Artificial Intelligence in Data Centre Operations

'Agentic core networks shape 6G, unlocking new business'

At MWC Barcelona 26, Dr Wen Tong, Huawei Wireless CTO, delivered a keynote speech on 6G core network. He introduced Agentic Core Networks as the revolutionary 6G-orientated AI core network driven by agentic AI and explained that the architecture seamlessly integrates application creation with network customisation to deliver intent-as-a-service, empowering operators to explore new business models and drive growth in the 6G era. The agentic AI technology is rapidly redefining applications and services from human-centric to agent-centric. This transition is already fuelling an explosion in data traffic, with global token consumption surging by over 100 times in the past year and traffic from AI-training web crawlers increasing 21-fold. At the same time, AI agents have seen rapid adoption in enterprise scenarios, with 80% of Fortune 500 companies now integrating them into their operations. AI will be a pivotal enabler of 6G. From AI-enabled terminals to AI-powered wireless networks and AI core networks, the industry is exploring ways to integrate AI into end-to-end 6G systems to improve spectral and energy efficiency, as well as to establish a robust foundation for the rapid growth of AI applications. In this transformation, the role of the AI core network is particularly critical. It will align with the advancing trends in AI technologies, reshaping the 6G core network by incorporating agentic AI. This transformation will unlock new service models and monetisation avenues, as well as expanding business opportunities for operators. The introduction of Agentic Core Networks Agentic Core Networks architecture brings a fundamental shift to service processes. Traditionally, all operations were carried out based on predefined procedures. However, the AI core network utilises Agentic NAS to proactively detect user needs, predict user intent ahead of OTT applications, and autonomously generate, execute, and continuously optimise personalised services through multi-agent collaboration. This transition enables fully automated operations, reduces TCO, ensures a superior user experience, shifting from fixed connections to intent-driven services. Agentic Core Networks will become integrated platforms of network functions, operator services, and third-party tools. This architecture enables service applications to be dynamically onboarded and iterated like plug-ins, cutting service rollout time from weeks down to minutes. More than a technological advancement, this marks a strategic shift in operators' business models: from providing connectivity to delivering intelligent services, from passively meeting user needs to proactively enabling service scenarios, and from relatively closed network systems to open ecosystems. Closed-loop capabilities spanning intent recognition, AI-driven generation, and ecosystem monetisation will be essential for operators seeking to capture value in the 6G era. Agentic Core Networks capabilities will allow 6G to deliver precise services in high-value scenarios. For example, in dynamic hotspots such as stadiums or disaster recovery sites, 6G can be deployed on demand and reclaimed once the need subsides. In the short term, high-value applications - like autonomous taxi dispatch or remote assistance by humanoid robots and AI-driven orchestration - will unlock new business opportunities. Ultimately, it will help 6G strike the optimal balance between deployment costs and business value. In his address, Wen concluded that the strategic priorities of Agentic Core Networks are becoming increasingly clear. He called for accelerating exploration in the 5G-A era to build a solid connectivity foundation for AI terminals and applications, powered by multi-dimensional network capabilities. This, he noted, represents the first step for the evolution of the entire industry ecosystem. Looking ahead, Wen emphasised that with the advancement of 6G standards and technologies, Agentic Core Networks will enable collaboration between terminals and networks, foster scenario-specific applications, and cultivate a robust industry chain ecosystem. These efforts, he added, will infuse the entire mobile industry with new vitality and unlock new growth opportunities. MWC Barcelona 2026 was held between 2–5 March in Barcelona, Spain. During the event, Huawei showcased its latest products and solutions at Stand 1H50 in Fira Gran Via Hall 1. The era of agentic networks is now approaching fast, and the commercial adoption of 5G-A at scale is gaining speed. Huawei says it is actively working with carriers and partners around the world to unleash the full potential of 5G-A and pave the way for the evolution to 6G. It adds that it is also creating AI-Centric Network solutions to enable intelligent services, networks, and network elements (NEs), speeding up the large-scale deployment of level-4 autonomous networks (AN L4), and using AI to upgrade its core business. Together with other industry players, it says it will create leading value-driven networks and AI computing backbones for a fully intelligent future. For more information, you can visit Huawei’s website by clicking here. For more from Huawei, click here.

