AI for GovCon Compliance

The 'Can I put this into AI?' decision framework

Every piece of data your team considers putting into an AI tool should pass through this decision tree. Print this out. Post it next to every BD and proposal team member's desk.

Step 1: Is the data publicly available?

If the data is from a public source — a SAM.gov posting, an FPDS query, a publicly posted agency forecast, an unclassified solicitation posted on contract opportunities — it is safe for commercial AI tools. These documents are publicly available to anyone with internet access. There is no data sensitivity concern.

Step 2: Is the data company-internal, non-controlled?

Your own capabilities statement, your past performance descriptions (the ones you write, not the government's CPARS records), your proposal templates, your capture plan frameworks, your win theme libraries — these are your proprietary data. You can process them with AI tools, but you should use enterprise-tier AI services with appropriate data retention and privacy policies, not free consumer-tier tools that may use your data for training.

Step 3: Is the data CUI (Controlled Unclassified Information)?

Check the document for CUI markings (banner markings, portion markings, or designation indicators). If the data is CUI, it must be processed in an environment that meets NIST SP 800-171 requirements. Most commercial AI tools in their standard configurations do not meet this standard. Microsoft Azure OpenAI Service with Government Cloud (GCC High) configuration and certain other FedRAMP High authorised AI services may be acceptable — but this must be verified by your security team against your specific CUI handling plan.

Step 4: Is the data ITAR-controlled?

If the data includes technical data related to defence articles or services on the United States Munitions List, ITAR restrictions apply. ITAR-controlled data generally cannot be processed by cloud-based AI tools unless the tool is hosted in a US-person-only, ITAR-compliant environment. This is a hard constraint that few commercial AI tools currently satisfy.

Step 5: Is the data classified?

Classified data (Confidential, Secret, Top Secret) cannot be processed by any commercial AI tool. Period. If you work in classified environments, AI assistance is limited to classified-environment-approved tools, which are a separate and evolving category.

Step 6: Does your contract have specific data handling restrictions?

Some contracts include clauses that restrict how contract-related data can be processed or shared, beyond standard CUI/ITAR requirements. Check your contract's data rights, security, and information handling clauses.

FAR/DFARS clause analysis

Every government contract incorporates FAR and DFARS clauses — sometimes dozens of them. These clauses impose specific compliance requirements: reporting obligations, security requirements, insurance minimums, subcontracting plan requirements, cost accounting standards, and more. On a new contract, your contracts officer needs to read every incorporated clause, identify the compliance requirements, and ensure your systems and processes meet them.

This is exactly the kind of systematic, document-heavy work AI handles well. Feed AI the list of incorporated FAR/DFARS clauses from your contract (Section I) and ask it to produce a compliance requirements summary.

Analyse the following FAR/DFARS clauses incorporated into this
government contract.

CONTRACT CLAUSES (from Section I):
[List all incorporated clauses by number and title]

For each clause, provide:
1. Clause number and title
2. Summary of compliance requirements (what the contractor must do)
3. Reporting obligations (what must be reported, to whom, when)
4. System requirements (what systems or processes must be in place)
5. Flowdown requirements (which clauses must be flowed to
   subcontractors)
6. Key deadlines or trigger events
7. Risk level (High/Medium/Low based on consequences of
   non-compliance)

After analysing all clauses, produce:
- A compliance checklist organised by category (reporting, security,
  cost accounting, subcontracting, data rights, etc.)
- Clauses that require immediate action (system certifications,
  initial reports, plan submissions)
- Clauses with ongoing compliance requirements (periodic reporting,
  continuous monitoring)

Your contracts officer reviews the output, adds context about your current compliance posture for each requirement, and produces a compliance management plan. What would take days of cross-referencing the FAR and DFARS to produce manually takes hours with AI assistance.

DCAA audit readiness

If you are a government contractor with cost-reimbursable contracts or if you expect DCAA to audit your incurred costs, your cost accounting system, timekeeping practices, and billing procedures need to withstand scrutiny. DCAA auditors are thorough, and findings can result in questioned costs, billing system disapprovals, and contract payment suspensions.

AI supports DCAA audit preparation in several ways:

Policy and procedure review: Feed AI your timekeeping policy, cost accounting practices, and billing procedures. Ask it to compare them against DCAA audit standards (DCAM — Defense Contract Audit Manual) and flag areas where your documented procedures may not meet expectations. AI identifies gaps — for example, a timekeeping policy that does not explicitly address correction procedures, or a cost accounting disclosure statement that does not align with CAS 401-418 requirements.

Documentation organisation: DCAA audits require specific documentation: timesheets, cost accounting records, indirect rate calculations, billing records, and supporting documentation. AI can help organise and index this documentation, creating an audit-ready package that maps each document to the specific audit area it supports.

Self-assessment questionnaires: Before a DCAA audit, AI can generate a self-assessment based on common DCAA findings at companies of your size and contract mix. This is not a substitute for your accountants and contracts staff — but it ensures you have considered the areas where DCAA most frequently identifies issues.

