Sustainability-in-Tech : 600% Data-Centre Electricity Increase In a Decade

In a speech shared on LinkedIn, National Grid Chief Executive, John Pettigrew, highlighted how demand for electricity from commercial data centres will increase six-fold, within just ten years.

Double The Demand On The Grid By 2050 

Comparing today’s problem of grid network constraint to that of the 1950s, Mr Pettigrew identified the key challenges of demand on the grid growing dramatically, and forecast to double by 2050 as heat, transport and industry continue to electrify.

Why The Dramatic Increase In Data Centre Power Demand? 

Mr Pettigrew put the dramatic predicted six-fold commercial data centre power demand down to factors like the future growth in foundational technologies like AI and quantum computing requiring larger scale, energy-intensive computing infrastructure.

Innovative Thinking Required 

Mr Pettigrew also highlighted how the UK’s high voltage ‘supergrid’ of overhead pylons and cables that powered the UK’s industries and economy over decades is now 70 years old. As such, faced with the challenge of needing to “create a transmission network for tomorrow’s future” Mr Pettigrew suggested that we are at a “pivotal moment” that “requires innovative thinking and bold actions.”

Possible Solutions 

One possible solution, highlighted in Mr Pettigrew’s speech, for creating a grid that can meet future demands is the construction of an ultra-high voltage onshore transmission network of up to 800 thousand volts. It’s thought that this could be “superimposed on the existing supergrid” to create a “super-supergrid” which could enable bulk power transfers around the country. One key advantage of this approach could be using strategically located ultra-high capacity substations which can support the connection of large energy sources to big demand centres, including data centres, via the new network.


It has long been known that data centres are power-hungry and require enormous amounts of water (for cooling), as well as needing to find sustainable solutions for using the excess heat productively. Factors such as the growth in cloud computing and the IoT, as well as the huge power demands of AI, have been identified as key factors driving the growing need for energy by data centres. Recent ideas for how to provide cooling for data centres have included immersion cooling / submerging servers in liquid and even having them submerged under the sea as underwater data centres. Ideas for producing enough power have included building dedicated small nuclear power stations / Small Modular Reactors (SMRs) adjoining each data centre. Ideas for how to best use the excess heat include heating nearby homes and businesses and even growing algae which can then be used to power other data centres and create bioproducts.

What Does This Mean For Your Organisation? 

The growth in cloud computing, the IoT, and now AI, have all meant an increase in the demand for more power. All of this comes at a time when there is a need to decarbonise and move towards greener and more sustainable energy sources. This rapidly increasing demand, coupled with the constraints of an ageing, creaking grid (as highlighted in the recent speech by John Pettigrew), means that there is now an urgent need for innovative ideas and the action to match if the UK’s businesses are to be served with the power they need to fuel the tech-driven future.

The ideas, however, must be ones that not only meet the demand for power from UK businesses and data centres, but do so in a sustainable way that meets decarbonising targets. As highlighted by Mr Pettigrew, creating a “super-supergrid” is an idea currently on the table, but a boost in wind, wave, solar, nuclear, and other power sources, as well as more carbon offsetting by data centre owners, and many other cooling and excess data centre heat distribution ideas will likely all contribute to these targets in the coming years. Also, although running AI models is a major power drain, ironically, AI may also help to provide solutions for how to manage the country’s energy requirements more efficiently and efficiently.

Sustainability-in-Tech : Data-Centres Using One-Third Of Ireland’s Electricity By 2026

A report from the International Energy Agency (IEA) forecasts that almost one-third of electricity demand in Ireland is expected to come from data-centres by 2026.

Doubling Of Electricity Demand 

The IEA’s ‘Electricity 2024 – Analysis and forecast to 2026’ highlights how having one of the lowest corporate tax rates in the EU (12.5 per cent) is a key reason why Ireland now has 82 data-centres. However, the fact that data-centres require enormous amounts of energy has meant that, even back in 2022, electricity demand from data-centres in Ireland represented a massive 17 per cent of the country’s total electricity consumption.

