How proposal teams can use AI to win smarter

Artificial intelligence (AI) is increasingly essential for government contractors aiming to streamline business development (BD) and proposal workflows. But its value isn’t confined to a single function. AI can support a range of roles across the entire proposal lifecycle each with distinct responsibilities and perspectives. From capture managers and BD leads to proposal writers and subject matter experts, AI helps make the entire process more efficient and effective. 

Let’s explore how different roles in the proposal lifecycle can use AI tools in their daily work. We’ll also share sample prompts to help proposal professionals get the most from their AI platforms. 

Business development and account managers: Opportunity identification and qualification 

BD and account managers are responsible for identifying and qualifying opportunities. Their ability to align customer needs with organizational strengths sets the foundation for a strong proposal. 

How AI helps 
AI tools that use data analytics and natural language processing (NLP) can assist with market trend analysis, opportunity evaluation, and identifying decision-makers in target agencies. By parsing large datasets, AI helps highlight opportunities most likely to align with your firm’s capabilities and past performance. 

• Opportunity qualification: Analyze historical data, client feedback, and federal spending patterns to assess win probability, enabling teams to focus on high-value pursuits. 

• Client analysis: Uncover client priorities and concerns so teams can tailor outreach and positioning. 

Example use case 
A BD manager uses AI to analyze a new RFP and compare it against previous wins. The tool identifies a strong match in cybersecurity experience, marking it as a high-probability opportunity. 

Capture managers: strategic planning and competitive analysis 

Capture managers shape win strategies, lead capture planning, and build competitive messaging. They need a deep understanding of both the client and the competitive landscape. 

How AI helps 
AI can accelerate competitive research and support development of win themes by quickly surfacing insights from past contracts, competitor performance, and client feedback. 

• Win theme development: Compare internal strengths to competitor weaknesses to build messaging that resonates. 

• SWOT analysis: Automate internal and external SWOT analyses to inform capture strategy. 

Example use case 
A capture manager leverages AI to review recent competitor contract outcomes. Based on the findings, the tool recommends a theme focused on cost-effective delivery. That was a key differentiator in past evaluations. 

Proposal managers and writers: drafting and compliance 

Proposal managers and writers ensure that proposals are compliant, persuasive, and on schedule. With tight timelines and complex requirements, AI can be a powerful partner. 

How AI helps 
AI tools can generate initial drafts, build compliance matrices, and review documents against RFP requirements. This frees up proposal teams to focus on refining content. 

• Proposal drafting: Use past submissions and RFP inputs to generate first drafts quickly. 

• Compliance checks: Flag missing or incomplete responses by comparing the draft with solicitation requirements. 

Example use case 
A proposal manager uploads an RFP into an AI platform. The tool creates a compliance matrix and drafts an executive summary using relevant project history and client goals. 

Subject matter experts: content creation and review 

SMEs provide the technical depth required for strong responses. But with competing demands on their time, proposal writing often falls low on the priority list. 

How AI helps 
AI tools support SMEs by drafting technical content and sourcing relevant information from prior projects. 

• Drafting technical content: Use previous submissions to create first drafts, allowing SMEs to focus on reviewing and fine-tuning. 

• Knowledge retention: Pull data from earlier proposals to ensure continuity and accuracy in responses. 

Example use case 
An SME uses AI to create a first draft of a technical response for a cybersecurity opportunity. The draft pulls from previous projects, and the SME refines it for accuracy and detail. 

Solution architects: designing methodologies and approaches 

Solution architects are responsible for the technical strategy in a proposal. They must align capabilities with client requirements. 

How AI helps 
AI tools can recommend methodologies and validate technical approaches based on previous success. 

• Methodology suggestions: Identify approaches aligned with successful outcomes in similar projects. 

• Performance analysis: Review past performance data to tailor strategies to client objectives. 

Example use case 
A solution architect analyzing a cloud migration RFP uses AI to suggest an approach emphasizing scalability and cybersecurity, two key concerns for the requesting agency. 

Sample prompts for proposal teams 

Here are a few AI prompt examples to streamline your proposal process: 

• For proposal drafting: “Generate an executive summary for a Department of Homeland Security RFP highlighting our IT modernization capabilities and federal track record.” 

• For compliance matrix creation: “Create a compliance matrix for this RFP and flag any areas needing clarification or additional content.” 

• For competitive analysis: “Develop a SWOT analysis of competitors based on recent cybersecurity contract awards.” 

• For win theme suggestions: “Recommend win themes based on our performance in cloud services and the client’s focus on cost efficiency and scalability.” 

AI has the potential to boost efficiency across every role in the proposal lifecycle. By automating routine tasks and uncovering valuable insights, AI frees your team to focus on what matters most—crafting high-impact proposals that win business. 

To learn more about how Unanet ProposalAI can help your team members work faster, smarter, and more effectively, connect with a Unanet expert today.