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How to Use AI in Proposal Management: 5 Practical Workflows

Learn how proposal and RFP response teams can use AI across five practical workflows: bid/no-bid preparation, first drafts, content adaptation, SME review preparation, and quality checks—while keeping humans in control of strategy, compliance, accuracy, and client relevance.

About This Webinar

About This Webinar

In this APMP Winning AI Essentials session, Olivia Hardy of QorusDocs shows proposal professionals how to use AI in five repeatable workflows without handing over strategy or accountability.

The session covers bid/no-bid preparation, first drafts grounded in approved content, buyer-focused content adaptation, targeted SME review preparation, and proposal quality checks. Olivia also explains where human judgment must remain, how to introduce practical guardrails, and why teams should prove one low-risk workflow before increasing automation.

Quick Answer

Proposal teams can use AI most effectively by delegating work that is repeatable, easy to review, and relatively low-risk. Five practical starting points are bid/no-bid preparation, approved-content first drafts, buyer-focused content adaptation, targeted SME review briefs, and proposal quality checks.

Humans should retain ownership of strategy, compliance, accuracy, and client relevance, with a named reviewer approving every client-facing output.

What You'll Learn

  • How to identify proposal work that is suitable for AI

  • Three filters for evaluating an AI workflow: repeatability, handoff potential, and risk

  • How AI can support structured bid/no-bid and go/no-go preparation

  • How to create traceable first drafts from approved content

  • How to adapt proposal content to a buyer’s language, priorities, and evaluation criteria

  • How to prepare focused review briefs that make better use of SME time

  • How to use AI for objective and judgment-based proposal quality checks

  • Which responsibilities should always remain with proposal professionals

  • How to establish human review gates and practical AI governance

  • How to test a workflow safely using a previously submitted bid

Key Takeaways

  • AI should remove repetitive work, not replace proposal strategy or professional judgment.
  • Strategy, compliance, accuracy, and client relevance remain human responsibilities.
  • Better instructions and governed source content produce stronger, more trustworthy AI output.
  • AI can prepare and structure SME reviews so experts spend time only on decisions requiring their expertise.
  • Objective checks can be delegated more safely than checks requiring interpretation or judgment.
  • Teams should move from AI assistance to task delegation and automation only after the previous stage becomes predictable.
  • One of the most valuable AI investments a proposal team can make is improving its content governance.
  • Start with one low-risk workflow, test it on a past bid, document the results, and expand from there.

Who This Webinar is For

This webinar is for proposal and bid managers; RFP and RFI response teams; proposal writers and content managers; business development professionals; subject matter experts involved in proposal reviews; sales enablement, revenue operations, proposal operations, and transformation leaders; teams evaluating generative AI, AI assistants, AI agents, or proposal automation; and security, legal, and governance stakeholders assessing the use of AI in client work.

Key Topics Covered

  • Choosing the right AI workflows: How to prioritize proposal work that is repeatable, easy to review, and relatively low-risk.
  • Bid/no-bid preparation: How AI can evaluate opportunity information against documented criteria and structure more productive go/no-go discussions.
  • Approved-content first drafts: How to produce traceable proposal drafts grounded in approved sources while clearly identifying missing information.
  • Buyer-focused content adaptation: How AI can tailor approved content to a client’s vocabulary, priorities, and evaluation criteria without changing the underlying facts.
  • SME review preparation: How AI can create concise context and targeted questions so subject matter experts focus on decisions requiring their expertise.
  • Proposal quality checks: How AI can identify unanswered requirements, word-limit issues, contradictions, unsupported claims, and other potential problems for human review.
  • Human review and AI governance: Why strategy, compliance, accuracy, and client relevance must remain human responsibilities supported by clear review gates and practical guardrails.

FAQs

How can proposal teams use AI?

Proposal teams can use AI to prepare bid/no-bid decisions, assemble first drafts from approved content, adapt responses to buyer priorities, create targeted SME review briefs, and identify potential quality or compliance issues.

Which proposal responsibilities should remain human?

Humans should retain responsibility for strategy, compliance sign-off, factual accuracy, client relevance, and final approval of anything delivered to a buyer.

What is the best proposal workflow to automate first?

Start with work that is repeatable, easy to review, and relatively low-risk. Test the workflow on a previously submitted bid before introducing it into live client work.

Can AI confirm that a proposal is compliant?

AI can identify missing answers and surface potential compliance issues, but it cannot fully confirm compliance. Final compliance decisions require human review and judgment.

How can AI improve SME reviews?

AI can summarize the relevant context and generate a small set of targeted questions for the SME. This allows the expert to focus on technical fit, decisions, constraints, and facts only they can verify.

When should proposal teams use AI agents or automation?

