Key Points
- China is implementing a comprehensive plan to integrate AI across the entire bidding and tendering process, aiming to improve transparency, efficiency, and combat fraud.
- The initiative targets the deployment of AI in over 20 specific use cases, from bid planning and document preparation to intelligent evaluation and identifying bid rigging (Wei Chuan Biao 围串标).
- Key scenarios like document detection, intelligent evaluation, and bid rigging identification are expected to achieve full coverage in selected provinces and cities by the end of 2026, with a nationwide rollout by the end of 2027.
- The strategy adopts a hybrid public-private model: private companies can develop tools for transaction efficiency, while the government leads in building systems for fairness and regulation.
- A critical guardrail is that AI will remain auxiliary, assisting human decision-making and not replacing the independent judgment or legal responsibilities of involved parties.
- National strategy for end-to-end AI integration in bidding.
- Focus on high-risk areas: bid rigging and document fraud.
- Phased rollout: full pilot coverage by 2026, national by 2027.
- Public-private partnership for tool development and governance.
The Chinese government just dropped a major policy blueprint that’s about to reshape how bidding and tendering work across the entire country.
We’re talking about artificial intelligence (AI) integration at every single stage of the procurement process—from initial planning all the way through contract signing and dispute resolution.
This isn’t some vague tech-forward vision statement either. The National Development and Reform Commission (Guojia Fazhan He Gaige Weiyuanhui 国家发展改革委) and other departments just issued concrete implementation opinions with specific timelines and measurable targets.
Let’s break down what’s actually happening and why it matters for investors, founders, and anyone building in the Chinese tech ecosystem.
The Big Picture: Why China Is Moving Fast on AI-Powered Procurement
Here’s the reality: procurement markets are messy.
They’re prone to bid rigging, collusion, unfair document practices, and slow decision-making.
China’s government sees AI as the antidote. Instead of relying on humans to manually review thousands of bids and spot irregularities, AI can do it at scale, faster, and more consistently.
The strategy is straightforward:
- Improve the quality and transparency of bidding documents
- Catch potential fraud and collusion before it happens
- Speed up the evaluation process
- Make the system more accessible across provinces and cities
- Reduce human bias and corruption
The government wants key scenarios like document detection, intelligent evaluation, and bid rigging identification to achieve full coverage in select provinces and cities by the end of 2026.
By 2027, these practices should be rolled out nationally.
15 Specific AI Applications Getting Deployed Across the Bidding Lifecycle
This policy document outlines 20 concrete use cases where AI is being integrated into the procurement process.
Let’s organize them by stage:
Stage 1: AI in Bid Planning (For Bidders)
1. Bid Planning Assistance
AI analyzes industry trends, market supply and demand, and resource availability to help bidders make informed decisions.
It can generate objective, quantified bidding requirements and technical conditions based on project data.
Translation: Bidders get better market intelligence before they even submit.
2. Document Preparation
The system uses historical transaction data to intelligently match document templates and recommend appropriate qualification conditions and evaluation standards.
This improves document quality and reduces errors.
3. Document Detection & “Health Checks”
Before publishing, bidding documents get multi-dimensional checks for:
- Compliance with regulations
- Rationality of terms
- Problematic language or restrictions on competition
The AI automatically flags illegal provisions and sensitive language.
Stage 2: AI in Tendering (For Suppliers)
4. Tendering Planning
AI captures project information globally and pushes relevant opportunities to suppliers based on their specific characteristics and capabilities.
It extracts key elements from bidding plans and automatically analyzes economic feasibility for participation.
5. Compliance Self-Check
Before submitting bids, suppliers can use AI to:
- Determine technical solutions and price ranges
- Compare their bid documents against all requirements
- Get automatic alerts for illegalities, errors, or omissions
- Receive risk warnings if their bid appears below cost
This is basically a pre-flight checklist powered by machine learning.
Stage 3: AI in Opening & Evaluation
6. Bid Opening with Digital People (Shuzi Ren 数字人)
Here’s where it gets interesting: human-like digital avatars manage the bid opening process.
These Digital People handle:
- Reading opening disciplines
- Announcing bid lists
- Decryption procedures
- Real-time anomaly handling
It’s automation meets theater—the process is still official and formal, but it’s powered by AI.
7. Expert Selection
Instead of manually selecting evaluation experts, AI automatically generates extraction plans that match:
- Project characteristics
- Geographic requirements
- Expertise needs
This ensures a more scientific and fair selection process.
8. Intelligent Assisted Evaluation
This is the big one. AI uses human-like reasoning to parse bid documents and evaluation criteria.
It generates reference results that assist experts during evaluation, enhancing fairness and depth.
Key point: AI is still auxiliary. Experts make the final decision, not the algorithm.
Stage 4: AI in Awards & Contracts
9. Evaluation Report Verification
Intelligent audit systems check:
- Report accuracy
- Logical consistency
- Scoring inconsistencies
- Calculation errors
Catches mistakes before they become official.
10. Decision Support & Multi-Dimensional Profiling
Before awarding a contract, the system creates comprehensive profiles of winning candidates using:
- Credit data
- Tax records
- Judicial information
- Historical performance
Digital People can also assist during defense sessions to support final award decisions.
11. Contract Signing & Hidden Contract Detection
AI automatically extracts key signing elements and generates contracts.
More importantly, it provides risk alerts for critical clauses to prevent “Hidden Contracts” (Yin Yang Hetong 阴阳合同) or unauthorized tampering.
For context: hidden contracts are when parties have two versions—one official and one real. It’s a major fraud vector.