The expansion of the data-centre sector, driven by factors like AI, cryptocurrencies, demand for more compute capacity and their associated elevated electricity demand has led to the IEA’s forecast that the electricity demand in Ireland from data-centres will double to 32 per cent of the country’s total electricity demand by next year!


As may be expected with a doubling of demand, the report warns that the reliability and stability of Ireland’s electricity system will be challenged.

Safeguarding Measures 

The IEA reports that in order to safeguard Ireland’s electricity system, in 2021 the country’s Commission for Regulation of Utilities had published requirements applicable to new and ongoing data-centre grid connection applications. These included looking at whether a data-centre is within a constrained region of the electricity system, and the ability of the data-centre to bring onsite dispatchable generation and/or storage equivalent, at least, to their demand. The requirements also included looking at the ability of the data-centre to provide flexibility in their demand by reducing it when requested by a system operator.

This highlights the need by local governments in Ireland to only grant connections to operators who can make efficient usage of the grid and incorporate renewable energy sources with a view that incorporates decarbonisation targets.


Looking at the global data-centre sector, there are more than 8000 data-centres, with about one-third of these in the US, 16 per cent in Europe and around 10 per cent in China. The 1,240 datacentres in Europe (mostly in Frankfurt, London, Amsterdam, Paris, and Dublin) consume 4 per cent of the EU’s total electricity demand. The IEA forecasts that with increasing demand, electricity consumption in the data-centre sector in the EU will reach almost 150 TWh by 2026.

What Can Be Done To Moderate Data-Centre Electricity Demand? 

Measures that could be taken to moderate the IEA’s projected surge in the amount of energy data-centres consume could include:

– Introducing more energy-efficient data-centre cooling mechanisms, e.g. direct-to-chip water cooling systems and liquid cooling systems.

– Data-centres sourcing their power from renewable sources like solar, wind, and hydro. For example, the IEA report highlights a global trend toward clean electricity sources, with renewables set to cover a substantial part of the additional electricity demand.

– Data-Centres participating in demand response programs to adjust their power consumption during peak periods, helping to balance the grid.

– Integrating data-centres more closely with the energy grid to optimise power distribution and reduce waste.

– Governments encouraging or mandating the use of renewable energy and energy-efficient technologies in data-centres through incentives, subsidies, or regulations that set minimum energy efficiency standards.

– Investment in energy storage and grid infrastructure to ensure reliability and the integration of intermittent renewable energy sources.

– Ongoing research into more energy-efficient computing technologies, like advanced chip designs or quantum computing, can reduce the energy footprint of data-centres over time.

Needed, And Part Of The Solution 

It should be remembered, however, that data-centre services are now critical to the daily functioning of the business, consumer, and economic landscape because they add value, and they are enabling the growth of new technologies like AI. It could therefore be argued that more data-centres and the value and compute power they bring could deliver key solutions to solve the energy and climate challenges. In doing so, they could also find ways to generate more energy than they consume, thereby reducing their demand on the grid, and becoming part of the solution to their own problems.

What Does This Mean For Your Organisation? 

Factors like the growth of cloud computing, which has helped businesses, the demand for compute capacity, the growth of AI and cryptocurrency, are all contributors to a rapidly growing demand for more electricity and threats to current supply systems (such as Ireland’s).

That said, as shown above, safeguarding and mitigating measures can (and must) be taken. Also, multiple data-centres being sited in countries like Ireland can be a boost to their economy and their standing within the tech-world. Although an electricity demand surge in the growing data-centre sector is inevitable now, technologies such as AI (which increases energy demand from data-centres) may help find intelligent ways to mitigate the extra demand issues it creates and it would be difficult to argue that the world doesn’t need more data-centres to drive forward vital technologies for business and economies.

Nevertheless, there is a need for sustainable action. For example, using cleaner energy and governments working together with industry, combining their technologies and innovations could be the way forward to supporting the energy, economic, and technological outlook.

Sustainability-in-Tech : London Data Centres To Heat New Homes

A new £36 million UK government project is to use data centre waste heat to provide heating and hot water to 10,000 new homes and 250,000 square metres of commercial space in London.

