Not a Threshold, but a Moat
The issuance of the Implementation Opinions marks that China's AI governance has entered a new stage — from regulating the technology itself to regulating the application behavior of technology; from passively responding to problems to proactively building a trusted system.
For AI + biometric enterprises, the significance of compliance has transcended the negative level of "avoiding penalties". When the penetration rate of agent enterprises exceeds 70% in 2028 and the market enters a stage of large-scale competition, compliance qualifications will become a pass to enter high-value scenarios, while non-compliance will be a substantive market access barrier.
The compliance construction costs invested today will be transformed into competitive barriers in the next three years. Those enterprises that are already prepared today will be the first batch of players to get the admission tickets tomorrow — and also the last winners to stay on the field.
