Hezelburcht Grant & Funding Consultancy’s Post

Data centres are the new factories. The question isn't whether we build them. The question is what they're built on, what powers them, and what they leave behind. I've written before about the enormous opportunity AI presents, but also about the unprecedented demand it places on electricity systems. Recent proposals in Scotland have brought that debate into sharp focus. Concerns have been raised over whether some large AI developments can realistically deliver on their renewable energy ambitions, while local communities question the impacts on landscapes and infrastructure. This isn't an argument against AI. Nor is it an argument against data centres. It's an argument for systems thinking. Every hyperscale data centre creates demand for three things: ⚡ Electricity. 💧 Water. 🌿 Land. For decades, we've treated these as separate conversations. They're not. Electricity production increasingly depends on resilient landscapes. Healthy catchments support hydropower, cool thermal assets, reduce wildfire risk and help secure water for energy generation. At the same time, restoring nature can make electricity infrastructure itself more resilient. The irony is that AI may become one of the world's largest consumers of electricity just as we need every kilowatt of clean energy to decarbonise transport, industry and heating. This isn't simply an energy transition. It's an infrastructure transition. The winners won't be those who build the biggest data centres. They'll be those who integrate renewable generation, storage, flexibility, water stewardship and natural capital into a single system. Because nature isn't competing with AI. It's providing the resilience that AI—and the electricity system it depends on—will increasingly need. Perhaps the next generation of data centres shouldn't just aim to be net zero. They should aim to be net positive—enhancing biodiversity, restoring catchments, improving water security and strengthening the landscapes that sustain both communities and the grid. The AI revolution will undoubtedly consume electricity at scales we've rarely seen before. The real challenge is ensuring it also helps regenerate the natural infrastructure that makes that future possible. #AI #DataCentres #NaturalCapital #EnergyTransition #NatureBasedSolutions #Electricity #ClimateResilience #Infrastructure #Biodiversity #RenewableEnergy

AI data centers are digesting data around the clock. Voraciously. Continuously. At a scale that is reshaping electricity grids from America to Australia. US utilities are committing approximately $1.4 trillion in capital investment through 2030, up 27% from last year's $1.1 trillion projection, largely in response to AI data center demand pulling load that existing grid capacity cannot absorb. (Source: PowerLines / Fortune, April 2026) The EIA projects US residential electricity prices will rise a further 5.1% in 2026. (Source: EIA / Tech-Insider, April 2026) The grid is being rebuilt around a demand surge it did not anticipate. We have been digesting around the clock for years. Our Flexibuster does not run on data. It runs on organic waste. The output is not a query result or a model inference. It is electricity, heat, biofertilizer, and verified carbon credits. Generated continuously, at the exact facility where the waste is produced. AI created a significant share of the energy demand problem currently stressing grids globally. On-site anaerobic digestion is part of the infrastructure built to absorb it. While data centers pull from the grid, our systems generate behind the meter. Two technologies working through the night. One is intensifying grid pressure. The other is built to relieve it. Which side of that equation is your operation on right now? Drop a comment below. #AI #AnaerobicDigestion #WasteToEnergy #EnergyTransition #SEaBEnergy

Every single AI prompt uses up to 10x more electricity than a traditional search engine query. By 2030, the data centers powering these networks could demand double their current energy output, placing massive strain on global infrastructure. But there is a twist. AI is also the most powerful tool we have to optimize clean energy grids, predict renewable outputs, and eliminate industrial waste. What do you think: Is AI the biggest threat to our energy grid, or the ultimate solution to climate change? Drop your thoughts below. 👇 NileAGI #AI #EnergyTransition #EnergyAccess #Gridinfrastructure

AI data centres are digesting data around the clock. Voraciously. Continuously. US utilities are planning approximately $1.4 trillion in capital investment through 2030, up 27% from last year's $1.1 trillion projection, largely in response to AI data centre demand pulling load that existing grid capacity cannot absorb. (Source: PowerLines / Fortune, April 2026) The EIA projects US residential electricity prices will rise a further 5.1% in 2026. (Source: EIA / Tech-Insider, April 2026) The grid is being rebuilt around a demand surge it did not anticipate. We have been digesting around the clock for years. Our Flexibuster does not run on data. It runs on organic waste. The output is not a query result. It is electricity, heat, biofertiliser, and verified carbon credits, generated continuously at the exact facility where the waste is produced. AI created a significant share of the energy demand problem currently stressing grids globally. On-site anaerobic digestion is part of the infrastructure being built to absorb it. While data centres pull from the grid, our systems generate behind the meter. Two technologies that never sleep. One is intensifying grid pressure. The other is built to relieve it. Which side of that equation is your operation on right now? 📩 Link in first comment. #AI #AnaerobicDigestion #WasteToEnergy #EnergyTransition #SEaBEnergy

The same AI demand that can strain the grid can also strengthen it in two ways: By serving as a buffer during peak demand with behind-the-meter production, and by providing the scale that makes clean energy solutions cheaper. https://lnkd.in/ezbxrdc7

One of the biggest barriers to clean energy adoption isn't technology. It's complexity. ⚡ In this episode of Lead with AI, Dr. Tamara Nall speaks with Joe Glass, Founder of Microgrid Me, about the challenge that inspired the company. Designing a solar and battery system often requires → Hours of research → Technical knowledge → Specialized knowledge & → Significant time investment. For many people, that complexity becomes a barrier to action. After spending more than 20 hours researching and designing his own power system, Joe realized there had to be a better way. Microgrid Me uses its AI to help users design customized solar and battery systems in a fraction of the time traditionally required. This reflects a larger shift happening across industries: AI isn't just automating work. It's making expertise accessible. And when expertise becomes accessible, more people can participate. What other industries are still relying on unnecessary complexity where AI could unlock broader adoption? 🎧 Listen to the full conversation on Lead with AI. Watch Now: https://lnkd.in/ejXfPAQa #LeadWithAI #AI #MicrogridMe #CleanEnergy #RenewableEnergy #SolarPower #EnergyTech #ClimateTech #Innovation #FutureOfEnergy #Sustainability #TechForGood