Using Heat From Data Centres 

Data centres in our digital society and cloud-based business world now play a crucial role in supporting countless industries, businesses and services. However, the increasing demands upon them mean that getting enough power across to them plus finding ways to provide effective cooling and dealing with the surplus heat generated are two major challenges.

The new project, therefore, will provide a way to re-distribute some of the surplus heat so that it benefits the community, advances sustainability, and supports London’s efforts to reach net zero city by 2030.

Heat Network 

The £36 million funding award will support the commercialisation and construction of a district heat network scheme that is expected to deliver 95GWh of heat across 5 phases between 2026 and 2040.

The Old Oak Development 

The new, major urban brownfield regeneration project has been named ‘The Old Oak Development’ because it includes the Old Oak HS2 and Elizabeth Line interchange areas and will be operated by the Old Oak and Park Royal Development Corporation in the London boroughs of Hammersmith and Fulham, Brent, and Ealing. The Old Oak Development, which covers three London Boroughs, and a brownfield development, and which will create 22,000 new jobs, has been enabled thanks to a wider £65m award from the government’s Green Heat Network Fund (GHNF) to five projects across the UK.

Data Centre Heat Delivered Via Plastic Ambient Network 

The scheme will involve harnessing/recycling the surplus heat from two (as yet unnamed) data centres within the Old Oak/Park Royal area. The data centres will supply ‘low grade’ waste heat (i.e. between 20°C [68°F] and 35°C [95°F] ) via a plastic “ambient” network. The network will supply heat pumps that raise the temperature to Low Temperature Hot Water “LTHW” which will be piped via a traditional steel network to a mixture of new and existing residential buildings.

David Lunts, OPDC’s Chief Executive said of the scheme: “Recycling the massive amounts of wasted heat from our local data centres into heat and energy for local residents, a major hospital and other users is an exciting and innovative example of OPDC’s support for the mayor’s net zero ambitions. 

We are excited to be leading the way in developing low carbon infrastructure, supporting current and future generations of Londoners in Old Oak and Park Royal to live more sustainably.” 

Jo Streeten, Managing Director, Buildings + Places – Europe and India, AECOM re-iterated the importance and benefits of the project, saying: “This is a fantastic opportunity for the new communities emerging within the OPDC area to lead the way in how our cities can operate more sustainably, by using the waste heat sourced from data centres.”  

Previous Data Centre Controversy 

This positive news for homes and business contrasts with reports from July last year that data centres’ huge power demands were putting such acute pressure on the west London grid, that new home-building projects had to be halted because not enough power could be sent to substations, i.e. local data centres were using all the power.

What Does This Mean For Your Organisation? 

How to deal with the heat produced by the ever-growing demand on and for new data centres, particularly since generative AI chatbots came along is a significant issue. This project, therefore, is an example of a way to put the heat to good use for the community and businesses rather than wasting it, thereby providing hopefully cheaper and abundant supplies of heat (albeit in a limited area), giving a greener and more sustainable way to heat homes and businesses, plus helping to meet London’s ambitious target to become a net zero city by 2030.

That said, although the local West London data centres can provide surplus heat for the project, as concerns from last year show, their huge energy requirements in the first place is a problem in itself both in how to supply it in a greener way and in the negative impact on local area housing developments, i.e. local data centres using so much power that demand for new home projects can’t be met.

This scheme, however, is one of many new, innovative, and welcome ways around the world to use the surplus heat from data centres for homes and businesses, although tackling the initial issues of how to meet data centres’ enormous power demands with cleaner and more sustainable energy and not just relying on offsetting, and finding effective cooling solutions for data centres remain major challenges.

Sustainability-in-Tech : Microsoft’s Green Concrete In Data Centres

As part of its commitment to be carbon negative by 2030, Microsoft is trialling cement containing microalgae-based limestone in its data centre builds.

The Issue For Microsoft 

The main issue for Microsoft is that it needs to decarbonise its data centre builds by reducing the amount of ‘embodied carbon’ in the concrete used to build its data centres, thereby helping it to hit its green targets. Embodied carbon is the measure of the carbon emitted during the manufacturing, installation, maintenance, and disposal of a product or material (in this case, concrete).

