AI Agents for Proposal Teams: RFP Volume Is Up, Headcount Isn't

Proposal teams have quietly become one of the most important revenue functions in many companies, and one of the most stretched. The latest benchmark data shows a team being asked to submit more bids with the same people, and turning to AI to keep up.

Loopio's 2026 RFP Response Trends & Benchmarks Report, based on a survey of 1,533 response management professionals across more than 17 industries, found that annual RFP submissions rose 9% over the prior year. For the first time, 50% of respondents ranked bandwidth as a top challenge. (Loopio sells RFP response software, so read its framing with that in mind, but this is one of the largest recurring surveys of proposal professionals available.)

The more interesting finding is what happened once AI arrived. Drafting got faster, but the overall workload didn't shrink.

More Bids, Same Team

The volume numbers are clear. According to Loopio's breakdown of the report, organizations now respond to an average of 166 RFPs a year, up from 153. Enterprise teams average 260, mid-market 164 and SMBs 79. Meanwhile:

• The average RFP team has held at 8 people for the fifth year in a row.
• Each RFP still pulls in about 9 contributors, a number unchanged since 2021.
• Fewer than half of teams (46%) gained any new headcount, budget or software.

Loopio describes bandwidth's jump to the number one challenge as "a 20-point surge" reflecting teams "significantly increasing their submission volumes without a corresponding increase in headcount."

The stakes are high. In Loopio's press release, CEO Zak Hemraj said RFPs influence 40% of company revenue, and 67% of teams say winning more RFPs is an important part of their sales strategy.

AI Already Writes the Answers

Proposal teams have adopted AI faster than most functions. Per the report:

• 79% of teams used generative AI in their RFP process, up from 68% a year earlier.
• 84% of those teams use it at least once a week.
• 62% use AI to generate specific RFP answers, up 16 points from 2024. Other common uses include editing and proofreading, first drafts, executive summaries and analyzing proposal quality.

And it has helped. The average RFP now takes 33 hours to complete, two hours faster than the year before.

But two hours is a small gain against a 9% increase in volume, and the report suggests why. Writing answers was never the whole job.

The Bottlenecks AI Writing Tools Don't Touch

Look at what's slipping in the same dataset:

• Bid qualification is eroding. The share of teams using a formal go/no-go process fell to 75%, an 8-point drop. Loopio's read is that "teams are bypassing formal evaluation to keep pace with mounting submission pressures." Top performers do the opposite: 81% of them use go/no-go.
• Win rates are down. The average team now wins 39% of its RFPs, below the 45% average for 2019 to 2026. Shortlist rates dropped from 54% to 46%.
• Portals are still manual. About 45% of RFPs are submitted through online procurement portals, which Loopio notes "typically create bottlenecks due to the manual bidding process."
• Leadership wants more. In the press release, 42% of respondents said leadership expects better results as AI becomes more integrated, and 32% said they're expected to take on new responsibilities.

The pattern is familiar: a tool that speeds up one step moves the bottleneck to the next one. Once drafting is quick, the slow parts are deciding which bids to pursue, chasing nine contributors for input, keeping the answer library current and getting everything into the buyer's portal on time.

Where AI Agents Fit in the Proposal Workflow

That remaining work is multi-step coordination, which is the kind of work AI agents (rather than single-prompt writing assistants) are designed for:

• Intake and go/no-go prep. Reading an incoming RFP, pulling the requirements, deadlines and evaluation criteria into a summary, and scoring it against the team's own qualification criteria so a person can make a faster, better-informed decision. That helps protect the process that top performers rely on.
• SME coordination. Sending each subject-matter expert only the questions they own, following up before the deadline, and assembling their replies in one place.
• Content library upkeep. Flagging answers that are out of date, contradicted by newer approved content, or reused so often they need a refresh.
• Compliance and completeness checks. Matching every requirement in the RFP to an answer in the draft and flagging gaps before submission.
• Portal preparation. Breaking the finished response into the field-by-field structure a procurement portal expects, so final entry becomes a check rather than an afternoon of copying and pasting.

In each case, people still decide what to bid on, shape the win themes and sign off on what goes out. The agent takes on the coordination work that currently consumes the team's time.

What Top Performers Already Do Differently

Loopio defines top performers as teams that win more than half their bids. They aren't simply using more AI. According to the report, they "use it for high-impact tasks: analyzing proposal quality, verifying accuracy, and interpreting data," and submit about 180 bids a year by "focusing on efficiency over effort." They also spend slightly more time per bid (35 hours versus the 33-hour average) on personalization and polish.

That's the model for agents: hand off the repetitive work so the team's limited hours go into the parts of a proposal that actually win.

What This Means for Proposal Teams Going Forward

Looking ahead, proposal professionals told Loopio the top skill they'll need is AI and automation (51%), ahead of content development (48%) and strategic planning (44%). The teams that pull ahead won't stop at AI-drafted answers. They'll apply automation to the whole bid process, from qualification to submission, and use the time saved to raise win rates.

Frequently Asked Questions

How many RFPs does the average company respond to each year?

Loopio's 2026 report puts the average at 166 RFPs a year, up from 153. Enterprise teams average 260, mid-market 164 and SMBs 79.

How many proposal teams use AI?

79% of teams used generative AI in their RFP process, up from 68% a year earlier, and 84% of those use it weekly. 62% use it to generate specific RFP answers.

What's the difference between an AI writing tool and an AI agent for RFPs?

A writing tool drafts an answer when asked. An agent carries out a multi-step workflow, such as summarizing a new RFP, routing questions to experts, following up, checking that every requirement has an answer and preparing the portal submission, and hands decisions back to a person.

Does AI improve RFP win rates?

Not by itself. Win rates fell to 39% even as AI adoption rose. Top performers, who win more than 50% of bids, use AI for quality and accuracy checks and keep a disciplined go/no-go process.