\u00a0<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\nAs hyperscalers and others invest to meet AI\u2019s growing data capacity appetite, it\u2019s vitally important that they also bring more standardization and modularity to data center design and construction.\u00a0<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\nUltimately, the architectural aesthetics with these projects are secondary to efficiency, security, safety and repeatability. This means that unless a particular project has unique environmental, siting or regulatory requirements, heavily customized designs are unnecessary, even frivolous.<\/span><\/span><\/span><\/span><\/span><\/span>\u00a0<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\nFor general building design, the occupant experience almost always comes first. But for data centers, while the safety and comfort of those who work onsite should be a high priority, so, too, is creating an optimal environment for server racks and their contents.\u00a0<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\nAs much as stakeholders might feel inclined to treat a data center like most other buildings, with customizations and unique design elements to make the building more appealing and the occupant experience richer, those considerations take a back seat to standardization, predictability, modularity, repeatability and sustainability.<\/span><\/span><\/span><\/span><\/span><\/span>\u00a0<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\nIn fact, data centers may be more repeatable than most other types of building projects. Many of their critical components \u2014 power density, cooling strategies, security zones, structural loads and commissioning requirements \u2014 tend to follow predictable patterns. Once these patterns are identified \u2014 with the help of artificial intelligence, of course \u2014 they can be used to inform design and construction strategies from the start.<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\nThat, in turn, creates an opportunity to develop a repeatable blueprint or formula that data center developers can readily apply to future projects.\u00a0<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\nExcessive customization<\/span><\/span><\/span><\/span><\/span><\/span> leads to <\/span><\/span><\/span><\/span><\/span><\/span>longer timelines, higher and less predictable costs, quality inconsistencies and elevated risk. Modularization, on the other hand, allows projects to be designed, approved, built and commissioned faster, at a more predictable and often lower cost, with fewer surprises along the way.<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\nHere are the specific advantages modularization brings:<\/span><\/span><\/span><\/span><\/span><\/span>\u00a0<\/span><\/span><\/span><\/span><\/span><\/span>\u00a0<\/span><\/span><\/strong><\/span><\/span><\/span><\/p>\nSpeed<\/span><\/span><\/strong><\/span><\/span><\/span>: Modularization and standardization can significantly speed up projects without compromising quality. The ability to develop one megawatt modules, for example, with standardized HVAC configurations, materials and labor requirements can enable developers to scale different components and then assemble the project as a whole. AI tools can help design and configure the modules themselves.<\/span><\/span><\/span><\/span><\/span><\/span>\u00a0<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\nOff-site fabrication of modules, as well as continuous commissioning within a project, where stakeholders can identify and address issues as they arise, offer additional time savings.<\/span><\/span><\/span><\/span><\/span><\/span>\u00a0<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\nBetter cost control, if not cost reduction: <\/span><\/span><\/strong><\/span><\/span><\/span>Modularization brings greater project cost certainty and likely cost reductions, due to fewer customizations and economies in procurement.<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n