The Issue With Traditional Concrete

The issue with traditional concrete is that its embodied carbon is responsible for around a massive 11 per cent of global greenhouse gas emissions!

Most of the emissions associated with concrete are the result of the key ingredient of cement being limestone. For example, traditional Portland cement is produced by quarrying limestone in large quarries and burning it at high temperatures (heating it with clay around 2,650 degrees Fahrenheit) which results in the production 2 gigatons of carbon dioxide every year! Also, Portland cement, the most popular kind of cement, uses ground (quarried) limestone. The quarrying process not only produces massive amounts of damaging greenhouse gasses, but also has a serious environmental impact. Although Portland Cement typically forms 7 to 15 per cent of a concrete mix by weight, it can contribute 80 to 95 per cent of the embodied carbon in concrete.

What Is Microalgae-Based Limestone And How Can It Help? 

Microalgae-Based Limestone, often referred to as a “biogenic limestone,” is produced (in the lab) from microalgae such as coccolithophores, which has a cloudy white appearance. These microalgae produce the largest amounts of new calcium carbonate on the planet at a much faster rate than coral and do so by capturing and storing CO2 from the atmosphere in the form of calcium carbonate shells that form on their surface. By replacing the quarried limestone with this naturally produced biogenic limestone (which also stores carbon from the atmosphere) in a concrete mix, Microsoft aims to find a mix design that can lower embodied carbon in concrete by more than 50 per cent compared to traditional concrete mixes.

Pilots Under Way 

With this in mind, Microsoft already has a pilot under way in Quincy (Washington) for biogenic limestone concrete mix.

Microsoft is also experimenting with a concrete mix with fly ash and slag that are activated with alkaline soda ash, and with both the alkali activated cement and biogenic limestone.

Signed An Open Letter 

Amazon (AWS), Google, Meta, and Microsoft all recently released an open letter on the iMasons (Infrastructure Masons) website, which calls for action to use greener concrete in data centre infrastructure and encourage other companies to join them.

Other Investment 

Microsoft’s Climate Innovation Fund, which was launched in 2020, also invests in early-stage companies engaged in work to find solutions that could cut the amount of embodied carbon in concrete and other building materials to zero.

For example, one early investment was in ‘CarbonCure,’ which deploys low carbon concrete technologies that inject captured carbon dioxide into concrete, where the CO2 immediately mineralises and is permanently embedded as nanosized rocks within the physical product. This acts both as both a carbon sink and a way to strengthen the material, enabling a reduction in the amount of carbon-intensive cement required.

What Does This Mean For Your Organisation?

Microsoft’s pursuit of greener concrete through micro-algae-produced biogenic limestone shows how its leveraging its influence partly to meet its own targets, but also for a more sustainable future. Their initiative not only aligns with their overarching objective to achieve carbon negativity by 2030, but also seems to underline a broader vision of constructing markets and technologies that facilitate the decarbonisation journey. If a way could be found to completely replace quarried limestone, the prize could be a potential reduction of 2 gigatons of carbon dioxide annually, a game changer in the global fight against climate change. Also, the mass production of microalgae not only sequesters more carbon but also promises multiple environmental benefits like improved air quality and reduced quarry-induced damage.

The prospect of seamlessly substituting biogenic for quarried limestone without compromising product quality, combined with the potential economic benefits from microalgae by-products, does sound very promising.

Drawing from insights like those of the iMasons Climate Accord, the path forward appears to need collective industry efforts, innovative research, and consistent progress measurements. If Microsoft’s pilot experiments manage to pinpoint the ideal green concrete mix, it could help revolutionise the building industry, let alone help Microsoft to decarbonise its own data centre builds. This could significantly curb greenhouse gas emissions and environmental degradation linked to cement and concrete production (which is something that’s much needed).

Pioneering efforts by Microsoft and the other big tech companies that published the open letter may not only advance their own sustainability goals but could potentially present effective and sustainable solutions for the greater good of the planet.

Sustainability-in-Tech : Data Centres May Have Their Water Restricted

The recent announcement by Thames Water that it may restrict water flows to London data centres and charge them more at times of peak demand may be the shape of things to come.

