Source: National Development and Reform Commission
Implementation Opinions of the National Development and Reform Commission and Other Departments on Accelerating the Promotion and Application of Artificial Intelligence in the Field of Bidding and Tendering
National Development and Reform Commission Regulation [2026] No. 195
Development and Reform Commissions, industrial and information technology authorities, Departments (Commissions, Bureaus) of Housing and Urban-Rural Development, Departments (Bureaus, Commissions) of Transportation, and Departments (Bureaus) of Water Resources (Water Affairs) of all provinces, autonomous regions, municipalities directly under the central government, and the Xinjiang Production and Construction Corps; Departments of Agriculture and Rural Affairs (Bureaus, Commissions), competent authorities for commerce, State-owned Assets Supervision and Administration Commissions, departments responsible for guiding and coordinating bidding and tendering, and lead departments for the integration of public resource trading platforms; Communications Administrations of all provinces, autonomous regions, and municipalities directly under the Central Government; and all central state-owned enterprises:
To implement the requirements of the Central Committee of the Communist Party of China and the State Council regarding the deepening of reforms in the bidding and tendering sector, and in accordance with the relevant provisions of the “Opinions of the State Council on the In-Depth Implementation of the ”Artificial Intelligence+’ Initiative,” the following opinions are hereby put forward to promote the deep integration of bidding and tendering with artificial intelligence and to foster the standardized and healthy development of the bidding and tendering market.
I. Overall Objectives
Focusing on the entire process of bidding and tendering transactions and key management stages, and in accordance with the principles of government guidance, multi-stakeholder participation, scenario-driven development, and security and controllability, we will actively and prudently advance the application of artificial intelligence in the bidding and tendering sector, improve bidding and tendering practices, and enhance the level of digital and intelligent transformation in services and regulation, thereby providing strong support for ensuring the fair and efficient allocation of public resources and standardizing the order of the bidding and tendering market.
By the end of 2026, key applications—such as tender document verification, intelligent bid evaluation assistance, and bid-rigging detection—will be fully implemented in select provinces and municipalities; by the end of 2027, these key applications will be rolled out nationwide, establishing a set of best practices in areas such as model training, scenario-based applications, and institutional safeguards, thereby effectively promoting the standardized and healthy development of the bidding and tendering market.
II. Accelerating the Development of Scenario-Based Applications
(1) “Artificial Intelligence+” Tendering
1. Tender Planning. Assist the tenderer in conducting a comprehensive assessment of industry trends, market supply and demand, and resource factors; accurately understand and analyze information regarding the project’s investment approval, bidding and tendering, and performance acceptance; and develop objective, quantifiable tender requirements as well as technical and commercial terms, thereby enhancing the scientific and rational nature of the tender process from the outset.
2. Preparation of Bidding Documents. Based on a thorough understanding of project objectives, scope of work, bidding requirements, and technical and commercial conditions—and taking into account historical transaction data and policy and regulatory requirements—the system intelligently matches template bidding documents, recommends appropriate qualification criteria, bid evaluation methods, and evaluation standards, and assists the tendering entity in preparing or automatically generating bidding documents to improve the quality of the bidding documents.
3. Tender Document Review. In accordance with relevant policies and regulations, conduct multi-dimensional reviews of tender documents—including compliance, reasonableness, and sensitive terms—to automatically identify various violations of laws and regulations, as well as issues that exclude or restrict competition. Provide the basis for such determinations and recommendations for revisions to assist the tendering entity in intelligently correcting the tender documents. The practice of “reviewing tender documents before publication” is encouraged.
(2) “AI+” Bidding
4. Bid Planning. Comprehensively capture tender information for all types of projects; push relevant project information tailored to the bidder’s characteristics; automatically extract and parse key elements from materials such as project tender schedules, tender notices, and tender documents; intelligently generate a tender requirements map; and highlight important content. By incorporating historical transaction data and information on similar projects, the system assists in analyzing and evaluating the economic viability of participating in project competitions, thereby improving bidding efficiency.
5. Bid Compliance Self-Assessment. Conduct an in-depth analysis of the project’s bidding requirements and the tender documents, taking into account the bidder’s specific characteristics and strengths, to assist the bidder in determining the technical proposal and pricing range. For bid documents prepared by bidders, we conduct a compliance comparison against the tender documents, automatically flagging any violations, errors, or omissions in the bid documents to assist bidders in making targeted revisions and improvements. We also issue risk warnings for bids that may be below cost, thereby reducing instances of malicious low-ball bidding.
(3) “AI+” Bid Opening and Bid Evaluation
6. Bid Opening. Create a human-like digital bid-opening host to manage the entire bid-opening process, automatically handling tasks such as reading the bid-opening rules, announcing the list of bidders, decrypting bid documents, reading out the bids, and confirming the results. The system intelligently detects anomalies during the bid opening and issues alerts, assisting the tendering authority in handling issues in real time and efficiently.
7. Expert Selection. By comprehensively analyzing project characteristics and bid evaluation criteria, and taking into account factors such as the experts’ professional specializations, geographic distribution, and recusal rules—along with requirements for remote and off-site bid evaluation—the system automatically generates an expert selection plan tailored to the project. This enhances the match between the selected experts and the project, ensuring the scientific rigor and fairness of the selection process.
