December 3-4, 2025 | Vienna International Centre
We attended the IAEA's AI & Nuclear Energy Symposium in Vienna.
Although the event focused on energy infrastructure, the insights apply directly to organisations navigating nuclear-AI co-location. Hyperscalers, nuclear operators, data center developers, and infrastructure investors alike.
What we observed confirmed a fundamental shift. AI is now core infrastructure, not a feature.
Every major organisation represented treated AI as essential to competitiveness and resilience. Operators, regulators, researchers.
If your organisation thinks of AI as an enhancement rather than the foundation of your next infrastructure deployment, you may fall behind faster than expected.
Five Core Insights from Vienna
1/ Trust, auditability and safety are becoming the main differentiators
A strong theme throughout the symposium was the priority placed on trustworthy AI. Explainability, traceability, governance and human oversight dominated every discussion.Organisations that cannot demonstrate these capabilities will struggle in regulated markets. Nuclear, energy, critical infrastructure.
Strategic implication: Differentiation should not rely on raw model sophistication alone. It should be the reliability and safety envelope built around AI-enabled infrastructure.
2/ High-quality data and disciplined data governance are non-negotiable
Every nuclear AI example ultimately came back to data integrity. Without structured data pipelines, lineage, and curated training sets, organisations simply cannot deploy advanced AI with confidence.
The challenge: If you want to compete in an AI-first infrastructure market, improving your data foundations is not optional. It is a prerequisite for any credible AI strategy.
3/ Human-AI teaming is the dominant operating model
Despite the hype around full automation, the realistic vision presented was human-AI collaboration. AI handles orchestration, triage and drafting. People supervise, validate and refine.
Design implication: Infrastructure projects will increasingly adopt workflows where AI provides analysis and recommendations while teams provide expertise, oversight and quality assurance.This applies to site selection, regulatory approval, commissioning, and operations alike.
4/ Compute and energy realities will reshape infrastructure planning
A point that surfaced repeatedly is that AI workloads carry heavy and rising compute costs. LLMs, agentic systems, Digital Twins. All require substantial energy resources.
Strategic implication: Nuclear-AI co-location is not just an opportunity. It may become necessary. Organisations need a more deliberate approach to efficiency, optimisation and deployment.This is why our atlas platform focuses on behind-the-meter economics and grid interconnection intelligence.
5/ Standards, governance and cross-sector cooperation will shape market winners
The symposium highlighted that common frameworks and international alignment are already forming. The organisations that engage early in governance, interoperability, monitoring and safe-use standards will gain trust and access faster.
Recommendation: Don't wait for regulation. Lead with responsible, documented, verifiable AI practices now.
Beyond Insights: Strategic execution patterns
We observed three strategic patterns from the symposium that are already reshaping how leading organisations execute nuclear-AI infrastructure projects.These patterns apply to hyperscalers deploying 500 MW+ data centers, nuclear operators exploring co-location revenue, developers navigating regulatory pathways, and investors assessing opportunities.
We discuss these strategic patterns during consultations to help organisations assess their relevance to specific projects and business contexts.
Apply these Insights to your Organisation
Interested in exploring how these patterns apply to your nuclear-AI infrastructure project?
We discuss:
We'll share the three strategic patterns we validated in Vienna and help you assess their relevance to your situation.
Contact us at [email protected]
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