In February 2026, eight departments jointly issued a document. One detail in it went largely unnoticed: "bid compliance self-check", "tender document screening" and "AI-assisted bid evaluation" were written in as standard scenarios across the whole tendering and bidding process.
Which is to say: from this document onward, your bid document is no longer only read by people.
Less than four months remain until the first milestone it sets. In this article I take the few of the twenty scenarios that genuinely concern bidders and break them down one by one.
1. First, see how much this document weighs
In February 2026, the National Development and Reform Commission and seven other departments jointly issued the "Implementation Opinions on Accelerating the Promotion and Application of Artificial Intelligence in the Field of Tendering and Bidding" (NDRC Regulation [2026] No. 195).
Which eight departments? The NDRC, the Ministry of Industry and Information Technology, the Ministry of Housing and Urban-Rural Development, the Ministry of Transport, the Ministry of Water Resources, the Ministry of Agriculture and Rural Affairs, the Ministry of Commerce, and the State-owned Assets Supervision and Administration Commission — together covering essentially every competent authority for public resource trading in China.
This is not a "we encourage exploration" discussion draft. It comes with a timetable:
- By the end of 2026: key scenarios such as tender document screening, AI-assisted bid evaluation and bid-rigging detection reach full coverage in some provinces and municipalities;
- By the end of 2027: more key scenarios are rolled out nationwide.
The words "full coverage" matter. They mean these functions are not optional extras but prescribed actions that local trading platforms must build and must use.
The document lists twenty key scenarios spanning the entire process: tendering, bidding, bid opening, evaluation, award, management and supervision. I have sorted them into three groups:
(1) Used by the tendering side (it will read your bid)
Tender document drafting, tender document screening, bid opening, expert selection, AI-assisted bid evaluation, evaluation report verification, assisted award decision-making, and contract signing with the winner.
(2) Used by the bidding side (it helps you self-check)
Bid planning, and bid compliance self-check.
(3) Used by the supervisory side (it looks for collusion)
Expert management, bid-rigging detection, credit management, coordinated supervision, and complaint handling.
There is one more group easily overlooked — on-site management and the service side: venue scheduling, witness management, archive management, and intelligent Q&A.
2. How the machine will "read" your bid
Of the twenty scenarios I have picked four that concern you most directly, and take them one by one.
1. Tender document screening: a health check first
The document requires that, before publication, tender documents undergo intelligent screening — checking what? Whether clauses set unreasonable restrictions, whether they conflict with higher-level law, whether they are discriminatory.
What that means for bidders: the tender document you receive from now on may already have been run through a machine. Conditions that obviously set up a "tailored slot" will be more likely to be stopped.
Conversely, if you are used to exploiting vague wording in documents for room to manoeuvre, that room will shrink.
2. Bid compliance self-check: the most consequential one
This scenario is stated plainly — carry out a compliance self-check of the bid document, helping bidders find missing responses, format deviations, substantive clauses left unanswered and so on.
In plain language: the machine will take the requirements of the tender document and compare them against your bid line by line, to see whether you actually responded.
Anyone who has prepared bids knows that the most common cause of a rejected bid was never "the price is too high" but failing responsiveness review — one missing seal, one missing signature, one missing row in the clause-response table.
In the past such errors relied on human review, which came down to luck and time. From now on it is automated comparison.
So the subtext of this scenario is: people who prepare bids properly come out ahead. Because those who fudge it get filtered out by the machine first.
3. AI-assisted bid evaluation: squeezing "discretion"
Assisted evaluation does not mean letting AI decide the award. The document repeatedly stresses its "assistive positioning" — conclusions generated by the model cannot replace the evaluation committee's own judgement.
But it does do several things: structuring bid documents, extracting each scoring item one by one, and producing a preliminary comparison result.
The impact on bidders: the more structured your material is and the more accurately a machine can extract it, the better for you. A single paragraph used to be able to cover several scoring points, relying on an evaluator to "read it out"; from now on you may have to split it up and write against each scoring item.