Thames Water Ltd – Considering Restrictions 

The announcement follows an investigation last year into how much water was being used by London and M4 corridor datacentres. At the time, Thames Water’s Strategic Development Manager, John Hernon, said that he was looking to work closely “with those consultants planning for new datacentres in the Slough area” and saying, “Our guidance has already resulted in a significant reduction in the amount of water requested by these new centres due to guidance on additional storage and cooling procedures”. 

What’s The Issue? 

The main issue is that datacentres require vast amounts of water for cooling and the water they currently use is drinking water from supply pipes. This can put pressure on supply and infrastructure during hot weather when demand for water surges. It should also be noted that datacentres also require substantial amounts of electricity.


To address these issues, Thames Water Ltd has announced that it has discussed with at least one datacentre operator in London about physically restricting the water flow at peak times. John Hernon has been reported as saying that this could involve introducing flow restrictions on pipes.

What Are The Alternatives To Physically Restricting Water? 

Although Thames Water has discussed restricting water flow to the datacentres, the company has said it would prefer to take a collaborative approach with datacentres, encouraging them to look at water reusage and recycling options on-site. This could involve reusing final effluent from the company’s sewage treatment works or intercepting and surface water before it reaches treatment plants.

Thames Water first raised the issue of datacentres using raw water in August 2022. At the time, a drought had led them to introduce a hosepipe ban affecting 15 million customers in the southeast (including London and the Thames Valley area), bringing the issue of how much drinking water datacentres were using into sharp focus.

In Other Countries 

Although water is the traditional cooling method for data centres, in some other countries and regions they also use different cooling methods depending on factors like climate, local regulations, and available resources. For example, some common cooling methods include air cooling, or specialised cooling solutions like chilled water systems. Some recent experiments in data centre cooling methods have also included immersing servers in liquid / engineered fluid, i.e. immersion cooling (which Microsoft now uses at its datacentre in Quincy, WA in the US), and underwater datacentres such as Microsoft’s Project Natick. Other recent and innovative data centre cooling ideas have included a decentralised model whereby homeowners are incentivised to have business servers attached to their home water tanks for cooling.


Even though it would make sense for datacentres to get their large water requirements from somewhere other than the drinking water supply, some have criticised Thames Water for scapegoating the datacentre industry when the water company doesn’t appear to be doing much about losing 600 million litres of water a day (nearly a quarter of its daily supplies) through leaks.

What Does This Mean For Your Business? 

Pressures such as climate change, the growth of the digital society, cloud computing, the IoT, and the newer pressures of widescale use of generative AI have all fed the demand for more datacentres and have exacerbated the cooling challenges faced by them. Although some innovative alternatives are being tried, datacentres predominantly have huge water and power requirements and, as the Tames Water area example shows, the fact that they tap into drinking water can be a big problem in drought or at peak general demand times. Businesses require reliable computing and access to their cloud resources as well as water (and power) illustrating the importance to the wider economy and society of finding a solution that enables data centres to function reliably while not negatively impacting other infrastructure, businesses, and the economy or, indeed, climate targets.

Using raw water may be one alternative that could help (as could fixing leaks as some critics argue). Some other methods such as immersion cooling or underwater datacentres look promising, but these may take some time to scale up. AI may also prove to be helpful in helping to improve the management of datacentre cooling.

There are, in fact, many methods that could ultimately all help tackle the problem, such as optimising airflow management, implementing intelligent monitoring systems, utilising computational fluid dynamics simulations, and exploring innovative architectural designs. All these methods could help by enhancing airflow efficiency, preventing hotspots, improving heat dissipation, proactively adjust cooling parameters, informing cooling infrastructure design, and dynamically adapting to workload demands to meet the modern cooling challenges faced by data centres.

For Thames water, the idea of working collaboratively with datacentres rather than simply imposing water restrictions sounds a sensible way forward because datacentre cooling is a challenge that now affects all of us and needs intelligent solutions that work and can be put into practice soon.

Tech Insight : The Impact of Generative AI On Datacentres

Generative AI tools like ChatGPT plus the rapid and revolutionary growth of AI are changing the face of most industries and generating dire warnings about the future, but what about the effects on datacentres?

