Operators use biomimicry, community co-design, and brownfield redevelopment to reduce the visual impact of data centers and improve local acceptance.
Beauty may be in the eye of the beholder, but it’s unlikely that the recent rash of data centers popping up across the US and globally is winning many people over on looks alone. To ease community concerns about noise, energy, and water use – and especially their visual impact – some operators are rethinking how facilities look, how they sit within landscapes, and even where they’re built.
Anti-data center sentiment often goes beyond complaints about water, energy, and noise pollution to include criticism of a facility’s appearance and its aesthetic impact on nearby neighborhoods. A description from the Virginia-based Piedmont Environmental Council captures a common view: “The data center developments proposed in the County are hyperscale facilities, which are massive, windowless concrete buildings that can bring potential noise and electrical infrastructure such as substations and transmission lines. They are also often out of scale with existing communities and fenced with cameras, security guards, and guard gates.”
Some operators are taking steps to make facilities a bit easier on the eyes. One approach is to use landscaping to soften profiles and blend sites into their surroundings. Microsoft, for example, has begun applying “biomimicry” – borrowing strategies from local ecosystems to guide land, water, and restoration plans – to improve how some of its newest data centers look and function.
Recursive self-improvement is touted as AI’s next major milestone. If it’s ever achieved, the impact will be felt across the data center industry and far beyond.
Recursive self-improvement (RSI) describes AI systems that can design, code, and deploy their successors with minimal human input. If achieved, improvements could compound rapidly as smarter models beget even smarter generations – potentially accelerating beyond human comprehension and, worryingly, control. For data center operators, RSI would reverberate across power, cooling, orchestration, governance, and certification.
Although RSI is loosely defined, much like artificial general intelligence (AGI), there are signs it’s edging closer to reality. Achieving RSI depends on fast advances in AI-assisted coding, which labs say are already underway. For example, frontier AI model creator Anthropic, in its report titled “When AI Builds Itself,” says its Claude model now authors a substantial proportion of its own codebase: “As of May 2026, more than 80% of the code we merge into Anthropic’s codebase was authored by Claude. Before Claude Code launched in research preview in February 2025, this number was in the low single digits.” If sustained, this kind of contribution is a step toward systems that can improve themselves.
Sustainability’s legacy was sidelined by AI growth and politics, but public scrutiny and hard economics are forcing a course correction.
Data centers are where compute turns into real electrical load, heat, and water demand, and where efficiency and resilience are engineered under grid, thermal, and permitting constraints.
For operators, power, cooling, water stewardship, air quality, and building performance aren’t background considerations but instead define the operating envelope. At the megawatt scale, every kilowatt and liter translates into cost, risk, and compliance. Because data centers are the physical manifestation of the cloud – sited in communities and tied to local grids and water systems – they carry a clearer and more enforceable environmental mandate than the software stack they host. That visibility has brought sharper regulatory oversight and pressure from environmental groups over the years.
Incoming UK Prime Minister Andy Burnham appears to favor homegrown AI, but planning disputes and data center moratoriums could cause early friction.
Incoming UK Prime Minister Andy Burnham has established an informal dress code that owes more to US West Coast tech execs than the blue-suited standard issue of British politics.
Whether his Silicon-Valley-casual-style – including a black T-shirt reminiscent of Steve Jobs’ trademark black turtleneck – extends to his technology policies has yet to be determined.
Burnham, who has previously held cabinet positions including Secretary of State for Health, most recently served as Mayor of Greater Manchester before standing as a member of Parliament to challenge outgoing UK PM Sir Keir Starmer. He will replace Starmer as leader of the Labour Party this week before being appointed UK prime minister on July 20.
Troughs usually precede inspiring slopes and productive plateaus
Troughs can be good for some
Words matter. But so does context.
Terms like ‘trough of disillusionment” from Gartner’s (in)famous Hype Cycle appear to have obvious negative implications.
Being in any kind of trough can’t be a good thing right? (farmyard animals and drunken cowboys from 1950s films and TV aside)
But a little bit of analysis, or simply engaging with the detail, reveals a more nuanced story. And let’s face it, amid all of the current hype around Gen AI, a little bit of nuance should be welcome.
As Gartner’s prognosticator in chief, or to give him his correct title Distinguished VP analyst, chief of research, John Lovelock explained it this week:
“For AI we are in the trough of disillusionment this year,” he said speaking on a webcast to explain Gartner’s latest quarterly IT spending predictions. “The lowest point for expectations. But let’s be careful to remember that expectation is the vertical axis of the hype cycle. It is not what the technology can do, it is what the users of the technology expect it to do and right now it is at a low point.”
Gartner Gen AI Hype Cycle
So what Lovelock is explaining is that not that Gen AI is inherently bad or not delivering but rather that customers have adjusted their expectations based on their experience of AI to date. As Lovelock explains: “Even though we are in the trough of disillusionment we are seeing overall AI spending continue to grow. It will hit $4.7 trillion by 2029.”
“It is not what the technology can do, it is what the users of the technology expect it to do and right now it is at a low point.”
Gartner’s John Lovelock explaining how to interpret the Hype Cycle
$4.7 trillion by 2029! That is not a small number. (for context, Gartner predicts that worldwide IT spending is expected to reach $6.31 trillion in 2026, up 13.5% from 2025).
AI being in the trough, needs to be understood in the broader context of the Hype Cycle. Following the trough, there is fortunately a slope, then a plateau. Everyone loves a plateau – especially a plateau of productivity.
