AI is transforming enterprise workflows, from proposal writing to content analysis to decision support. But as highlighted in Fergal McGovern’s LinkedIn article, Subcontractors: Your AI Tools Could Be a Ticking Time Bomb, there’s a growing gap between adopting AI and using it safely. In industries where primes, subcontractors, and government customers work closely together, that gap can quickly become a risk.
A new wave of AI-related legal terms is now being pushed down from prime contractors to subcontractors. These are terms that directly restrict where prime-owned data can go and what systems are allowed to touch it.
This summary captures key insights from the article, offering practical guidance for leaders on how to navigate people, process, and automation challenges to adopt AI securely and confidently.
Why Do People and Roles Matter so Much When Deploying AI in Complex Organizations?
AI doesn’t remove responsibility, it shifts it. Many subcontractors receive AI tools along with heavy contractual obligations, yet no one clearly defines who owns the outputs, who reviews the results, or who monitors quality.
When roles aren’t clear, it doesn’t matter how good the technology is. Confusion spreads, accountability gets fuzzy, and the “AI advantage” can quickly turn into a risk.
For subcontractors, this matters even more. If a team member puts prime data into an unapproved tool, the organization, not the tool vendor, is on the hook.
How Should Processes Evolve to Support AI and Automation Effectively?
A lot of organizations are still running processes built long before AI came into the picture. That creates friction, especially now that primes are flowing down strict AI-related terms to subcontractors.
To stay compliant and avoid accidental misuse, teams need to revisit how proposal content, RFP data, and internal drafts move through the organization. Processes should have:
- Clear review steps
- Defined escalation paths
- Guardrails that prevent AI tools from bypassing compliance
In regulated spaces, words matter. Documentation, requirements, and contract language must stay tightly aligned; otherwise, automation simply amplifies the inconsistencies.
What Hidden Risks Appear When Subcontractors Use AI Tools Managed by External Vendors?
This is where the new legal clauses hit hardest.
If a subcontractor runs prime data through a third-party AI tool, there’s a real risk of breaking AI-use clauses. Even with “zero data retention” promises, the data still passes through a third party. That means the subcontractor may be out of compliance the moment the request is sent.
If downstream partners don’t fully understand how their AI tools handle data, the risks multiply:
- Data leakage
- Unclear model behavior
- No audit visibility
- Legal exposure
- Misaligned incentives across the value chain
The reality is simple: if a subcontractor can’t explain exactly where the data goes, how it’s used, and whether it’s ever stored, then the AI solution becomes a liability instead of a productivity boost.
How Can Enterprises Get the Benefits of AI and Automation Without Losing Human Judgment or Oversight?
AI can take on repeatable, time-consuming work but it can’t replace human context or decision-making. Teams still need people who understand the data, the customer, and the business impact.
And when working with CUI (Controlled, Unclassified Information), ITAR (International Traffic in Arms Regulations), or other sensitive information, the environment matters. AI tools must run in an isolated, controlled setup, one where the organization can say with confidence that data never leaves their environment.
Automation should expand human capability, not sidestep human oversight. The organizations that get this right focus on blending smart automation with strong governance and clear human checkpoints.
What Practical Steps Should Leaders Take to Make Their AI Strategy Safe, Sustainable, and Competitive?
Here are the moves that make the biggest difference:
- Map the Value Chain: Understand where AI is used internally and across every subcontractor and partner.
- Assign Clear Ownership: Decide who monitors outputs, who handles exceptions, and who signs off on compliance.
- Modernize your Processes: Update workflows around documentation, review, and approvals so they anticipate AI, not react to it.
- Keep Humans in the Loop: Critical decisions should never move to fully automated paths.
- Use Isolated Environments for Sensitive Data: Self-hosted or private cloud deployments are the safest options for regulated work.
- Communicate Clearly and Consistently: The clearer the language, the fewer the misunderstandings, internally and across partners.
Organizations that build this foundation don’t just stay compliant. They deliver faster, respond with more confidence, and stand out in competitive captures.
Conclusion
The real question isn’t whether teams can keep using AI. The real question is:
“What’s our plan to use AI in a way that’s compliant, secure, and ultimately an advantage?”
Teams that can walk into a meeting and say, “Our AI tools run in our own isolated environment, and your data never leaves our control” offer something primes value above all else: peace of mind.
To explore the full conversation behind these insights, check out the full article on LinkedIn.