Data Centres And Their Importance 

Data centres are the specialised facilities that house a large number of computer servers and networking equipment, serving as centralised locations where businesses and organisations store, manage, process, and distribute their digital data. These facilities are designed to provide a secure, controlled environment for storing and managing vast amounts of data in the cloud.

In our digital, cloud computing business world, data centres, therefore play a crucial role in supporting various industries and services that rely on large-scale data processing and storage, and are utilised by organisations ranging from small businesses to multinational corporations, cloud service providers, internet companies, government agencies, and research institutions.

The Impacts of Generative AI

There are number of ways that generative AI is impacting data centres. These include:

– The need for more data centres. Generative AI applications require significant computational resources, including servers, GPUs, and data storage devices. As the adoption of generative AI grows, data centres will need to invest and expand their infrastructure to accommodate the increased demand for processing power and storage capacity and this will change the data centre landscape. For example, greater investment in (and greater numbers of) data centres will be needed. It’s been noted that the massive data-crunching requirements of AI platforms like ChatGPT, for example, couldn’t continue to operate without using Microsoft’s (soon-to-be-updated) Azure cloud platform. This has led to Microsoft now building a new 750K SF hyperscale data centre campus near Quincy, WA, to house three 250K SF server farms on land costing $9.2M. Presumably, with more data centres there will also need to be greater efforts and investment to reduce and offset their carbon consumption.

– Greater power consumption and more cooling needed. Generative AI models are computationally intensive and consume substantial amounts of power. Data centres also have backup power sources to ensure a smooth supply, such as uninterruptible power supplies (UPS) and generators. With more use of generative AI, data centres will need to ensure they have sufficient power supply and cooling infrastructure to support the energy demands of generative AI applications. This could mean that data centres will now need to improve power supplies to cope with the demands of generative AI by conducting power capacity planning, upgrading infrastructure, implementing redundancy and backup systems, optimising power distribution efficiency, integrating renewable energy sources, implementing power monitoring and management systems, and collaborating with power suppliers. These measures could enhance power capacity, reliability, efficiency, and sustainability. More data centres may also need to be built with their own power plants (like Microsoft did in Dublin in 2017).

In terms of the greater need for cooling, i.e. to improve cooling capacity for generative AI in data centres, strategies include optimising airflow management, adopting advanced cooling technologies like liquid cooling, implementing intelligent monitoring systems, utilising computational fluid dynamics simulations, exploring innovative architectural designs, and leveraging AI algorithms for cooling control optimisation. These measures could all enhance airflow efficiency, prevent hotspots, improve heat dissipation, proactively adjust cooling parameters, inform cooling infrastructure design, and dynamically adapt to workload demands to meet the cooling challenges posed by generative AI.

– The need for scalability and flexibility. Generative AI models often require distributed computing and parallel processing to handle the complexity of training and inference tasks. Data centres therefore need to provide scalable and flexible infrastructure that can efficiently handle the workload and accommodate the growth of generative AI applications. Data centres will, therefore, need to be able to support generative AI applications through means such as:

– Virtualisation for dynamic resource allocation.
– High-performance Computing (HPC) clusters for computational power.
– Distributed storage systems for large datasets.
– Enhanced network infrastructure for increased data transfer.
– Edge computing for reduced latency and real-time processing.
– Containerisation platforms for flexible deployment and resource management.

– Data storage and retrieval. Generative AI models require extensive amounts of training data, which must be stored and accessed efficiently. Data centres now need to be able to optimise their data storage and retrieval systems to handle large datasets and enable high-throughput training of AI models.

– Security and privacy. Generative AI introduces new security and privacy challenges. Data centres must now be able to ensure the protection of sensitive data used in training and inferencing processes. Additionally, they need to address potential vulnerabilities associated with generative AI, such as the generation of realistic but malicious content or the potential for data leakage. Generative AI also poses cybersecurity challenges, as it can be used to create vast quantities of believable phishing emails or generate code with security vulnerabilities. Rather than just relying upon a lot of verification, there is likely to be increased dependency on skilled workers and smart software may be necessary to address these security risks effectively.

