The explosive growth of AI and digital infrastructure is exposing a hard truth that many organizations are only beginning to confront: the power grid was not designed for what comes next. 

Across North America, hyperscalers, data center operators, and industrial developers are discovering that their biggest constraint is no longer land, silicon, or capital, it is time to power. Interconnection queues now stretch four, five, even ten years in some regions. Utility planning cycles move deliberately, while AI demand accelerates exponentially. The mismatch is structural, not temporary. 

For decades, the grid worked because demand grew predictably. Large loads could be planned, sequenced, and integrated over time. That assumption no longer holds. AI workloads introduce sudden, massive step changes in demand, often hundreds of megawatts at a single campus, with volatility profiles the grid was never engineered to absorb quickly. 

The result is not a shortage of energy in the abstract, but a shortage of deliverable, reliable power on modern timelines. 

This is the context in which Energy Parks are emerging. 

Energy Parks are often misunderstood as alternative power plants or niche workarounds. In reality, they are a pragmatic response to systemic grid constraints. When developers cannot wait years for interconnection, and when reliability requirements exceed what the grid can guarantee, organizations are forced to rethink the entire power delivery model. 

That rethink is often summarized as BYOP: Bring Your Own Power. 

Energy Parks enable large energy users to secure power on their own terms by developing campus-scale power ecosystems designed specifically for their load profile, reliability needs, and growth trajectory. In some cases, they operate independently of the grid. In others, they connect strategically, acting as flexible participants rather than passive consumers. 

Critically, Energy Parks are not about abandoning the grid. They are about working around structural timing and capability gaps that the grid cannot quickly close. 

This shift is not driven by hype. It is driven by arithmetic. When AI compute timelines are measured in quarters and grid builds are measured in years, waiting is no longer a viable strategy. The risk of delayed revenue, stranded compute assets, or underutilized capital quickly outweighs the perceived risk of developing dedicated energy infrastructure. 

For executive leaders, this is the real inflection point. The question is no longer whether Energy Parks are technically feasible. The question is whether organizations can afford not to consider them. 

Energy Parks are emerging because the grid was built for yesterday’s demand model. Tomorrow’s needs require something fundamentally different. 

And this is only the beginning of the Energy Park story. 

As Energy Parks gain traction as a response to grid constraints and accelerating AI-driven demand, a critical question remains: which power technologies can reliably support this new model at scale? 

One option increasingly discussed is next-generation nuclear. In our on-demand webinar “SMR to scale AI: Meeting the energy demands of tomorrow”, experts from Schneider Electric, Microsoft, Terra Praxis, and 92 Capital explore how Small Modular Reactors (SMRs) could play a role in delivering stable, carbon-free baseload power where traditional grids fall short, covering technology, financing, and electricity offtake considerations. 
 
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