8. Intelligent Bid Evaluation Assistance. Develop human-like evaluation reasoning capabilities; understand the knowledge frameworks of experts in various specialized fields; establish comprehensive evaluation indicator systems based on project types; recommend or match evaluation criteria tailored to specific projects; comprehensively extract elements from bidding and tender documents; conduct in-depth analysis of tender document content and the responsiveness of bid submissions; assist experts in conducting evaluations or generate results for expert reference; and enhance the fairness of the evaluation process.
(4) Setting Standards for “AI+”
9. Verification of Bid Evaluation Reports. Develop intelligent review capabilities for bid evaluation reports to assist the tendering entity in verifying the data accuracy, logical consistency, and content compliance of the reports. The system automatically flags issues such as inconsistencies in the scoring of objective evaluation criteria, errors in score calculations, and excessive deviations in expert scores, prompting bid evaluation experts to review, confirm, and make necessary revisions.
10. Assist in award decisions. Based on bidding requirements, supply chain management, and historical transaction data—combined with data from relevant industry, credit, tax, and judicial platforms—create a multidimensional profile of the winning bidders. By incorporating methods such as virtual avatar presentations, the system assists the tendering entity in conducting comprehensive comparative analyses of winning bid candidates and making award decisions, ensuring that the entire award process is documented and traceable.
11. Signing of the Winning Bid Contract. The system automatically extracts the key contractual elements of the winning bid contract from the bidding and tender documentation. It then generates the contract by referencing relevant model texts and incorporating project-specific contract terms, enabling online signing and archiving of the contract. Based on policy and regulatory requirements, as well as historical transaction data, the system provides risk warnings regarding key rights and obligations in the winning bid contract, thereby reducing issues such as “shadow contracts” and arbitrary alterations.
(5) “AI+” On-Site Management
12. Trading Venue Coordination. Implement comprehensive, intelligent management of trading venues; efficiently allocate workspace resources and personnel; dynamically monitor all types of personnel and activities within trading venues; enhance the level of intelligence in trading facilities; and create an unmanned, smart trading environment. Strengthen coordination and collaboration among trading venues and promote the complementary use of resources to improve the convenience of cross-regional trading services.
13. Witness Management. Establish a closed-loop witness system comprising “intelligent analysis—dynamic intervention—on-chain evidence preservation” to provide seamless digital witnessing at every stage of bidding and tendering transactions, comprehensively and accurately recording the entire transaction process. Strengthen the analysis and early warning of anomalous behavior, promptly issue reminders and dissuade suspected illegal or non-compliant activities, enhance the reporting of leads on issues, and provide support for relevant authorities in enforcing discipline and the law.
14. Records Management. Establish an intelligent management system for tendering and bidding transaction records; integrate this with intelligent witnessing management to enable automated completion of transaction documents and on-chain evidence storage of transaction data. Implement intelligent naming and categorization of tendering and bidding transaction materials, automatically generate record indexes and summaries, and provide intelligent search and query services. Fully leverage the role of transaction records in policy performance evaluation, analysis of bid-rigging and collusion, dispute resolution, and cost reduction and efficiency improvement to enhance the comprehensive utilization of transaction records.
15. Smart Q&A. Build a specialized Q&A engine for the bidding and tendering sector that provides multimodal, interactive consultation services covering various policies, regulations, business knowledge, and operational procedures. This engine will offer features such as intelligent operational guidance, intelligent template recommendations, Q&A for anomaly alerts, and consultation on objections and complaints, thereby enhancing the convenience of bidding and tendering transaction services.
(6) “AI+” Regulation
16. Expert Management. Establish an intelligent management system covering the entire lifecycle of bid evaluation experts. By integrating factors such as professional competence, performance evaluations, credit assessments, and education and training, create multidimensional profiles of bid evaluation experts and support dynamic performance evaluations to enhance comprehensive management capabilities. Taking into account the specific realities of various industries, we will enable “one-network management” of bid evaluation experts nationwide and promote the sharing and joint use of high-quality expert resources.
17. Identification of Bid-Rigging. Establish a comprehensive early-warning system that provides full coverage of “entities + behaviors.” Through multidimensional data cross-referencing and entity profiling, the system identifies hidden issues such as identical corporate characteristics, abnormal entity relationships, bidding behaviors, and winning probabilities, as well as biased expert scoring tendencies. Conduct in-depth scans of bid documents, bills of quantities, and price lists. Through semantic similarity analysis of technical proposals and comparisons of key pricing characteristics in commercial bids, identify leads on suspected bid-rigging and collusive bidding, thereby providing reference for relevant authorities in enforcing discipline and the law.
18. Credit Management. Develop smart credit management capabilities for the bidding and tendering process to enable the objective recording, automatic aggregation, shared use, and dynamic adjustment of credit information. Create a smart credit evaluation model for bidding and tendering to build a multidimensional credit profile of entities, thereby conducting credit evaluations, information dissemination, and early warnings with precision and efficiency.
