How AI Is Enabling Data Center Operators To Mitigate Risks, Track Progress And Build Faster

In Western Europe, a major data center builder recently faced a challenge that has become all too common in this booming industry. The firm was eager to get a new center up and running to meet skyrocketing demand — it already had a design and timetable in place — but it was unable to provide a concrete delivery date due to sliding schedule activities. 

As with many data center projects, several contractors from different trades were working in parallel, and disparate field data made it impossible to have a clear understanding of the project’s progress. This not only made it difficult to pin down a completion date but also impacted budgeting. 

Eventually, however, the data center builder was able to get actionable insight into exactly what was happening with its development, thanks to a little help from artificial intelligence. 

Slate Technology’s platform was designed to support better project outcomes for developments like this one, said Slate Vice President of Product and Customer Strategy Garrett Jones. 

The platform is designed to optimize core pain points across the project lifecycle, leveraging advanced analytics, real-time data capture and AI to boost productivity and deliver insights. It starts with design automation, enabling developers and builders to explore potential design outcomes, rapidly iterate with stakeholders, and then produce deliverables that can immediately be pushed to market for bids, proposal responses, procurement and more. 

“Slate supports progress-tracking in the field, enabling field workers to review progress in real time and stream that data back to a project management and controls center through our platform, allowing anyone guiding the project to make informed decisions about work sequencing to maintain key milestones for on-time delivery,” Jones said. 

It also highlights risks to schedules, the causes behind them, and potential mitigation strategies based on project context. 

All of this is supported by Slate’s proprietary AI, which digests all the disparate data involved in a project — from schedules to request for proposals to field diaries and beyond — assesses it for issues, and develops problem mitigation strategies. 

“Our platform enables work to be done better, faster,” Jones said. “AI is enabled to ensure the outcome is optimized for quick delivery. We feel it's important now, given where the market is, to empower teams to leverage AI — not to replace them but to supercharge their capabilities.”

Jones said the platform’s capabilities are particularly important for the data center industry, which is experiencing continuing staggering demand and needs to build new facilities faster than ever.

For data center operators, the ability to optimize design through automation and multiple stakeholder inputs allows them to get ahead of designs quickly and bring them to market faster. Expediting design through automation helps them stay on top of the ever-changing technology used to power and cool data centers and drive market-leading efficiencies, improving key metrics like power usage effectiveness while also allowing for flexibility to plan for future expansion. The platform also allows operators to get ahead of procurement, something that is particularly important for data centers. 

“Everyone's fighting for the same materials right now,” Jones said. “Long lead items are becoming exacerbated across the industry as we look at competition for not only the chips, but the steel, the concrete, the ductwork, all the guts that support this industry.”

He said that as the data center industry works overtime to meet the demand, Slate is working to “eliminate the noise.” It is more important than ever for operators to know their workforce is focused on issues critical to project delivery, not reacting to risks that should have been identified and eliminated before construction started. 

For the project in Europe, Slate’s progress teaching tool allowed the team to monitor what was happening across a multitrade, multidiscipline data center in real time by enabling workers to capture their work and immediately send it to a centralized system for all stakeholders to view. The platform analyzed and linked 80 building information models and more than 6,700 schedule activities to allow field users to track the progress of their specific scope against their own detailed schedule, Jones said. 

“We enabled this client to manage their telecom, mechanical, electrical and plumbing systems, some of the most complex components of a data center, and track their progress and production in real time to make sure they understood where their pitfalls occurred,” he said. 

In the end, Jones said, the client avoided what would have been a 20% overage on their budget. 

Among the many things that set Slate apart from other AI tools is the level of clarity and detail it is able to generate because it is the company’s own bespoke model, he said. Additionally, few companies focus on supporting the various workflows that constitute a project, especially on projects as complex as data centers. 

“The data is remarkable,” Jones said. “You get insights down to exact nail and screw sizes, not just the type of general, high-level risk overview you can get from other systems.” 

The ultimate goal, Jones said, is to create what Slate calls the “single source of truth” for a project. 

“The coalescence of data and the ability to understand all the key parameters in one fell swoop is a make-or-break for most major capital expense projects like data centers,” he said. “By centralizing everything across all the disparate platforms, we can drive better outcomes.” 

This article was produced in collaboration between Slate Technology and Studio B. Bisnow news staff was not involved in the production of this content.

Studio B is Bisnow’s in-house content and design studio. To learn more about how Studio B can help your team, reach out to studio@bisnow.com.