Huawei: Accelerating towards the agentic internet era

At MWC Barcelona 2026, Li Peng, Huawei's Senior Vice President and President of ICT Sales & Service, delivered a keynote on how carriers can maximise the value of 5G-A and AI to accelerate towards the agentic internet era. Li proposed that, as networks converge with AI, carriers have the opportunity to redefine the value of connectivity by upgrading to "5G-A x AI". He says this will allow them to not only monetise traffic and experience, but also AI services. Leap in industry value: Entering a 10-trillion-dollar agentic internet era Over the past few years, the mobile industry has steadily evolved from 4G to 5G, and some carriers have begun deploying 5G-A. As networks are stronger than ever, they are bringing intelligent applications to all kinds of devices. Li said, "This year, we're entering the agentic internet era. Networks will not only connect people; they will also connect hundreds of billions of agents." The rise of agent applications over the next decade, however, will increase connectivity demands, as networks will not simply facilitate human communication but also communication between agents. This will drive carriers to shift from offering traffic to offering high-value services and open up a new market worth $10 trillion (£7.4 trillion). Business model upgrade: Elevating brands and offerings to unlock new revenue streams The evolution of network capabilities will also result in changes to carrier business models. In the seven years since the commercialisation of 5G, more than 300 carriers around the world have launched new packages to monetise traffic, and this has helped them grow both their revenue and user-base. As 5G networks continue to mature, experience monetisation will be more essential to carriers' success. 5G SA and 5G-A provide more diverse network resources that more than 30 leading carriers have used to launch experience-based packages to monetise speeds, latency, and more. By dynamically scheduling resources, carriers can go beyond "best-effort" service to deterministic experience. This helps them strengthen brand reputation and users' willingness to spend on premium services. By offering services like custom logo displays and multi-level speed boosts, carriers are able to guarantee network performance at critical moments and enhance users' perception of network quality. Connectivity and AI service convergence: Unleashing new growth potential with AI-powered consumer, home, and enterprise services Li also explained how carriers will be able to transform their main services and improve consumer satisfaction by applying AI models: ● AI for consumers: First, AI can be integrated into traditional calling services. There are currently 5.4 billion calling service users around the world, and AI can be used to unlock features like transcription, translation, and AI assistants. Many of these features have already entered large-scale commercial use in China and South Korea. In addition, more and more carriers are launching AI phones to act as portals for the agentic era. They are using these phones to upgrade their B2C services - the largest source of revenue for most carriers. ● AI for homes: In addition to the recent initiatives by carriers to upgrade home broadband towards ultra-gigabit, AI is also being implemented to enable smart home services. For example, acceleration assistants can guarantee deterministic speeds for key services like gaming and livestreaming. Network assistants can help people optimise their Wi-Fi and resolve network faults via voice commands. AI lifestyle assistants are also a promising avenue for carriers looking to unlock new value from traditional services. By integrating AI with video and storage services, they do things like automatically generating cloud-based family albums that can be shared between devices. ● AI for business: In industrial scenarios, the convergence of 5G-A and AI can be used to transform core workflows and significantly improve production efficiency. For example, in flexible manufacturing, AI-enabled factories will be able to respond to demand in seconds, schedule new production runs in minutes, and deliver new products in hours. New vision: Helping carriers upgrade their portfolio with AI services "Looking ahead, there are still many opportunities just waiting to be unlocked with 5G-A and AI, and carriers are in the best position to explore future applications like massive IoT and embodied AI," said Li at the event. He also recommended three courses of action for carriers to seize these opportunities: First, carriers should evolve all services, devices, and frequency bands to 5G-A to create a thriving network ecosystem. Second, carriers should introduce AI into B.O.M. (business, operations, management) domains; this will provide a foundation for diversified O&M services. Third, carriers should bring intelligence to infrastructure to support the evolution of future network architecture. "Huawei is ready to work closely with carriers to make the most of 5G-A and AI and help them evolve into AI service providers," concluded Li. "We can work with carriers to upgrade their main services through the multi-agent collaboration platform. We can also help them build AI-centric networks for more efficient operations. Together, we can unlock a world of new opportunities and lay a strong foundation for future networks." MWC Barcelona 2026 was held between 2–5 March in Barcelona, Spain. During the event, Huawei showcased its latest products and solutions at Stand 1H50 in Fira Gran Via Hall 1. The era of agentic networks is now approaching fast, and the commercial adoption of 5G-A at scale is gaining speed. Huawei says it is actively working with carriers and partners around the world to unleash the full potential of 5G-A and pave the way for the evolution to 6G. It adds that it is also creating AI-Centric Network solutions to enable intelligent services, networks, and network elements (NEs), speeding up the large-scale deployment of level-4 autonomous networks (AN L4), and using AI to upgrade its core business. Together with other industry players, it says it will create leading value-driven networks and AI computing backbones for a fully intelligent future. For more information, you can visit Huawei's website by clicking here. For more from Huawei, click here.