19. Collaborative Oversight. Develop analytical and early-warning models that cover the pre-bid, during-bid, and post-bid phases of projects; strengthen data collection, management, and utilization throughout the entire process; and, through data cross-referencing and comparative analysis, automatically identify issues such as failure to invite bids when required, illegal subcontracting or subleasing, unauthorized personnel changes, severe delays in progress, and discrepancies between low, medium, and high-level project completions. Strengthen the integration of administrative, criminal, and disciplinary oversight in the bidding and tendering process to achieve intelligent, closed-loop management—including early warning and referral of problem leads, collaborative investigation and enforcement, and feedback on results. This will enhance the capacity for in-depth analysis and handling of complex cases, fostering a smart regulatory framework characterized by “integrated governance through a single network” among administrative law enforcement, criminal justice, and discipline inspection and supervision.
20. Complaint Handling. Develop intelligent complaint handling capabilities for the bidding and tendering process to assist administrative oversight departments in analyzing complaint submissions. By integrating relevant policies, regulations, historical cases, and investigation findings, the system will generate preliminary review opinions, provide categorized recommendations for resolution, and assist in drafting complaint resolution decisions, thereby enhancing the efficiency of complaint handling. The system will also perform intelligent screening and processing of malicious complaints to strengthen efforts to prevent and address such complaints.
III. Standardizing Deployment and Implementation
(7) Scientific Organization and Implementation. Localities should scientifically determine implementation pathways based on practical needs and their technological foundations. For scenarios that enhance transaction efficiency and are suitable for market-driven advancement, efforts should be made to actively cultivate AI application service providers. For scenarios aimed at ensuring fair and impartial transactions and improving the quality and efficiency of regulation, emphasis should be placed on leveraging the government’s leading role, strengthening coordinated planning, and promoting efficient, centralized development. Prefectural-level cities should deploy and implement applications under the unified guidance of provincial authorities, while counties and lower-level administrative units should, in principle, reuse model resources provided by higher-level authorities.
(8) Strengthen system integration. All localities should continue to deepen the integration and sharing of public resource trading platforms; based on unified institutional rules and technical standards, they should carry out centralized upgrades in an orderly manner, enhance the standardization of bidding and tendering processes and related platform systems, strengthen the interoperability of relevant platform systems, and improve the efficiency of model deployment and application.
(9) Strengthen the data foundation. All localities should enhance data governance for bidding and tendering, improve data cleansing and annotation, and accelerate the development of high-quality datasets and knowledge bases covering bidding and tendering policies, regulations, and all stages of the process. By leveraging government data-sharing mechanisms, they should promote the joint development and sharing of high-quality datasets, as well as the collection and governance of generated data, to better support model training and application.
(10) Continuous Iteration and Optimization. Local authorities should establish a routine mechanism for upgrading AI models, promptly update datasets and knowledge bases, conduct targeted training using specialized data on bidding and tendering, continuously optimize model algorithms, and improve model accuracy. They should also establish a user evaluation and feedback mechanism to promptly collect and address user needs, refine application features, and drive the iterative optimization of models through user feedback.
(11) Improve the application mechanism. All localities should strengthen the integration of artificial intelligence applications with every stage of the bidding and tendering process, improve the mechanism for converting and applying content generated by models, and ensure that the models function to their full potential. The auxiliary nature of the technology must be upheld; conclusions generated by models do not replace the independent judgment of the tendering entity, tendering agencies, bidders, bid evaluation experts, and others, nor do they alter the statutory responsibilities of the entities using the technology.
(12) Enhance security standards. Strictly implement security management requirements for artificial intelligence models; strengthen security capabilities for model algorithms, data resources, infrastructure, and application systems; and rigorously carry out the filing and security reviews of algorithms and models. Establish a security protection system covering data, computing power, algorithms, and systems to ensure that models are secure and reliable, and to effectively prevent and address risks such as model “black-box” issues, hallucinations, and algorithmic bias.
IV. Strengthening Organizational Support
Provincial-level development and reform departments must effectively fulfill their roles in providing guidance, coordination, and overall leadership; intensify efforts in organization and implementation; actively coordinate to address data and computing power needs; work with relevant departments to promptly identify application scenarios and implementation pathways; promote implementation on a categorized basis; and improve application support mechanisms. They must also strengthen cooperation with universities, research institutes, and AI enterprises, fully leverage the role of AI enterprises, and promote the transformation of research into industrial applications; Efforts must be made to strengthen talent development and enhance cross-disciplinary talent cultivation. The National Development and Reform Commission, in conjunction with relevant departments, will strengthen overall coordination, carry out public outreach and risk management, guide local governments and central state-owned enterprises to deepen exploration and application in accordance with local conditions, improve supporting institutional rules, advance the development of a standards system, and promptly summarize and promote exemplary practices and approaches.
National Development and Reform Commission
Ministry of Industry and Information Technology
Ministry of Housing and Urban-Rural Development
Ministry of Transport
Ministry of Water Resources
Ministry of Agriculture and Rural Affairs
Ministry of Commerce
State-owned Assets Supervision and Administration Commission of the State Council
February 6, 2026