Buy AI RFP software for the work beyond the draft
Any capable AI writes a decent first draft now. Judge AI RFP software on the rest: running the process, routing work to the right experts, and keeping a record of what happened.
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Typically, a bid team evaluating AI RFP software pastes questions from a previously answered RFP into each trial and compares how well each vendor answers. Now that any capable model can write a decent first draft of an RFP answer, we think AI RFP software is worth buying for the work beyond the drafting. That means running your own process, working the plan back from the submission date, routing each part to the right experts for validation and approval, and keeping a full record of who changed and approved what.
A team evaluating this kind of software may currently use general-purpose AI in one of its forms: a chat assistant, an AI capability bolted onto an existing tool, or a tool it built in-house.
Most RFP packs hold several files. The main requirements document holds qualifying questions that each carry a word limit and ask for supporting documents. Alongside it come a security questionnaire, an ESG questionnaire, and the contract requirements, sometimes with the draft contract and its indemnity clauses.
A trial focused on drafting measures what each tool shares
Many bid teams evaluate AI RFP software as a drafting engine, and so do the “best AI RFP software” roundups. They rank tools on how well each answers those pasted questions, and on time saved. Their case is that the answer is what the buyer scores, and speed to a first draft is easy to measure in a trial.
Since general-purpose AI in any form now writes a decent first draft, such a trial measures what every candidate in the RFP response software category shares. It leaves out the work that sets the tools apart.
A team that primarily focuses on drafting can end up with fluent answers while planning, routing, and the approval record stay completely manual, so that work is what the trial has to test. Run it on a whole tender pack from a bid your team has already submitted, and ask four questions of each tool:
- Does it support your process?
- Does it execute according to your plan?
- Does it route each part to the right subject matter expert for validation, approval, or sign-off?
- Does it keep a full record of what happened, when, who changed it, and who approved it?
Work starts from the whole tender pack
The work starts well before the writing. Whatever documents the pack holds, your team turns what it finds in them into something it can use, through a process built for your organisation. That process runs in detailed steps so that the team misses nothing, and AI RFP software should carry out each step the way your team does it.
The plan works that process back from the submission date, step by step, so everyone knows who does what by when and the final deadline holds. Once each file’s requirements are read out, the plan also has to hold the links between them.
In a typical pack, the answer to the data-hosting question in the security questionnaire has to agree with the delivery model in the main requirements document. The indemnity clause sits in the draft contract, in a different file from the scored questions. Sample questions pasted one at a time show none of these links.
In the trial, check whether the plan built from the whole pack assigns an owner and a date to every step, the questionnaire’s questions and the contract’s clauses included.
Each answer goes to the right experts
Each answer needs validation and approval from the right experts. In a typical RFP, that means the product expert for the delivery model, the security lead for the data-hosting question, and legal counsel for the indemnity clause. Getting each part to its appropriate owner, chasing it, and seeing it through to sign-off is the hard work the software has to carry.
The route is the one your team already runs: from the sales and product subject matter experts (SMEs) through legal, compliance, or other specialist review to a final sign-off by an approver. It is also where response work slips or gets rushed, waiting on an SME or on a legal review brought in late.
Check whether the software carries each question’s route, with its owner, reviewer, approver, and status, and shows what is waiting on whom, so the quality of the response never rests on an indemnity answer legal counsel did not see.
The record outlasts the bid
Years after award, the buyer, your own lawyer, or an external auditor can challenge you on a submitted answer: what it promised and who approved it. By then, the person who drafted the answer in an AI chat, or built the team’s own tool, may have left the organisation.
In the EU, for example, an EU institution’s draft framework contract makes the winning bid, including the clarifications the supplier gave during evaluation, an annex that forms part of the contract.
The NIST AI Risk Management Framework expects roles and responsibilities for managing AI risk to be documented, and processes for human oversight to be defined and documented. We think a similar approval record for each answer is how a bid team shows that oversight in its own work.
A trial should show, for each submitted answer, the names of whoever supplied, changed, and approved it, with the date, and whether that approval record exports for a buyer’s or an auditor’s question.
Evaluators score the answer you submit
Experienced bid writers on the team will push back: the buyer’s evaluators score the words on the page, so draft quality wins bids and should lead the choice.
What they score is the answer that went in: the one the SME corrected, legal counsel cleared, and the team cut to the word limit. A fluent method statement on the delivery model that skips that review and runs past its word limit, or an answer that contradicts the indemnity wording legal counsel cleared on an earlier bid, costs the team more than a weak draft caught in review. In the UK, for example, government guidance says a contracting authority may disregard a bid if the supplier broke a procedural requirement in the tender documents, such as exceeding the prescribed word count.
Fluent text still needs a reviewer: NIST’s Generative AI Profile names confabulation, false content stated with confidence, as a risk of generative AI. The only answer worth reusing is the approved one, with its owner and review date attached, so the same commitment goes out on every bid.
Keep, build, or buy depends on who runs the process
Keeping general-purpose AI gives your team a decent first draft, fast, for whoever is typing. Around each answer, the team itself puts together, runs, and maintains the process. A team can also keep its assistant and ground it in a governed platform, so the decision is whether to build, to buy, or to keep the assistant and ground it.
| Option | What the team gets | What it maintains | Whom it suits |
|---|---|---|---|
| Keep general-purpose AI | A decent first draft, fast, for whoever is typing | The plan, the routing, the sign-off, and the record around each answer | A team that wants drafting help and runs review and sign-off elsewhere |
| Build in-house | Its own tool, set up around its process | Permissions per contributor, review and sign-off per question, a library of approved answers with an owner and review date on each, checks on answer quality as models change, and someone to run it when its builder moves on | A team with ongoing engineering capacity and one fairly simple process that rarely changes |
| Buy dedicated software | A tool it chose by testing the plan, the routes, and the record in its trial | Its own content, and a check that the tool still fits its process | A team with a complex process that wants that work carried for it |
An in-house build also leaves the team dependent on whoever built it. For a team leaning towards buying, comparing the alternatives on the plan, the routes, and the record is the next step.
SEQUESTO aOS, for example, carries the work around each answer for your team: James, its orchestrating agent, reads the tender alongside your organisation’s governance process and places each sign-off stage in the bid’s timeline as a milestone, with a named reviewer and time set aside. SEQUESTO logs every action, approvals included, with who took it and when.
Judge the work beyond the draft
Trial each tool on a whole pack from an RFP your team has already submitted, and judge the planning, the routing, and the approval record it produces. Bring your sales and product experts, security lead, and legal counsel into that trial, since the routing is tested on their answers and on legal review. Draft quality comes last, as a check that every shortlisted tool should pass.