Huawei showcases industrial intelligence at MWC 2026

During MWC Barcelona 2026, Chinese multinational technology company Huawei released 115 industrial intelligence showcases, together with its customers, during Industrial Digital and Intelligent Transformation Summit 2026. The summit, titled 'Advancing Industrial All Intelligence', was held by Huawei to explore new practices in industrial intelligence with its customers, partners, and peers. The company also announced the launch of upgrades to its SHAPE 2.0 partner framework. In addition, Huawei showcased 22 new industrial intelligence solutions with partners for the electric power, manufacturing and retail, finance, transportation, oil and gas, ISP, media, public service, and smart city sectors. Huawei proposed the ACT Pathway: A replicable intelligence framework AI technologies have advanced rapidly over the last year, with reasoning models and agentic workflows both maturing and physical AI beginning to truly take off. This has allowed AI tools to begin entering core production scenarios and helped applications move from pilots to large-scale use. AI agents can now better understand and interact with the physical world, being capable of making decisions independently. With this in mind, Huawei has introduced the ACT Pathway, which has been developed during its collaboration with global customers over the past few years. Three key steps specified in the ACT framework were mandatory for achieving comprehensive industrial intelligence: The first step is “assessing high-value scenarios”. So far, Huawei has helped customers identify over 1,000 core production scenarios where AI can play a big role. The second step is “calibrating AI models with high-quality vertical data”. Huawei has built a six-layer AI security framework to ensure every stage of the AI lifecycle is secure and trustworthy. The third step is “transforming business operations with AI talent”. Talent that understands both industry and AI are needed. Huawei does this by focusing on four areas, including hands-on practice programs, CANN open-source communities, vertical industry communities on Huawei Cloud, and ICT Academies. Huawei worked with customers to release global industrial intelligence showcases During the summit, a number of Huawei’s customers joined on stage to help launch 115 global showcases for industrial intelligence, including executives from Eskom, Shandong Port Group, Converge ICT, HM Hospitales, and PetroChina (Beijing)’s Digital Intelligent Research Institute, CNPC, providing reference for organisations of various sectors to embark on their journey towards intelligence. MWC Barcelona 2026 is being held from 2 March to 5 March in Barcelona, Spain. During the event, Huawei is showcasing its latest products and solutions at Stand 1H50 in Fira Gran Via Hall 1. For more information, click here to visit Huawei’s website. For more from Huawei, click here.