But while Gartner was positive about the future promise of AI, there are some well documented challenges ahead when it comes to the small matter of return on investment (ROI). Lovelock went on to discuss the thorny issue of how hyperscalers will recoup the hundreds of billions invested into new data center capex over the recent past which is expected to continue into the near future at least.
Not even including the data center physical infrastructure (power, cooling, building shell etc), there is a significant gap between projected future revenues from selling AI services versus the investment in AI IT infrastructure.
Gartner AI ROI Gap
“We notice there is a tremendously large gap,” said Lovelock. “If these hyperscalers are to meet the return on investment of 25% for just the servers and networking equipment they are going to need about $1.5 trillion dollars in revenue.”
“If they stuck to their current revenue models they would be in trouble,”
John Lovelock, Gartner
However, again, the nuance matters. Lovelock explained that if the hyperscalers were approaching AI in the same way as say cloud, they could be facing a write down on some of the capital investment by 2029, 2030. “If they stuck to their current revenue models they would be in trouble,” he said.
But most hyperscalers appear to be diversifying their revenue streams, using AI servers to buy interests in new AI start-ups for example. The take-away message from Lovelock is that the dynamic and fluid nature of AI investments, adoption and monetization make simplification a dangerous game. “The market is tremendously complicated. Looking at it through a simplified lens could lead you to a simple outcome that is not likely to happen”.
So there you have it. Words matter. And being in a trough is not necessarily bad if there is a beautiful plateau in your future too.
The full webcast is available here. There is also some good analysis of the impact of AI on jobs which is also worth chewing over.
The adage, ‘hope for the best, plan for the worst’, is particularly apt for the data center industry right now.
Investment in new data center infrastructure is often based on an optimistic take of future technology demand but operators are also aggressively pragmatic when it comes to preventing downtime.
No matter what the cause – faulty equipment, cybercriminals or grid-level power outages – investment in resilient infrastructure combined with rigorous operating practices should ensure the lights stay on or, at worst, only go off for the minimum amount of time.
Unfortunately, as recently released research Post Pandemic Data Centers from Uptime Institute Intelligencepoints out, many operators were largely blindsided by Covid-19.
While there appear to have been relatively few (public) examples of Covid-19 related downtime over the last few months, the pandemic has put additional pressure on everything from data center design and construction to supply chains and staffing.
Iceotope is a UK-based company I have been tracking since it first emerged in 2009, and then disappeared, before resurfacing in 2012 backed by Peter Hopton (of VeryPC fame). I had been aware of the concept of cooling datacenters with liquid rather than air – the technology dates back to the mainframe era – but it has largely remained a niche technology only found in high performance computing and supercomputing systems. It’s fair to say that Iceotope probably did more than other companies to turn me on to the idea that this could be a disruptive technology in enterprise datacenters too (although there are a lot of reasons why it might not do). So it was good to see this week that others have bought into its approach – to the tune of $10m – including datacenter giant Schneider Electric. I will be following up with Iceotope later this week and am also working on a Long Format Report for 451 Research on the 15 plus companies developing direct liquid cooling technology.
I spoke with European datacenter start-up Eco4Cloud a couple of weeks back and the report based on that conversation has just been published (for 451 subscribers) on 451 Research.com. Eco4Cloud (E4C) is a spinoff from the Institute for High Performance Computing and Networking (ICAR) of Italy’s National Research Council (CNR) and the University of Calabria. The company has developed software designed to deal with virtual machine (VM) sprawl and low server-utilization rates. E4C’s software effectively automates the real-time consolidation of VMs onto the minimum number of physical servers. The remaining servers, with a low number of VMs or none at all, can be power-managed dynamically based on workload variations, or even retired. E4C has received early stage funding from two external investors, and is looking to attract new investment and partners in 2014.
I took part in this webcast with TSO Logic in December 2013. The webcast looked at the importance of IT energy efficiency to lowering datacenter operating and capital costs. 451 Research gave an overview of some of the main themes and trends in this area before TSO Logic gave a detailed account of how its software can be used to identify and eliminate under-utilised servers, and power manage IT equipment.
Datacenter modularity is one of the hot-topics for us at 451 Research’s Datacenter Technologies team. I have just completed a couple of reports back to back on what HP and Dell offer in this area. There are certain similarities but also big differences. Dell is going down a mainly services route while HP sees containerized datacenters as a natural extension of the server, rack and row.
However some critics have written off containers as a dead-end technology. We think that containers are selling, and will continue to do so for the immediate future but prefabricated IT, power and cooling modules (similar to Dell’s offering or HP’s Butterfly product) are more likely replacements for traditional bricks and mortar builds.
Check out these two reports for more (451 Research subscribers only I am afraid)
451 Research report: Dell eschews containers in favor of modular datacenter services
Dell’s competitors sell a range of modular datacenter products, such as Hewlett-Packard’s Performance Optimized Datacenter and IBM’s Portable Modular Data Center. However, Dell’s Modular Data Center group (part of Dell Data Center Solutions, or DCS) prefers to provide products and services with an emphasis on customization and best fit for the customer.(MORE)
451 Research report: HP talks up Performance Optimized Datacenters, but should it be chasing the Butterfly?
Hewlett-Packard recently asserted some ambitious potential market-size data for its container-based Performance Optimized Datacenters (PODs). The supplier believes PODs could be a relevant option for up to 45% of new total capital expenditure on datacenters over the next few years (up to $13bn in 2012). (MORE)
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