Security Questionnaires and Requests for Proposals (RFPs). Chances are if you work in B2B sales, security, or ops you’ve run across these time-consuming titans before. 

Understanding the differences between them is crucial to building trust and selling efficiently. 

Below we’ll explore what makes each unique, how AI solutions should account for their specialized nuances and why generative AI is the perfect solution to automating completion of both.

What is a Security Questionnaire?

Purpose: Security Questionnaires are designed to evaluate a vendor’s security practices and ensure they meet the required standards. 

Example: J.P. Morgan is buying Figma’s software. They want to know that Figma is practicing J.P. Morgan’s definition of a suitable level of security. 

Content: These tend to be fairly technical documents and usually have detailed questions about data protection, risk management, regulatory compliance, and security policies. They often come in Excel, PDF, and Word and online portal-based formats - sometimes with enough hidden cells and multiple choice answers to make your head spin. 

Benefits of a Security Questionnaire: The main goal is to verify a vendor’s security measures are robust and aligned with mitigating potential risks.

What is a Request for Proposal (RFP)?

Purpose: A request for proposal (RFP) is a business document that announces that a company needs a vendor for a specific project or service. A business (or the entity requesting the bids) will publish the RFP that details the scope of the project if they want a large group of vendors or privately to a hand selected group they want to compete against one another. Interested parties submit answers to the request for proposal (RFP) that meet the requirements and hope to be shortlisted and win the contract against the other companies that respond.

Example: J.P. Morgan wants to buy design software. They release an RFP privately to Figma, Adobe, and Canva -- all potential vendors -- who need to position their best selves as the best solution.

Content: They typically include a mix of high-level and detailed asks: such as company information, requirements, product differentiation, pricing, and proposed solutions.

Benefits of a Request for Proposal (RFP): The objective is to assess the suitability, expertise, and cost-effectiveness of potential suppliers and choose the best vendor; it is a chance for vendors to gather information and show their best selves in an executive summary.

Key Differences Between Security Questionnaires and RFPs

Security Questionnaire vs. Request for Proposal (RFP)

When It's Used

  • RFP Process: Typically early in the sales cycle so the buyer can move vendors from the big pile to the little pile
  • SQ Process: Typically midway in the sales cycle so the buyer can evaluate the capabilities offer versus risk incurred


  • RFP: Evaluate capabilities and see how they match up against selection criteria
  • SQ: Evaluate security risk


  • RFP: Strategic, Sales and marketing-focused
  • SQ: Detailed, Security and privacy-focused


  • RFP: Mix of business and technical information
  • SQ: Mostly technical security and compliance information (sometimes business information)


  • RFP: Company information, Product or solution differentiation, RFP requirements satisfaction, Pricing
  • SQ: Data protection, Cloud security, Incident management, Privacy and legal, Risk and vulnerability management, Security governance, Vendor management, Personnel security, Disaster recovery, Application and data security, Device and access management

Main Sources of Content

  • RFP: Product marketing (new releases, product launches, slide decks), Corporate strategy (M&A, new markets), Information Security, Legal and Privacy, Finance, Sales, Product, Engineering
  • SQ: Information Security, Legal and Privacy, Compliance, Finance, Product, Engineering

Why legacy RFP software causes teams to spend more time than necessary on responses

Why are current solutions failing to address the team's needs in a typical RFP process?

Currently, the best solutions out there for automating the RFP process rely on keyword matching to "match" the question being asked on an RFP to an underlying source, typically a knowledge base of question and answer pairs. These tools can only confidently generate the right answer 40-50% of the time which means teams using these vendors to generate RFP answers are stuck re-writing the answers they get from this automation.

These legacy tools deal with the complexity of RFP sources by building out unwieldy knowledge bases that balloon to thousands of question and answer pairs. The result? Teams are swamped maintaining a “database” that quickly goes out of date. 

Not only is the maintenance load a burden, but the answers the software generates still has high inaccuracies because of limitations with keyword matching. 

Why are current solutions failing to address the team's needs when answering Security Questionnaires?

