Yes, you can use ChatGPT to help write a tender or RFP response, and many bid teams already do. It is good at summarizing long tender packs, drafting first answers from material you give it and tightening prose. What it cannot do on its own is know your company's approved facts, keep answers consistent across every document in the bid, or guarantee that each requirement is met. So every answer still needs a verified source and a person's approval before submission.
This guide is for bid managers, presales leads and small business owners who have started pasting RFP questions into ChatGPT and want to know where that helps, where it creates risk and what buyers think about it. If your organization bans generative AI tools outright, this article will not change that policy.
Key takeaways
- Loopio's 2026 benchmark reports that 79% of RFP response teams used generative AI in 2025, up from 68% the year before.
- UK guidance under Procurement Policy Note 017 states that suppliers' use of AI in bids is not prohibited, but buyers may ask suppliers to disclose it.
- ChatGPT drafts well from material it is given, but it does not know a company's approved answers unless someone supplies them for every task.
- OpenAI states that by default it does not train on data from ChatGPT Business, Enterprise, Edu or its API, which matters when tender documents are confidential.
- AI-drafted tender answers carry a risk of hallucination, so every factual claim, price and commitment needs checking against a source before submission.
Can you use ChatGPT for an RFP or tender response?
You can, and you will not be alone. In Loopio's 2026 RFP Response Trends and Benchmarks Report, 79% of response teams said they used generative AI in 2025, up from 68% the year before. The question has shifted from whether to use AI to which parts of the response to trust it with.
Public buyers have taken a position too. The UK government's Procurement Policy Note 017 on AI use in procurement states that suppliers' use of AI to develop bids is not prohibited, and it compares AI to a bid writer the supplier has hired. It also lets contracting authorities ask suppliers to disclose their AI use, warns that AI tools can introduce misleading statements through hallucination, and suggests buyers may carry out extra due diligence, such as clarification questions or presentations, to confirm a supplier can actually deliver what the bid describes.
Read together, the message to bidders is clear. Using ChatGPT is acceptable. Submitting something you have not verified is not, and a buyer may test whether the capability on the page exists in your company.
What does ChatGPT do well in a tender response?
ChatGPT is a strong writing assistant. It works best on tasks where the facts are in front of it and the job is to read, summarize or rephrase. It works worst on tasks that depend on knowledge it does not have, or on consistency across many documents and many days.
The highlighted row is the one that catches teams out. A tender response is not one answer but dozens, spread across a technical proposal, a questionnaire, a pricing schedule and sometimes a presentation. When each is drafted in a separate chat, the hosting region, the service levels or the team size can quietly differ between them, and evaluators read those differences as risk.
Where does ChatGPT fall short on an RFP response?
The limits of ChatGPT in bidding are not about writing quality. They come from what the tool can see and what it is designed to manage.
It does not know your company unless you tell it every time
Your approved answers live in past proposals, policies, case studies and the heads of your experts. ChatGPT sees only what you paste or upload into the conversation. When a fact is missing, a general-purpose model tends to write something plausible rather than say it does not know. In a bid, a plausible certification or a plausible response time is a commitment you did not mean to make. A maintained content library is what normally solves this, but someone still has to feed it to the chat.
It does not manage compliance
Winning starts with answering every requirement in the buyer's structure. ChatGPT can help list requirements, but it does not track which ones are answered, by whom and where. That is the job of a compliance matrix, and it has to sit outside the chat and be checked by a person against the documents.
It does not coordinate a team
Bids involve sales, presales, security, legal and finance. A chat is a conversation with one person. It has no shared tasks, no approval step and no record of who validated which answer, which is exactly what you need when a buyer asks a clarification question three weeks later.
It does not know this buyer
The answers that score highest refer to what the buyer said: their constraints, their systems, the problem in their own words. That context lives in your CRM, your call notes and your emails, not in the tender PDF. Without it, ChatGPT writes a competent generic answer, and generic answers score poorly against specific evaluation criteria.
What an evaluator sees in an unedited AI answer
Take a typical requirement: "Describe how you will ensure continuity of service during the transition from the incumbent." An answer drafted by ChatGPT with no source material usually reads like this: "We follow a proven, structured transition methodology that ensures seamless continuity of service, leveraging best practices and an experienced team to minimize disruption."
Nothing in it can be scored. It names no steps, no timeline, no people and no fallback. An evaluator with a scoring sheet gives it the same mark as a blank, and may note that it reads as generated. The same model, given your transition plan from a past contract and the buyer's stated go-live date, can draft an answer that names the phases, the parallel-run period, the handover checklist and the reference where you did it before. The difference is not the model. It is the material it was given and the person who checked it.
