TL;DR: Space startups need an AI policy before employees paste technical data into chatbots. A good policy lists approved tools, classifies data, bans controlled technical data in unapproved AI services, requires human review of outputs and assigns an owner. Build it on NIST's voluntary AI Risk Management Framework, check it with export counsel and keep it short enough to follow.

Key takeaways

• Under the ITAR, releasing technical data to a foreign person, even inside the U.S., is an export.
• Your AI policy should say which data can go into which tools, in plain language.
• NIST's AI Risk Management Framework and its Generative AI Profile give you a free, credible structure.
• Human review, logging and training matter as much as the rules.

This post is general information, not legal advice. Export control decisions belong with your empowered official or export counsel.

Why do space startups need an AI policy?

AI tools are now part of daily work: drafting proposals, summarizing papers, writing code and analyzing data. In most industries the main risks are confidentiality and accuracy. In space and defense, there is another: export controls.

The ITAR definition of export in 22 CFR 120.50 includes releasing or otherwise transferring technical data to a foreign person in the United States, called a deemed export. The Commerce Department's Bureau of Industry and Security describes the same concept under the EAR: a deemed export is the sharing or release of controlled technology or source code to a foreign person within the United States. If an AI service stores, processes or exposes your data in ways you do not control, you need to understand that before engineers use it.

Our ITAR-safe marketing guide covers the public-content side. This post covers internal AI use.

What does the ITAR say about storing data in the cloud?

The ITAR lists activities that are not exports in 22 CFR 120.54. One covers sending, taking or storing technical data that is unclassified, secured with end-to-end encryption that meets the standards described there, and not intentionally sent to or stored in certain proscribed countries. Whether a specific AI tool meets those conditions is a question for your export lead and the vendor's documentation. Do not assume it does.

What frameworks can you build on?

The National Institute of Standards and Technology published the AI Risk Management Framework on January 26, 2023, for voluntary use, to help organizations build trustworthiness into how they design, develop, use and evaluate AI. In July 2024, NIST added the Generative AI Profile (NIST AI 600-1), a companion resource focused on generative AI risks.

You do not need to implement either in full. Use them as a checklist so your policy covers governance, risk mapping, measurement and management, and so customers see you followed a recognized approach.

What should a space startup AI policy include?

Section	What to decide
Purpose and scope	Who the policy covers, including contractors
Owner	Who approves tools and answers questions
Approved tools	Which AI tools and account types are allowed, and for what
Data classes	Public, internal, confidential, customer, export-controlled, classified
Data rules	Which data classes can go into which tools
Human review	Who checks outputs before they are used or sent
Disclosure	When to tell customers AI was used, such as in proposals
Security	Accounts, access controls, logging and vendor review
Training	How staff learn the rules and where to ask
Incidents	What to do if controlled data goes into the wrong tool

A simple AI policy template

Adapt this outline with your export lead and counsel.

1. Purpose. We use AI tools to work faster while protecting customer data, export-controlled technical data and our IP.
2. Owner. The [role] approves AI tools and maintains this policy.
3. Approved tools. Only tools on the approved list may be used for company work, through company-managed accounts.
4. Data rules.
5. Public information: may be used in approved tools.
6. Internal and confidential information: only in tools approved for that class.
7. Customer information: only where the customer agreement allows it.
8. Export-controlled technical data (ITAR or EAR): never in an AI tool unless the export lead has approved that tool and configuration in writing.
9. Classified information: never.
10. Human review. A qualified person reviews AI output before it is used in engineering, proposals, customer communication or public content.
11. Accuracy. AI output can be wrong. Verify facts, figures, citations and code.
12. Disclosure. Follow customer and solicitation rules on AI use.
13. Incidents. If controlled or sensitive data may have gone into an unapproved tool, stop and report it to the owner and the export lead at once.
14. Training and review. All staff complete training on this policy, and the owner reviews it on a set schedule and when tools change.

How do you roll it out?

• Start with an inventory. Ask the team which AI tools they already use.
• Approve a small set that covers real needs, so people are not tempted to use personal accounts.
• Train with examples from your own work, like "Can I paste this test report into a chatbot?"
• Make it easy to ask. A named owner and a quick answer beat a long document.

Your AI policy also helps sales. If a defense or enterprise buyer asks how you use AI, a clear policy is an easy, credible answer. If security is part of your pitch, our Space Force ACES security clearance post shows how security readiness affects deals, and the WarpWare lessons post covers marketing AI products to engineers.

Want to compare AI policies with other space founders? Join Space Entrepreneurs, our free Skool community.

The space marketing guide shows where AI fits safely in your marketing. For the broader AI job map, see our guide to AI use cases for space companies.

Frequently asked questions

Does a startup need an AI policy?

If your team uses AI tools for work, yes. A short policy sets which tools are approved, what data can go into them and who reviews outputs. For space and defense startups, it also protects export-controlled data.

Can you put ITAR technical data into ChatGPT or other AI tools?

Not without approval from your export lead. Releasing technical data to a foreign person is an export under the ITAR, and storage exemptions in 22 CFR 120.54 have specific conditions. Treat controlled data as banned from AI tools unless a specific tool and setup has been approved in writing.

What is the NIST AI Risk Management Framework?

It is a voluntary framework NIST released on January 26, 2023, to help organizations manage AI risks and build trustworthy AI. NIST added a Generative AI Profile, NIST AI 600-1, in July 2024.

What should an AI acceptable use policy include?

Scope, an owner, approved tools, data classes and rules, human review, disclosure, security, training and an incident process.

Who should own the AI policy at a space startup?

A named leader, often the CTO or operations lead, working with the export compliance lead. Export questions should always go to your empowered official or export counsel.

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