The RFP vendors of the last 5+ years have largely been hacked to work for security questionnaires to varying degrees of success. It hasn't been a slam dunk for teams hoping to work on both types of question answering because of the different topic areas and trouble the legacy software has with differentiating between nuance and context when the same question is asked in a variety of different ways.

And for a time these legacy RFP tools were “good enough”. Unfortunately, the response nuances, sources, and detail level for security questionnaires never made it into product prioritization. Today, with generative AI, “good enough” is no longer the only option. 

What is needed to better automate answering a request for proposal and security questionnaires?

Where legacy Request for Proposal (RFP) automation software falls short:

  • Not generating the right answer the first time causing more time spent on re-writing
  • Teams having to sift through dozens of matches to find the source data they're looking for
  • Teams using legacy proposal software to answer both have to store Q&A pairs for dozens of different topic areas
  • Legacy RFP technology can't understand context or nuance of questions asked so a question and answer pair must be stored for every question imaginable (including the same question written in ten different ways)
  • Teams having to dedicate a FTE to managing the content in the knowledge base since you need thousands of pairs just to get the tech to work properly
  • Keeping a knowledge base updated is an ongoing, manual, and tedious task

Advanced LLMs, GenerativeAI, plus high quality workflows built together from the start are driving more accuracy and less maintenance for RFP and Security Questionnaire answering

Why is Generative AI the best solution for tackling an RFP and Security Quesitonnaires?

Generative AI can be used to answer both a security questionnaire and an RFP! Because generative AI can better understand nuance and context and read from a variety of sources to answer a proposal or security questionnaire quickly with customer-ready answers, it is the clear choice for teams having to respond to tens and hundreds of these proposals and/or security questionnaires a month.

But anyone can slap AI on a product these days - so what’s the key to getting 90%+ accurate responses and actually saving time?

1. Ingest every data source: public sources (like a website or Help Center), documents (like release notes or infosec policies), private sources (like a Google Slide deck), past answers, and a curated knowledge base collectively increase the size of the AI’s knowledge graph

2. Remember every SME answer: one-off answers that fall on the long-tail of frequency belong in the AI’s brain, not in an answer library users must maintain

3. Auto-sync sources daily: sources should always stay up to date (like daily sync on your Help Center content or company slide deck with latest positioning) without manual intervention.

4. Reduce human maintenance: the highest frequency responses should be maintained with high fidelity in a low impact knowledge base - we find that 90% accuracy is possible with around 200-400 Q&A pairs.

5. Cite every source and securely link: submitting a questionnaire or RFP with lots of attachments is neither secure nor small - AI should autogenerate links to source material so there’s never a black box, risk of hallucination, or extra work to hit submit.

The next generation of RFP response software starts with AI

Understanding the distinct purposes and requirements of Security Questionnaires and RFPs is crucial for effectively managing the process to respond to both in a quick and painless way. Generative AI is the perfect solution for understanding context and choosing the right sources when generating the perfect answer to any question asked, whether it is in an RFP or in a security questionnaire. With advances in LLMs, the way that legacy RFP software vendors have traditionally helped automate the RFP process just isn't "good enough" anymore.

What proposal and presales teams should look for when trying to identify the best vendor to use for automating their RFP response process and/or security questionnaire process is AI that can read from any source so they don't have to spend time constantly updating source information. They should also set criteria around how many precise (sales-ready and accurate) answers to an RFP or security questionnaire the AI can get right on the first pass. This should be at least 80-90% with some external sources, documents, and a few hundred question and answer pairs in a knowledge base (not thousands).

There are much easier ways to answer proposals today that go beyond maintaining a giant answer library. When evaluating potential vendors, keep an eye out for the newer AI software on the market that can handle both request for proposals and security questionnaire answering without compromising accuracy and time spent on maintenance.


Conveyor, the original security questionnaire automation software, uses AI that's so accurate, we turned it on for RFPs. Teams can use Conveyor to get instant, precise answers to both RFPs and security questionnaires with a low maintenance knowledge library since ConveyorAI can read from any source (external sites, documents, Q&A pairs, and past answers).

For more information on how ConveyorAI can transform your response process, visit Conveyor for RFPs.