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How Microsoft uses AI for RFP response management

By Tim Murphy

After extensive testing, Microsoft's proposal team implemented a generative AI tool to automate the first draft of RFP responses.

Proposal teams play an important role because they submit the request for proposal (RFP) responses that can win big deals. However, these teams face increasing complexity and volume of RFPs, so some have turned to AI for help. For instance, Microsoft uses AI-powered RFP response platform Responsive to streamline workflows and scale its operations globally. The tool's generative AI (GenAI) capabilities, which Microsoft tested in a sandbox, can create first drafts of complex proposals to save employees' time.

"If we can reduce that chunk of time where people are just plugging questions and answers in and doing a search one by one, then we can focus much more time on the strategy," said Carrie Jordan, global director of program execution and former global director of proposals at Microsoft.

Microsoft's RFP response challenge

Until 2020, Microsoft's sales teams were fully responsible for responding to RFPs and requests for information. Yet, this left sales reps with limited time to interact with customers and build their sales pipelines, Jordan said.

To resolve this problem, the company created a centralized proposal team. This team, which Jordan was part of and eventually led, has two main functions:

1. Its certified industry proposal experts offer direct support for Microsoft's most critical deals.
2. It implements repeatable processes and tools to help sales reps across the company complete proposals on their own.

As part of its mission to scale the company's RFP response processes, the team implemented Responsive in 2020 and went live with the tool's AI drafting feature in early 2025.

Automating RFP response with generative AI

Responsive's developers layered the tool's GenAI drafting feature over its core functionalities, which include a central repository for proposal knowledge and a project collaboration tool. The repository stores proposal information, which Microsoft's sales team uses to quickly answer RFP questions.

Thousands of sales reps across the company can search this library for proposal questions, response templates and field user guides, Jordan said. She estimated this repository, which her team curated with approximately 20,000 documents over a five-year period, saves the company $6 million per year in employee productivity.

Additionally, Responsive's project collaboration features let the team upload RFPs directly into the platform, assign questions to subject matter experts (SMEs), track progress, and conduct reviews for accuracy and compliance. This feature has enhanced Microsoft's RFP response processes, but it plans to implement Responsive's GenAI capabilities for more optimization.

Responsive's GenAI functionality can pull data from the tool's library and other sources, such as technical documentation within SharePoint sites, to generate a first draft of proposals. This lets sales reps and proposal managers fill out RFPs -- many of which contain hundreds of questions -- with a single click. Jordan expects the tool to reduce the time to first draft by 93%.

The proposal team tested the tool on sample RFPs based on enterprise commercial and public sector contexts, which yielded positive results. The team went live with the tool in January 2025 and plans to extend the capabilities to all Microsoft sellers in spring 2025.

Implementation challenges

Although the Responsive implementation went smoothly, Jordan's team faced the following obstacles that other proposal teams can expect:

• Internal governance delays. Microsoft's strict internal governance reviews delayed implementation a few weeks beyond the expected time frame. Reviews included checks for security, responsible AI, accessibility and code.
• Overreliance on automation. Users tend to become overreliant on first drafts and not check for accuracy, Jordan said. Proposal managers, sales reps and SMEs who fail to edit the automated responses eventually submit incorrect information, which can harm their organization's bottom line. To overcome this challenge, proposal leaders must create clear guidelines for human-in-the-loop reviews.
• Preservation of critical language. As GenAI tools paraphrase and summarize source data to generate responses, they can alter the wording of sensitive corporate and legal statements, which can cause legal challenges and reputational damage. Jordan's team partnered with Microsoft's legal group and Responsive's product group to tag questions that require word-for-word responses so the tool answers these questions verbatim, Jordan said.

Advice for proposal leaders

Despite a few implementation challenges, Jodan said Responsive's AI drafting tool saves time for the proposal team and sales reps. This efficiency has become critical for growing organizations, and GenAI can help them stay ahead of, or at least keep up with, competitors.

Jordan said proposal leaders should embrace AI and foster a culture of continuous improvement because teams that feel safe to experiment and learn from failure are more likely to innovate.

Proposal leaders who want to streamline their processes should take a proactive approach in AI implementation, as opposed to letting leadership do everything. This involvement is important because proposal teams live and breathe RFPs and understand day-to-day operations.

"If you don't tell your leadership how you plan to implement AI in your proposal shop, then they will tell you how to do it. And I personally would rather be driving that ship for my team," Jordan said.

Tim Murphy is associate site editor for TechTarget's Customer Experience and Content Management sites.