The goal is not to use AI to pass an audit you should fail. The goal is to ensure your documentation is complete, your procedures are clearly articulated, and your team is prepared for the auditor's questions before they arrive.

Small business subcontracting plan monitoring

Any government contract over $750,000 (for non-construction) or $1.5 million (for construction) that is not set aside for small business requires a subcontracting plan. This plan commits you to specific goals for subcontracting to small businesses, small disadvantaged businesses, women-owned small businesses, HUBZone small businesses, veteran-owned small businesses, and service-disabled veteran-owned small businesses.

These are not aspirational goals — they are contractual commitments. The government tracks compliance through the Electronic Subcontracting Reporting System (eSRS), and failure to meet your subcontracting goals can result in liquidated damages, negative CPARS comments, and diminished competitiveness on future proposals.

AI helps monitor and manage subcontracting compliance:

Goal tracking: AI maintains a running comparison of your actual subcontracting against your plan goals, broken down by small business category. Instead of discovering at year-end that you are 15% below your SDVOSB goal, AI flags the shortfall in real-time.

Report generation: Individual Subcontracting Reports (ISRs) and Summary Subcontracting Reports (SSRs) are due semi-annually through eSRS. AI generates draft reports from your procurement and accounting data, ensuring the numbers are consistent and properly categorised.

Compliance risk identification: If your procurement patterns are trending away from your subcontracting goals, AI identifies which categories are at risk and which upcoming procurements could be directed to small business subcontractors to close the gap.

Organisational conflicts of interest screening

Organisational Conflicts of Interest (OCI) under FAR 9.5 can disqualify you from a procurement before you ever submit a proposal. OCI arises when your existing work gives you an unfair competitive advantage (unequal access to information), when you would be evaluating or advising on your own products or services (biased ground rules), or when your objectivity in performing advisory work would be impaired.

OCI screening should happen at the earliest stage of opportunity identification — before you invest capture resources in a pursuit that you may be legally barred from winning. Most contractors do some level of OCI screening, but it is often informal and happens too late.

AI can systematise OCI screening by cross-referencing a new opportunity against your current contracts:

Screen the following opportunity for potential Organisational
Conflicts of Interest.

NEW OPPORTUNITY:
[Paste opportunity description — agency, scope of work, any OCI
clauses in the solicitation]

OUR CURRENT CONTRACTS:
[List current contracts with: agency, scope of work summary,
advisory/evaluation roles, access to non-public information]

Analyse for three types of OCI:
1. Unequal access to information: Does any current contract give us
   access to non-public information relevant to this opportunity?
2. Biased ground rules: Did we help develop the requirements, SOW,
   or evaluation criteria for this procurement?
3. Impaired objectivity: Would winning this contract put us in a
   position to evaluate or advise on work performed by our own
   company or affiliates?

For each potential OCI identified:
- Describe the specific conflict
- Assess severity (potential disqualification vs. mitigatable)
- Suggest mitigation strategies (firewalls, recusals, disclosures)
- Flag whether this should be disclosed to the Contracting Officer

AI does not make the legal determination on OCI — that requires your contracts counsel. But it identifies potential issues early, so you can seek legal guidance before investing in capture rather than discovering the conflict during proposal review.

FedRAMP considerations for AI tool selection

FedRAMP (Federal Risk and Authorization Management Program) provides a standardised approach to security assessment for cloud services used by federal agencies. For government contractors, FedRAMP authorisation of an AI tool is relevant when you need to process government data that requires a certain level of protection.

FedRAMP has three impact levels:

• Low: suitable for data where loss of confidentiality, integrity, or availability would have a limited adverse effect
• Moderate: suitable for data where loss would have a serious adverse effect — this covers most CUI
• High: suitable for data where loss would have a severe or catastrophic adverse effect — required for the most sensitive unclassified government data

For most mid-size contractors, the practical question is: "Which AI tools are FedRAMP authorised, and at what level?"

As of early 2026, the landscape is evolving rapidly. Microsoft Azure OpenAI Service is available in Azure Government (FedRAMP High) and GCC High environments. Amazon Bedrock is available in AWS GovCloud (FedRAMP High). Google Cloud has FedRAMP authorised environments, with Vertex AI increasingly available. Anthropic's Claude is available through AWS GovCloud via Amazon Bedrock.

What FedRAMP authorisation means for your AI workflow:

• You can process CUI through a FedRAMP Moderate or High authorised AI service (subject to your specific CUI handling plan)
• The AI service meets federal security assessment standards for data protection, access control, audit logging, and incident response
• You have a defensible compliance position if questioned about your data handling practices

What FedRAMP authorisation does not mean:

• It does not automatically authorise processing of all data types (ITAR, classified, and specific contract restrictions still apply)
• It does not mean the AI output is certified or authorised by the government
• It does not replace your obligation to manage data access and retention policies

For your initial AI adoption, the practical path is: use commercial AI freely on public and company-internal data, evaluate FedRAMP-authorised AI services for CUI, and maintain a hard boundary around ITAR and classified data until purpose-built solutions are available and approved.