Stage 5: AI in On-Site Management
12. Venue Scheduling & Unattended Smart Environments
AI dynamically monitors transaction venues and personnel, creating spaces that can operate with minimal human oversight while improving cross-regional service access.
13. Witness Management
A closed-loop digital witnessing system that:
- Records the entire bidding process
- Provides early warnings for suspected violations
Immutable audit trails powered by AI.
14. Archive Management
Instead of manually organizing transaction records, AI handles:
- Automatic naming
- Classification
- Indexing
Makes archives searchable for performance evaluation and dispute resolution.
15. Smart Q&A Engine
A professional knowledge base for the bidding field that provides interactive consultation on:
- Policies
- Business knowledge
- Operational procedures
Basically ChatGPT for procurement.
Stage 6: AI in Supervision & Anti-Fraud
16. Expert Life-Cycle Management
A comprehensive system that tracks experts using:
- Multi-dimensional profiling
- Dynamic assessment
- Resource sharing across the national network
Keeps experts accountable across jurisdictions.
17. Bid Rigging Identification (The Fraud Detection Engine)
This is where AI really shines. The system identifies bid rigging (Wei Chuan Biao 围串标) by analyzing:
- Multi-dimensional data “collisions”
- Identical enterprise characteristics across bidders
- Abnormal bidding behavior patterns
- Expert bias indicators
- Semantic similarity in technical solutions to uncover suspected collusion
It’s pattern recognition at scale.
18. Credit Management
AI realizes:
- Objective recording of credit information
- Automatic collection of data across systems
- Precise credit evaluation models for market entities
Reputation systems powered by machine learning.
19. Collaborative Supervision & “One Network Governance” (Yi Wang Gong Zhi 一网共治)
AI identifies issues like:
- Failure to bid when required
- Illegal subcontracting
- Severe progress delays
Then integrates administrative, judicial, and disciplinary data into a unified governance system.
20. Complaint Handling & Case Analysis
AI assists administrative departments by:
- Analyzing complaint letters
- Reviewing historical cases
- Generating preliminary review opinions
- Improving handling efficiency
The Implementation Strategy: Who Builds What
The government is being strategic about who builds and deploys these AI systems.
Here’s the breakdown:
- Scenarios improving transaction efficiency: Market-based service providers should be cultivated. (Translation: Private companies can build these tools and sell them.)
- Scenarios ensuring fairness and regulation: Government should take a leading role in integrated construction. (Translation: The government will build these critical tools itself or heavily oversee them.)
- Provincial-level coordination: Required for resource sharing and standardization.
- County-level reuse: Lower-level entities should generally reuse higher-level model resources rather than building from scratch.
This creates a hybrid public-private model where efficiency improvements can be commercialized, but core governance functions stay under government control.
Critical Guardrail: AI Stays Auxiliary
The policy makes something crystal clear: AI maintains an auxiliary position.
This is important:
- Model conclusions do not replace the independent judgment of bidders, agencies, or experts.
- AI outputs do not change the legal responsibilities of the parties involved.
- Humans stay accountable for final decisions.
It’s a smart approach—using AI to reduce bias and catch errors, but keeping humans in the driver’s seat for accountability.
Timeline & Rollout: The 2026-2027 Roadmap
The government set specific targets:
By the end of 2026:
- Key scenarios like bidding document detection, intelligent assisted evaluation, and bid rigging identification will achieve full coverage in selected provinces and cities.
By the end of 2027:
- More key scenarios will be promoted nationwide.
- A set of experienced practices will form around model training, scenario application, and mechanism guarantees.
It’s a phased approach: pilot → refine → scale nationally.
What This Means for the Chinese Tech Ecosystem
This policy represents a massive opportunity for companies working in:
- AI/ML infrastructure — Building the models and platforms
- Fintech and compliance tech — Automating financial checks
- Data infrastructure — Aggregating and standardizing procurement data
- SaaS for procurement — Building tools for bidders and suppliers
- Digital governance — Creating platforms for government oversight
- Fraud detection — Specialized systems for bid rigging identification
The Chinese government is essentially creating a massive procurement ecosystem powered by AI—and they want private companies to help build parts of it.
For founders: there’s a clear regulatory framework, government backing, and defined timelines. That’s rarer than you’d think.
For investors: this is a multi-billion-yuan market being created from the top down, across dozens of industries (construction, water resources, agriculture, commerce, state-owned enterprises, etc.).
The Bottom Line: AI-Powered Procurement Is Coming to China
The National Development and Reform Commission (Guojia Fazhan He Gaige Weiyuanhui 国家发展改革委) just outlined a comprehensive blueprint for integrating AI across the entire bidding and tendering lifecycle.
From initial bid planning through contract signing and dispute resolution, AI is being deployed to improve efficiency, catch fraud, and reduce human bias.
The rollout is aggressive but thoughtful: pilot in select cities by end of 2026, scale nationally by end of 2027.
And the government is being smart about the split—letting private companies build efficiency tools while maintaining control over core governance functions.
If you’re building in the AI, governance tech, or procurement space in China, this is the policy to understand.
It signals where capital and resources are flowing, what the government prioritizes, and what opportunities exist for builders and investors in AI-powered bidding transformation.
References
- Implementation Opinions on Accelerating the Promotion and Application of Artificial Intelligence in the Bidding and Tendering Field – National Development and Reform Commission (NDRC)
- Official Website – Ministry of Industry and Information Technology (MIIT)
- Official Website – Ministry of Housing and Urban-Rural Development (MOHURD)