Is it safe to paste tender documents into ChatGPT?
It depends on two things: your ChatGPT plan and the buyer's terms. On the first, OpenAI states on its enterprise privacy page that by default it does not train its models on business data from ChatGPT Business, Enterprise, Edu and its API platform. Consumer accounts have a data control setting that decides whether conversations can be used to improve models, so check it before uploading anything sensitive.
On the second, many tender documents carry confidentiality clauses, and some public buyers restrict how their documents can be used. PPN 017 asks contracting authorities to consider controls that stop suppliers using confidential tender information as training data for AI systems. Read the instructions to bidders before uploading a tender pack anywhere, and never paste personal data or another client's confidential information into a consumer account.
How to use ChatGPT for an RFP response safely: a six-step workflow
If you use ChatGPT for bids, a simple workflow keeps the speed and removes most of the risk.
- Check the rules first. Read the tender for confidentiality terms and any AI disclosure question, and check which ChatGPT plan you are using.
- Build the requirement list yourself. Use ChatGPT to propose a list if you like, then check it line by line against the documents and keep it in your own compliance matrix.
- Give it the sources, not just the question. Paste the requirement text, your approved answer from a past bid and the relevant facts. Ask it to use only that material.
- Ask it to flag gaps. Tell it to mark any statement it cannot support from the material you provided, instead of filling the gap.
- Verify every fact, number and commitment. Certifications, response times, staffing, prices and legal terms are checked by the person who owns them.
- Review the whole response together. Read the technical answer, the questionnaire and the pricing side by side to catch contradictions before the evaluator does.
Three prompts that work better than "answer this question"
For requirement extraction: "From the attached section, list every requirement, instruction and evaluation criterion as a table with the section number, the exact wording and whether it is mandatory or scored. Do not paraphrase the wording."
For drafting: "Answer requirement 4.2 using only the approved answer and facts below. Start with one sentence that states how we meet the requirement. Mark any claim you cannot support from this material with [CHECK]."
For review: "Score this answer against the evaluation criterion below on the buyer's 0 to 5 scale, as a strict evaluator would. List what is missing to reach the top score."
When should a bid team move beyond ChatGPT?
ChatGPT is usually enough for a team that answers a few short RFPs a year. The signals that it is no longer enough are practical: you paste the same company facts into every chat, answers about the same topic differ between documents, contributors work in separate conversations nobody else can see, and the final assembly into the buyer's templates still takes days.
Cobl is the AI deal assistant for teams selling complex solutions. It does not ask you to give up the AI you already use: Cobl's deal context and capabilities are available inside ChatGPT and Claude. What it adds is the layer around the model. It keeps persistent context for each deal (the tender pack, the CRM record, the calls and emails), puts your approved company knowledge in the Shared Drive to work on every answer, produces the full response package in the buyer's formats, and lets sales, presales and experts contribute to the same deal with permissions and validation. Keep your general-purpose AI; use Cobl to turn company knowledge into repeatable bid execution.
We tested 15 AI models on a real public-sector RFP and published the results in our RFP model benchmark. On the customer side, Free Pro reports going from several days to 2 hours per RFP response, according to Albéric Mulliez, Director of Solutions and Services, in its customer story. That is the customer's own figure. A person still approves every answer before it leaves. To see the difference on your own documents, test Cobl on a live RFP.
Use it as a writer, not as the bid
ChatGPT can make a bid team faster at reading, drafting and editing. It cannot decide whether to bid, know what your company has promised before, or take responsibility for what you submit. Use it where it is strong, keep the facts, the compliance check and the approvals with your team, and answer any disclosure question honestly.
Can you connect ChatGPT or Claude to Cobl?
Yes. Cobl has an MCP server, so you can keep working in ChatGPT or Claude and hand bid work to Cobl from the same chat. MCP (Model Context Protocol) is the open standard both assistants use to connect to outside tools. Once Cobl is connected, the assistant works from your Cobl workspace, not only from what you paste into the conversation.
This closes the gaps described earlier in this guide. From a ChatGPT or Claude chat, you can open the deal for a tender, read the tender pack stored in it, search the Shared Drive for approved answers and start the response documents. The work runs in Cobl, with the deal context, company knowledge and access rules your team already set up. The documents stay in the deal, so colleagues review the same version instead of a copy pasted from a chat.
The rule from this guide does not change. A person approves every answer before it goes to the buyer: MCP changes where you start the work, not who signs it off.