– Customisation and integration. Generative AI models often require customisation and integration into existing workflows and applications. This means that data centres need to provide the necessary tools and support for organisations to effectively integrate generative AI into their systems and leverage its capabilities.

– Skillset requirements. Managing and maintaining generative AI infrastructure requires specialised skills and data centres will need to invest in training their personnel and/or attracting professionals with expertise in AI technologies to effectively operate and optimise the infrastructure supporting generative AI.

– Optimisation for AI workloads. The rise of generative AI also means that data centres need to find ways to optimise their operations and infrastructure to cater to the specific requirements of AI workloads. This includes considerations for power efficiency, cooling systems, network bandwidth, and storage architectures that are tailored to the demands of generative AI applications.

– Uncertain infrastructure requirements. The power consumption and hardware requirements of the increasing use of generative AI applications are yet to be fully understood and this means that the impact on software and hardware remains uncertain, and the scale of infrastructure needed to support generative AI is still not clear. The implications of this for data centres are, for example:

– A lack of clarity on power consumption and hardware needs/the specific power and hardware requirements of generative AI applications are not fully understood, makes it challenging for data centres to accurately plan and allocate resources.
– The impact of generative AI on software and hardware is still unclear which makes it difficult for data centres to determine the necessary upgrades or modifications to support these applications.
– Without a clear understanding of the demands of generative AI, data centres cannot accurately estimate the scale of infrastructure required, potentially leading to under-provisioning or over-provisioning of resources.

– The need for flexibility and adaptability. Data centres must now be prepared to adjust their infrastructure dynamically to accommodate the evolving requirements of generative AI applications as more information becomes available.

AI Helping AI 

Ironically, data centres could use AI itself to help optimise their operations and infrastructure. For example, through:

– Predictive maintenance. AI analysing sensor data to detect equipment failures, minimising downtime.

– Energy efficiency. AI optimising power usage, cooling, and workload placement, reducing energy waste.

– Workload Optimisation. AI maximising performance by analysing workload patterns and allocating resources efficiently.

– Anomaly Detection. AI monitoring system metrics, identifies abnormal patterns and flags security or performance issues.

– Capacity Planning. AI analysing data to predict resource demands, optimising infrastructure expansion.

– Dynamic Resource Allocation. AI dynamically scaling computing resources, storage, and network capacity based on workload demands.

What Does This Mean For Your Business? 

Overall, while generative AI offers opportunities for increased efficiency and productivity for businesses, it also poses several challenges related to infrastructure, trust, security, and compliance. Data centres in our digital society and cloud-based business world now play a crucial role in supporting industries, business, services and as such, whole economies so how data centres to adapt quickly and effectively to the challenges posed by AI (or not) is something that could potentially affect all businesses going forward.

As a data centre operator or a business relying on data centres for smooth operations, the impact of generative AI on data centres presents both opportunities and challenges. On the one hand, the increased demand for processing power and storage capacity necessitates investments in infrastructure expansion and upgrades, providing potential business opportunities for data centre operators. It may lead to the establishment of more data centres and the need for greater efforts to reduce their carbon footprint.

However, this growth in generative AI also brings challenges that need to be addressed. Data centres must ensure sufficient power supply and cooling infrastructure to support the energy demands and heat dissipation requirements of generative AI applications. This may require capacity planning, infrastructure upgrades, integration of renewable energy sources, and the adoption of advanced cooling technologies. It also presents huge challenges in terms of trying to provide the necessary capacity in a way that minimises carbon emissions and meeting environmental targets.

Additionally, with the rise of generative AI, data centres now need to consider scalability, flexibility, security, and privacy implications. They must provide the necessary infrastructure and tools for businesses to integrate generative AI into their workflows and applications securely. Skillset requirements also come into play, as personnel need to be trained in AI technologies to effectively operate and optimise the data centre infrastructure.

Overall, understanding and addressing the implications of generative AI on data centres is crucial for both data centre operators and businesses relying on these facilities. By adapting to the evolving demands of generative AI and investing in optimised infrastructure and pursuing innovation, data centre operators can provide reliable and efficient services to businesses, ensuring seamless operations and unlocking the potential of generative AI for various industries.