4. Intelligent Q&A: another signal hiding in the policy text
Among the twenty scenarios there is one called intelligent Q&A — the text requires "building a professional Q&A engine for the tendering and bidding field, providing multimodal interactive consultation services on policies, regulations, business knowledge and operating procedures".
That one is directly relevant to what we do: the policy is explicitly requiring that tendering and bidding policies, regulations and practical knowledge be turned into a structured knowledge base that can be queried in Q&A form.
And one more sentence worth noting: in the section on "consolidating the data foundation", the document explicitly requires that datasets and knowledge bases be updated in good time.
In other words, a knowledge base is not a one-off build but continuous operation.
3. Three overlooked opportunities
Opportunity one: procurement-share policy and the AI wave overlapping
For several years government procurement has been making way for SMEs.
Under current rules, procurement of goods and services under 2 million yuan and works under 4 million yuan should in principle be reserved entirely for SMEs; projects above that threshold must also set aside a proportion for them.
On one side, shares are tilting towards SMEs; on the other, AI is making "responsiveness review" transparent.
For small businesses that do the work properly, this is good news. In the past you could not match a large company's dedicated bid team on responsiveness; from now on, with the machine setting one standard, what is compared is whether you genuinely responded clause by clause.
Opportunity two: "responsiveness" turns from a soft expectation into a hard threshold
Responsiveness review used to be manual and tolerated vagueness. Now, with a comparison engine, "substantive response" gets checked clause by clause.
That means the quality floor for bid preparation has been raised.
For people with a methodology, templates and a review process, that is a moat. For people still "finding a template online and editing it", that is a risk.
Opportunity three: the policy text devotes a clause to "cultivating service providers"
In its safeguard measures, the document explicitly mentions cultivating providers of AI application services and promoting a healthy application ecosystem.
Translated into business terms: AI applications in tendering and bidding are a direction policy encourages you to pursue. And the part of it that most resembles infrastructure — the Q&A engine for policy, regulation and practical knowledge — is exactly what a knowledge base is best at.
4. Three pitfalls to avoid
Pitfall one: thinking AI can "guarantee a win".
The document draws the line of responsibility clearly — AI conclusions are assistive and do not replace the evaluation committee's judgement. Any claim that "AI guarantees you the contract" does not hold up.
Pitfall two: ignoring the compliance requirements for algorithms and data.
The document's data governance section mentions security requirements for models and data. In this line of work, compliance is not a bonus point; it is the ticket in.
Pitfall three: treating "AI writes the bid" as a cost-saving tool.
The real value is not in generation but in clause-by-clause response comparison. Looking only at generation means using a small fraction of what the capability can do.
5. What I do myself
Recently I have been delivering knowledge bases and AI customer service to several small engineering firms.
One client asked me something I still remember:
"Is today's bid document written for people, or for machines?"
At the time I did not realise how important that question was. Only after reading this document clause by clause did I see it — the policy has already half-answered it.
My judgement is that the real window on the bidder's side is these three quarters: before "full coverage" spreads out, make responsiveness review a process and distil your own bidding knowledge into a searchable library.
That does not need a heavy technology investment. It needs someone to turn scattered requirements into a checklist you can audit against.
I spent years in operations management — building systems, writing SOPs, running internal audit reviews — and what I have always been best at is not "getting the work done".
It is turning "done" into "acceptably done".
With bid documents, it is the same thing in essence.
In closing
Policy gives direction, not orders.
But this time the direction is clear enough: tendering and bidding is being redefined as a process that is structurally readable.
Whoever sorts out their own response logic first adapts to the new rules first.
#tendering and bidding #AI #bid documents #SME #knowledge base
Have you or someone you know recently been caught out by "responsiveness review" when bidding? Where do bids most often fail — qualification conditions, commercial clauses, or clause-by-clause response to technical parameters?
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