New alliance aims to fast-track AI data centre development
AI workloads are exploding, but delivery of new capacity is stuck behind slow site selection, strained utility capacity, and scarce hardware. A new alliance between hi-tequity and Site Selection Group (SSG) is built to compress that timeline by running the critical paths in parallel from day one.
The promise: a single, coordinated program that handles site selection, utility negotiations, incentive capture, and procurement of GPUs and electrical gear as one track-reducing handoffs, delays, and uncertainty.
The bottleneck today
Most projects still run in a linear sequence-find site, request power, hunt for incentives, then place long-lead orders-while AI demand can't wait. Suitable sites with real grid headroom are scarce. Interconnection queues are long. Lead times for high-density infrastructure and compute are unpredictable.
Teams end up juggling many vendors across disciplines that should be tightly linked. Each month lost is expensive-missed model launches, deferred product features, and idle engineering capacity.
What changes with a single program
The hi-tequity + SSG model integrates site diligence, utility strategy, incentives, and equipment procurement from project kickoff. Instead of serial tasks, these run together with one owner and one schedule. The goal is to cut calendar time without adding risk.
"We're creating a force multiplier for our clients. The traditional approach requires juggling multiple vendors, each working in silos. By integrating Site Selection Group's expertise with our equipment procurement from day one, we're collapsing timelines and eliminating costly delays when every month matters," said Ryne Friedman, Associate, hi-tequity.
Utilities and incentives as a core strategy
Access to real power-where and when you need it-is the gating factor for AI and HPC builds. SSG brings long-standing utility and economic development relationships, originally built in call center site selection and expanded as data centres scaled. That network can surface viable sites and incentives before they're widely known.
"We've been working with colocation operators, data center developers, utilities, and economic development groups for 15 years, building relationships that originated with our call center work and evolved as the data center market exploded. Combined with hi-tequity's ability to secure critical equipment in a constrained supply environment, we're delivering what the industry desperately needs: speed, certainty, and strategic advantage," said Michael Rareshide, Partner, Data Centre Practise, Site Selection Group.
Single-source delivery and accountability
Developers get one accountable team from site assessment through electrification and hardware installation. The alliance emphasizes early alignment with electrical capacity and network needs, so designs match what the grid can actually support. That's vital for high-density AI clusters and liquid cooling adoption.
What this means for IT and development leaders
- Set capacity targets tied to model and product roadmaps; work back from grid timelines and realistic GPU delivery windows.
- Treat power as the first-class constraint. Pre-qualify sites by interconnection feasibility, not just acreage and fiber.
- Run procurement, incentives, and utility workstreams in parallel. Long-lead equipment and GPUs are a P0 item.
- Design for density and cooling early (air-to-liquid transition plans, heat reuse options, and rack-level limits).
- Consider phased builds (pod-based, modular electrical rooms) to ship value earlier while the rest scales up.
- Negotiate incentives with performance milestones that align to staged energization and hardware arrival.
- Bake in SRE/SOC controls and compliance from the start-retrofits erase any schedule gains you make.
Projects in motion and expected timelines
hi-tequity and SSG are already executing multiple AI data centre projects across North America, with more in planning. Under this integrated model, the alliance says some projects can finish in as little as a quarter of the time required by traditional methods, depending on site conditions, interconnection, and permitting.
Useful context
Energy availability is the make-or-break factor for AI capacity. For context on data centre energy impact and growth, see the IEA's briefing on data centres and networks here.
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