Executive Summary
A new pattern is emerging in enterprise AI adoption: Shadow AI. Employees, frustrated with slow-moving official systems, are turning to consumer-grade AI tools like ChatGPT to get work done. MIT’s State of AI in Business 2025 study reports that over 90% of knowledge workers now use unsanctioned AI for drafting, research, and analysis.
In many industries, this trend raises governance and security concerns. In nuclear, it introduces regulatory, safety, and compliance risks that cannot be tolerated.
This paper examines Shadow AI as an enterprise trend, analyzes why it is incompatible with nuclear operations, and outlines how regulator-ready, domain-specific AI addresses the gap.
1. Shadow AI: A Growing Trend
MIT’s research identifies Shadow AI as one of the fastest-growing dynamics in AI adoption:
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Broad worker adoption. Employees bypass enterprise systems and use consumer AI tools directly.
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Enterprise lag. Corporate IT and compliance groups struggle to deploy secure alternatives at the same pace.
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Risk exposure. Sensitive information is copied into cloud-based tools with little oversight.
In industries like retail or marketing, the risks are financial. In nuclear, they are regulatory and existential.
2. Why Nuclear Cannot Tolerate Shadow AI
Nuclear operations rely on strict compliance regimes that consumer AI tools cannot meet:
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Part 810 Regulations. Export control prohibits the uncontrolled transfer of nuclear technical data. Shadow AI platforms, typically hosted on global cloud infrastructure, are non-compliant by default.
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Licensing-Basis Sensitivity. Technical Specifications, FSARs, and design-basis documents cannot be exposed to uncontrolled platforms. Even summaries must be regulator-ready.
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Audit Requirements. NRC oversight requires every evaluation and document to be traceable and verifiable. Shadow AI outputs are not.
Simply put: Shadow AI creates compliance gaps that nuclear regulators and operators cannot accept.
3. Case Study: Licensing Research
Observed Behavior:
Frustrated by slow search systems, engineers tested consumer AI tools to summarize licensing requirements. The AI produced text that appeared helpful but lacked citations and omitted key references.
Outcome:
Outputs could not be defended in NRC-facing documentation. The practice created risk, not efficiency.
Domain-Specific Alternative:
Nuclearn’s Gamma 2 model retrieves licensing basis documents from secure, on-premise repositories. Outputs include full citations, reasoning steps, and maintain alignment with IV&V. Engineers remain in control, but repetitive search is automated.
Result: regulator-ready documentation, compliant with Part 810, without Shadow AI risk.
4. Shadow AI vs. Secure AI
The Shadow AI trend reflects a workforce reality: employees want faster, more usable tools. Restrictive policies alone will not stop Shadow AI. Without secure alternatives, adoption will continue underground.
The solution is not prohibition, but replacement. Nuclear operators must provide systems that are:
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As usable as consumer AI. Engineers will only adopt what improves their daily work.
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As secure as required. On-premise, Part 810 compliant, and regulator-ready.
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Domain-specific. Trained on nuclear acronyms, licensing structures, and workflows.
5. Implications for Nuclear Operators
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Shadow AI is not theoretical. It is already happening across industries. Nuclear cannot assume immunity.
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Regulatory exposure is immediate. Even one instance of sensitive data entered into a consumer AI platform may trigger compliance investigations.
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Workforce demand must be addressed. Engineers will seek usable AI. If utilities don’t provide compliant systems, Shadow AI will fill the gap.
Conclusion
Shadow AI is the new trend shaping enterprise AI adoption. In nuclear, it is untenable. The compliance, regulatory, and safety demands of the industry mean that consumer-grade AI tools cannot be tolerated inside the plant.
The solution is not banning AI use — it is providing secure, domain-specific alternatives that meet the same standard as the industry itself: safety, compliance, and reviewability.
Nuclearn demonstrates that when AI is designed for nuclear — Part 810 compliant, regulator-ready, and embedded in real workflows — it delivers measurable value while eliminating the risks of Shadow AI.