Teams should introduce agents or automated workflows only after the underlying task has become predictable and consistently produces trustworthy results with an effective human review gate.

Ready to reduce repetitive proposal work?

See how QorusDocs helps proposal, sales, and business development teams manage RFP responses, pitches, and proposals with AI-powered automation and Microsoft 365 integration.
Request a Demo
Video Transcript

 

Darby:
Good morning, good afternoon, or good evening, wherever you are in the world. My name is Darby, and I am thrilled to have you for Winning AI 2025, day two.

We are thrilled to have you join us for this next session, “From Process to Purpose: Automating Unnecessary Steps in the Proposal Journey.”

If you have any questions during the presentation today, please submit them through the Q&A function. This session also has a designated forum for ongoing discussion, collaboration, and networking.

Now, without further ado, I’ll pass the floor to our presenter today, Olivia Hardy, Director of Product Marketing and Proposal Strategy at QorusDocs. Here with her today to help moderate the chat and questions is Kelly Sichel, Senior Product Manager at QorusDocs.

Olivia Hardy:
Thank you so much, Darby. Thanks everyone for joining. I’m excited to be kicking off this first session of day two.

My name is Olivia. I’ve been working with QorusDocs since 2013. I’ve had a career in sales prior to joining QorusDocs, and at QorusDocs I’ve worked across pre-sales, customer success, customer experience, implementation, adoption, strategic bids, and proposals.

My team and I also use QorusDocs as our proposal automation and RFP response software when we respond to RFPs and create proposals. That gives me a perspective as both an active user of the QorusDocs platform and someone who has helped many others on their proposal software adoption journey.

Today we are looking at how AI can help proposal teams move from process to purpose.

AI is very good at automation, particularly automating repeatable and tedious parts of a process. But AI does not exercise judgment, care, empathy, intuition, or years of lived experience. Those are still human strengths.

The goal is not to remove people from the proposal process. The goal is to remove unnecessary repetitive work so people can spend more time on the work that matters most.

A process question might be, “Did we complete every section?” A purpose question might be, “Have we made it easy and low-risk for the customer to choose us with a clear and confident narrative?”

AI can strip away repeatable overhead and give us the headspace to choose the right deals, craft the right story, protect the business, and help the team succeed.

The real power of AI is not only one huge automation moment. It is the sum of all the small ones: the little steps that disappear, the tasks that get faster, and the cumulative value those improvements create.

In the demo, I’ll show how QorusDocs can help throughout the proposal development process, including early RFP review, bid/no-bid preparation, proposal drafting, and finalist presentation preparation.

For this demo, I’ve already set up an RFP pursuit in QorusDocs. The pursuit is the collaborative workspace where we keep the information about the RFP, the customer documents, internal planning documents, assignments, recommendations, and everything else we need to do a good job.

I’ve uploaded an RFP from a fictional company, Blue Sky. One of the first things I want to do when I receive an RFP is prepare for a bid/no-bid decision meeting with key stakeholders. To do that, we need information about the opportunity.

Using QPilot, the QorusDocs AI assistant, I can ask it to read the RFP and draft an email to my team. The email can summarize the RFP background, key requirements, evaluation criteria, and timeline. This gives me a strong starting point that I can review and adjust before sending.

Next, I can use a Smart Skill to support the bid/no-bid process. The skill uses the context I provide and asks for additional information that may not be in the documents, such as our relationship with the client, whether we have the capacity and expertise to deliver the work, and whether we can price competitively and profitably.

The Smart Skill can then generate an output based on the configured framework. This is highly configurable, so teams can align it with their own criteria, internal processes, and decision-making approach.

The important point is that AI is not making the final decision for us. It is helping organize the information, apply a consistent framework, and create a strong starting point for human review.

After the bid/no-bid process and kickoff, we can use QorusDocs to help create an RFP response template and draft response content. The goal is to accelerate the repeatable steps while still allowing the proposal team to apply expertise, refine the story, and ensure the response is accurate and fit for purpose.

Later in the process, if we are selected as finalists, we may need to prepare a PowerPoint presentation or oral presentation. We can use the completed response as context to help create a finalist presentation, pulling forward relevant information from the proposal.

This is where the compounded savings become important. It is not only about saving time. It is also about improving quality, reducing repetitive work, supporting consistency, and helping teams focus on the strategic parts of the pursuit.

Our goal is to simplify the process so proposal professionals can focus more on purpose. AI can help automate and streamline repeatable work, but humans remain in control of the output.

Darby:
Thank you, Olivia, for such a wonderful session. And Kelly, thank you for moderating. Please take a few moments to complete the session survey. We hope you all have a great rest of your day at Winning AI.