It's not how much electricity exists that limits AI. It's whether that electricity shows up exactly when and where AI needs it. Right now, the limiting factor is still chips. Litowitz et al. (2026) show US AI systems running at a fraction of available power, around 125 tokens per person a day against a ceiling near 44,500. But push the timeline to 2028 and that answer flips, with projected power allocation capable of supporting 225,000 tokens per person a day. At that point, the question stops being how many chips you own and becomes whether the grid can sustain them. Prices, however, have already started to move. Electricity's share of AI firms' costs has already doubled since 2019, and developers keep chasing the frontier whether the power behind it is clean or not. An "adaptation trap" is slowly developing, one that makes fossil use key even as renewables scale. Credit to everyone behind this work: Alec Litowitz, Nick Polson, Vadim Sokolov, Christian Bogmans, Patricia Gómez-González, Ganchimeg Ganpurev, Giovanni Melina, andrea pescatori, Sneha T., Luyi Gui, Tinglong Dai, Mohammad Hemmati, Gbemi Oluleye PhD FHEA, Vassilis Charitopoulos, Eshta Bhardwaj, Rohan Alexander, Christoph Becker #AIinfrastructure #EnergyPolicy #AIecosystem #EUTech

The AI revolution won't be powered by algorithms alone—it will be powered by clean electricity. Artificial Intelligence is transforming industries at an unprecedented pace. But behind every AI model, every data centre, and every intelligent application lies one fundamental requirement: 'Electricity' As AI adoption accelerates, global electricity demand from data centres is expected to rise significantly over the coming years. This presents both a challenge and an opportunity for the energy sector. The conversation is no longer just about generating more power—it's about generating sustainable, reliable, and resilient power. The future of AI and the future of clean energy are becoming increasingly interconnected. The real question is not whether AI will reshape our world—it already is. The question is: Can we build the clean energy infrastructure quickly enough to power this transformation sustainably? The next decade will not simply be defined by advances in artificial intelligence. It will be defined by our ability to develop renewable energy systems, resilient grids, and responsible infrastructure that can support an increasingly electrified and digital world. 'The energy transition is no longer just about decarbonization—it is becoming the foundation of the AI economy.' #ArtificialIntelligence #EnergyTransition #RenewableEnergy #Sustainability #CleanEnergy #SolarEnergy #BatteryStorage #GridModernization #ClimateAction #ESG #Infrastructure #Energy #NetZero #Biodiversity #ClimateResilience

The Silent Crisis Nobody is Talking About: Industrial Water vs AI Data Centres... Here's a thought that has been bothering me lately. Everyone is debating whether AI will consume too much electricity. Very few are asking a more fundamental question: Where will all the water come from ? The AI revolution is quietly creating a new competition for one of our most precious resources — not just between people and agriculture, but between industries themselves. Consider this: • A large AI data centre can consume up to 2 million litres of water per day for cooling — equivalent to the daily water needs of thousands of households. • Semiconductor fabrication, the backbone of AI hardware, is even more water-intensive. A modern chip fabrication facility may require around 10 million gallons (≈38 million litres) of ultrapure water every day and producing 1,000 litres of ultrapure water itself requires roughly 1,500 litres of municipal water. Now add another rapidly growing sector — green hydrogen. Producing 1 kg of hydrogen theoretically requires about 9 litres of water, while practical industrial systems typically consume 15–20 litres after purification and process losses. The real issue, therefore, isn't whether AI or green hydrogen is "good" or "bad." The real challenge is resource convergence. By 2035, AI data centres, semiconductor fabs, hydrogen plants, battery gigafactories and advanced manufacturing facilities may increasingly compete for the same freshwater resources, particularly in water-stressed regions. Perhaps it's time we stop evaluating industries solely by their carbon footprint. The next strategic metric may well be the Water Footprint per Unit of Economic Value Created. The countries that lead the next industrial revolution may not be those with the cheapest electricity — but those that master water recycling, zero-liquid-discharge systems, closed-loop cooling and industrial water circularity. In the coming decade, water could become the new strategic infrastructure — just as electricity was in the last century.... #ArtificialIntelligence #DataCenters #WaterSecurity #Sustainability #Semiconductors #GreenHydrogen #IndustrialWater #CircularEconomy #ClimateTech #ResourceEfficiency #AdvancedManufacturing #FutureOfIndustry

AI and data centers are transforming the global economy, but their rapid growth is creating a new infrastructure challenge: they require enormous and continuous supplies of electricity and water. In many regions, power grids are already under pressure, renewable generation is not yet sufficient to meet round-the-clock demand, and freshwater resources are increasingly shared between communities, agriculture and industry. Without new solutions, the expansion of digital infrastructure could lead to higher energy costs, greater water stress, delayed projects and growing public opposition. This is why the next generation of AI infrastructure must be supported by more than faster chips—it needs new, reliable and sustainable sources of power and water. Our project is being developed around this opportunity: to create integrated infrastructure that expands essential resources instead of competing for those already under strain. By connecting clean energy, sustainable water production and resource recovery, we aim to support the growth of AI and data centers while protecting the communities and environments around them. The future of AI will not be defined only by computing power, but by how responsibly we build the systems that keep it running. Siam Eternal Energy Co.,Ltd. - Our Solution Is Your Future. #AI #datacenter #energy #renewableenergy #greenenergy #cleanenergy #alternativeenergy