Your team just spent 120 hours on an RFP.
If your first reaction is a tired little laugh, like, “only 120?”, then you’re not alone. RFPs have a special talent: they start as “just answering questions,” then turn into a company-wide scavenger hunt that leads to more questions.
This is where AI solutions can help, but not in the way most people think.
The goal isn’t to have AI “write proposals.” The goal is to remove the parts that secretly eat the calendar: hunting for past answers, reconciling versions, fixing contradictions, chasing approvals, and trying not to accidentally promise something that will later choke on a legal issue.
If you want the bigger picture of workflow-first AI (beyond proposals), it’s worth seeing how AI solutions focus on building repeatable processes instead of one-off automations. Now, let’s bring that same mindset into the RFP world.
Most RFP time isn’t spent writing. It’s spent assembling.
Someone looks for the “approved” security response and finds four different versions. Someone else reuses an old case study, then gets told it’s outdated.
Engineering answers one question in plain English, sales rewrites it, legal softens it, then security adds a caveat, and suddenly you’re three hours deep on a paragraph nobody even likes.
RFPs are a coordination problem disguised as a writing task. That’s why AI wins when it reduces coordination friction, not when you use it to be your copywriter.
A lot of teams only bring AI in when they’re already behind. They paste questions into a chatbot, get a draft back, and then spend the same amount of time verifying, rewriting, and getting approvals.
You don’t actually save time. You just spend it somewhere else.
A better approach is to use AI right after you receive the RFP, before anyone starts answering, so you can stop wasting effort on confusion and rework.
Here’s what that looks like in practice.
Before the team writes a single sentence, AI should help you understand what you’re actually committing to.
You want a clear summary of scope and deliverables, a list of hard requirements vs. nice-to-haves, and a quick spotlight on anything that could derail the deal later, like data handling, liability language, SLAs, deadlines, and compliance requirements.
This step sounds basic, but it’s where you gain momentum and win the deal. You’d be shocked at how many RFP efforts go sideways because the team starts answering without a shared understanding of what the buyer is truly evaluating.
If you only do one thing to cut RFP hours, do this:
Create a controlled library of your best, approved answers—your “Answer Core.” Not a messy folder of old proposals. Not a graveyard of PDFs. A complete and comprehensive set of responses your team trusts.
Think about the categories that show up in almost every RFP: company overview, implementation approach, support model, security controls, privacy posture, legal terms, and proof points.
These sections shouldn’t be rewritten every time, as if it were an English exam. They should be reused, tailored, and updated on purpose.
Once the Answer Core is complete, your AI tool becomes more reliable. It’s no longer inventing. It’s retrieving and adapting what you’ve already approved.
Instead of a human reading 200 questions and thinking, “Where do we even begin?” AI can match each question to the closest response in your Answer Core and create a structured first draft that’s actually grounded in your real content.
Now the team isn’t staring at a blank page. They’re reviewing and tailoring. That shift alone changes the entire feel of the process.
It also helps you spot gaps early. If 20 questions don’t map to anything credible in your library, you immediately know what needs SME input without dragging everyone into meetings just to discover you’re missing key details.
The fastest RFP teams aren’t the ones that “write quickly.” They’re the ones that review cleanly.
A sane review flow has lanes: sales reviews, positioning, and differentiation. SMEs review technical accuracy in their domain. Legal reviews risk language and commitments. Security reviews controls and policies. Then one person owns final consistency and packaging.
AI can help by making reviews less painful. It can standardize terminology across sections, keep answers within word limits, and flag places where the same concept is described two different ways.
That might sound small, but it’s the kind of small that saves an entire afternoon.
This is also a good moment to connect to the AI tools stack for leaders, because if you’re responsible for standardizing tools and governance across teams, the RFP workflow is where “AI chaos” shows up fast. A clear tool stack and clear rules keep speed from turning into risk.
Most avoidable RFP losses aren’t dramatic or significant. They’re mostly due to small mistakes and missed procedures.
A missing attachment. An unanswered question. A contradiction between two sections. A claim that sounds stronger than your policy allows. A requirement you thought you addressed, but actually didn’t.
Before submission, use AI to check consistency and completeness. Have it scan the full response and flag issues humans miss when they’re tired and staring at a screen for the fifth straight hour.
This is the real advantage of maximizing AI tools for your RFP process: fewer self-inflicted inefficiencies.
It can be, if you stop treating it as a cure-all or a magic pill and start treating it as a process that you have to build from the ground up.
The safest model is simple: AI drafts from approved material, humans approve commitments, and sensitive inputs remain under governance. You don’t want a workflow where someone can paste confidential buyer data into whatever tool they found on a normal workday.
You want something repeatable, controlled, and auditable. In other words, the same standard you’d apply to pricing approvals or contract redlines should apply here, too.
If “overhaul our whole RFP process” sounds like a project that will never get scheduled, start smaller and more realistically.
Pick one upcoming RFP and do two things differently: build a starter Answer Core from your most common questions, and use AI to triage and map questions before the team writes. That’s it.
Then measure what happened. Did you reduce back-and-forth? Did you cut rework? Did legal get cleaner inputs? Did SMEs spend less time repeating themselves?
After two or three cycles, you’ll feel the compounding effect. The fourth RFP won’t cost 120 hours because you’re not rebuilding the same knowledge from scratch. You’re running a system.
That’s how you use AI to win more RFPs: not by writing prettier paragraphs, but by shipping a faster, cleaner, more consistent workflow that buyers can trust.