Where does AI help most in capture and proposals?
AI is most useful where people spend hours reading or reformatting. It is least useful where the work depends on customer knowledge, judgment, or pricing.
| Task | AI role | Person's role |
|---|---|---|
| Opportunity screening | Summarize notices, score fit with reasons | Qualify decision |
| Requirement extraction | Pull candidate requirements into a matrix | Verify every row against the source |
| First drafts | Draft from approved past performance and boilerplate | Tailor to the customer and requirement |
| Resumes and past performance | Reformat to the solicitation's template | Confirm facts and dates |
| Review | Check drafts against the compliance matrix | Final compliance and quality sign-off |
Why does AI need an approved content library?
AI drafts are only as reliable as their sources. A library of approved past performance, resumes, and service language lets the AI draft from facts instead of inventing them.
- Each item has a source, an owner, and a last-reviewed date
- Approved content is separated from old drafts
- Drafts mark anything that needs new input rather than filling the gap
What are the risks of using AI on proposals?
The main risks are invented facts, missed requirements, and sending sensitive information to tools that have not been approved. Each one needs a specific control, not general caution.
- Invented claims: every fact traces back to approved content
- Missed requirements: a person verifies the compliance matrix
- Data handling: define which documents may be processed and by which tools
- Solicitation rules: check whether the solicitation restricts or requires disclosure of AI use
Where should a small contractor start?
Start with one repeatable task that eats time every week, usually opportunity screening or requirement extraction. Measure the hours saved and the corrections needed before expanding.