Using AI in Government Contracting

Bringing AI Into Your B2G Workflow: Practical Guidance and Key Considerations

AI is becoming part of everyday business operations, whether planned for or not. Organizations of all sizes are testing for writing, research, planning inputs, and a wide range of routine tasks. But adopting AI responsibly means understanding what it can and cannot do, especially when your work involves public-sector customers. That is where a practical, grounded approach becomes essential.

For businesses already trying to do more with limited time and resources, AI can help accelerate market research and early-stage proposal work and organize information more efficiently. It can also help you analyze whether an opportunity aligns with your capabilities and assess gaps and strengths, but it cannot make the bid or no-bid decision for your business.  Only you can weigh factors like risk, capacity, customer relationships, and long-term strategy.

Like any tool, it is important to set clear boundaries and have a realistic understanding of AI’s limits.

Where AI Helps Most in B2G
AI excels at tasks that involve pattern recognition, summarizing, organizing, and structuring information. It can quickly:

• Build a list of keywords to aid in market research and marketing
• Suggest potential target agencies based on your capabilities
• Support light agency research using publicly available information (missions, procurement portals, common buying patterns)
• Draft preliminary capability statements and past performance summaries (be intentional about what materials you’re willing to risk making public)
• Build outlines, compliance checklists, and first-pass proposal checklists
• Flag potentially overlooked requirements when you’re assessing an opportunity (go/no-go decisions)
• Identify keywords and recurring themes in a solicitation (for mirroring the solicitation)
• Review human-written drafts for clarity and consistency
• Build a draft response for a solicitation (but only if you feed it the right structure)

When used effectively, AI can help build a draft response by organizing the solicitation into its key pieces (requirements, scope, timelines, deliverables, submission rules, formatting, and evaluation criteria) and then working through each part individually. Once the bid is broken down and reviewed, going section-by-section will generally yield better results. It can also provide insights about tone, length, and what the response must cover. Some AI applications are better than others, and depending on your AI of choice, you may need to use a paid version that can retain information across prompts to build more consistent drafts. The quality of the draft depends entirely on the clarity of the inputs (role, objective, context, input material, constraints & rules, & output formatting).

Steps for Generating a Draft Proposal with AI

1. Review the Solicitation in its Entirety (You):
   Read the solicitation yourself first. AI cannot replace this step.
2. Generate a First Draft (AI):
   With that understanding in place, upload the publicly posted solicitation and give the AI clear instructions including key components and going section-by-section then let it produce an initial draft. Treat it as a starting point.
3. Review the Draft (You):
   Compare the AI’s output to the solicitation. Identify missing requirements, vague language, or inaccuracies.
4. Revise with Targeted Instructions (You → AI):
   Give the AI specific, actionable edits such as expand a section, align with evaluation criteria, clarify an approach, etc.
5. Produce the Final Draft (You):
   Humans must complete the final version, ensuring accuracy, compliance, and alignment with the agency’s expectations.

Where AI Should Not Be Used
AI is powerful, but not compliant by default. Public facing AI systems should never receive:

• Federal Contract Information (FCI), Controlled Unclassified Information (CUI), or any classified information
• Proprietary pricing, cost/volume build-ups, or subcontractor quotes
• Unreleased or source-selection-sensitive proposal content
• Sensitive internal documents such as employee data, company financials, internal policies, or system security plans (SSPs)
• Personally identifiable information (PII) such as employee resumes, background data, or client contact lists
• Requests to perform regulatory or contractual interpretation (FAR, DFARS, CMMC, flowdowns, etc.)
• Requests to generate compliance documents, cybersecurity policies, certifications, or assertions of qualification

As a rule, if the information is not publicly available, it shouldn’t be entered into a public AI system.

AI is also not a substitute for understanding federal regulations, agency nuance, or technical expertise. Technical content will always require expert human validation. AI cannot interpret FAR clauses, guide compliance, or replace customer relationships and capture strategy. It also cannot produce a submission-ready proposal. AI-generated text is often generic, incomplete, or missing required details.

How to Use AI Safely and Effectively
The best approach is to treat AI like a junior analyst: great at gathering and organizing information, helpful with early drafts, but always in need of human review and refinement. The quality of the output generated by AI depends heavily on the input, so clear instructions and good examples matter. And no matter how strong the draft, a human expert must verify accuracy, compliance, and alignment with both the agency’s mission and the company’s capabilities and capacity.

Used responsibly, AI can be a real accelerator for resource-restricted organizations, but it should not be viewed as an autopilot.

Mark Johnson
Government Contracting Advisor
Washington APEX Accelerator at Economic Alliance Snohomish County

This article was co-developed with AI as a drafting tool, following the same practical and responsible approach recommended in the content.