Vertiv launches AI predictive maintenance service

Vertiv, a global provider of critical digital infrastructure, has launched a new AI-powered predictive maintenance service, Vertiv Next Predict, aimed at modern data centres and facilities supporting AI workloads, including AI factories. The managed service is designed to move maintenance away from time-based and reactive models, using data analysis to identify potential issues before they affect operations. Vertiv says the service supports power, cooling, and IT systems with the aim of improving visibility and supporting more consistent infrastructure performance. The company notes that, as AI workloads increase compute intensity, data centre operators are under pressure to maintain uptime and performance across increasingly complex environments. In this respect, predictive maintenance and advanced analytics are positioned as a way to support more informed operational decisions. Ryan Jarvis, Vice President of the Global Services Business Unit at Vertiv, says, “Data centre operators need innovative technologies to stay ahead of potential risks as compute intensity rises and infrastructures evolve. “Vertiv Next Predict helps data centres unlock uptime, shifting maintenance from traditional calendar-based routines to a proactive, data-driven strategy. We move from assumptions to informed decisions by continuously monitoring equipment condition and enabling risk mitigation before potential impacts to operations.” AI-based monitoring and anomaly detection Vertiv Next Predict uses AI-based anomaly detection to analyse operating conditions and identify deviations from expected behaviour at an early stage. A predictive algorithm then assesses potential operational impact to determine risk and prioritise responses. The service also includes root cause analysis to help isolate contributing factors, supporting more targeted resolution. Based on system data and site context, prescriptive actions are defined and carried through to execution, with corrective measures carried out by Vertiv Services personnel. According to Vertiv, this approach is intended to support earlier intervention and reduce the likelihood of unplanned outages by addressing issues before they escalate. The service currently supports a range of Vertiv power and cooling platforms, including battery energy storage systems (BESS) and liquid cooling components. Vertiv says the platform is designed to expand over time to support additional technologies as data centre infrastructure evolves. Vertiv Next Predict is intended to integrate as part of a broader grid-to-chip service architecture, with the aim of supporting long-term scalability and alignment with future data centre technologies. For more from Vertiv, click here.

Vertiv predicts data centre innovation trends

Data centre innovation is continuing to be shaped by macro forces and technology trends related to AI, according to a report from Vertiv, a global provider of critical digital infrastructure. The Vertiv Frontiers report, which draws on expertise from across the organisation, details the technology trends driving current and future innovation, from powering up for AI to digital twins and adaptive liquid cooling. Scott Armul, Chief Product and Technology Officer at Vertiv, says, “The data centre industry is continuing to rapidly evolve how it designs, builds, operates, and services data centres in response to the density and speed of deployment demands of AI factories. “We see cross-technology forces, including extreme densification, driving transformative trends such as higher voltage DC power architectures and advanced liquid cooling that are important to deliver the gigawatt scaling that is critical for AI innovation. "On-site energy generation and digital twin technology are also expected to help advance the scale and speed of AI adoption.” The Vertiv Frontiers report builds on and expands Vertiv’s previous annual Data Centre Trends predictions. The report identifies macro forces driving data centre innovation. These include: • Extreme densification — accelerated by AI and HPC workloads• Gigawatt scaling at speed — with data centres now being deployed rapidly and at unprecedented scale• Data centre as a unit of compute — as the AI era requires facilities to be built and operated as a single system• Silicon diversification — noting data centre infrastructure must adapt to an increasing range of chips and compute The report details how these macro forces have in turn shaped five key trends impacting specific areas of the data centre landscape: 1. Powering up for AI Most current data centres still rely on hybrid AC/DC power distribution from the grid to the IT racks, which includes three to four conversion stages and some inefficiencies. This existing approach is under strain as power densities increase, largely driven by AI workloads. The shift to higher voltage DC architectures enables significant reductions in current, size of conductors, and number of conversion stages while centralising power conversion at the room level. Hybrid AC and DC systems are pervasive, but as full DC standards and equipment mature, higher voltage DC is likely to become more prevalent as rack densities increase. On-site generation - and microgrids - will also drive adoption of higher voltage DC. 2. Distributed AI The billions of dollars invested into AI data centres to support large language models (LLMs) to date have been aimed at supporting widespread adoption of AI tools by consumers and businesses. Vertiv believes AI is becoming increasingly critical to businesses, but how - and from where - those inference services are delivered will depend on the specific requirements and conditions of the organisation. While this will impact businesses of all types, highly regulated industries (such as finance, defence, and healthcare) may need to maintain private or hybrid AI environments via on-premise data centres, due to data residency, security, or latency requirements. Flexible, scalable high-density power and liquid cooling systems could enable capacity through new builds or retrofitting of existing facilities. 3. Energy autonomy accelerates Short-term, on-site energy generation capacity has been essential for most standalone data centres for decades to support resiliency. However, widespread power availability challenges are creating conditions to adopt extended energy autonomy, especially for AI data centres. Investment in on-site power generation, via natural gas turbines and other technologies, does have several intrinsic benefits but is primarily driven by power availability challenges. Technology strategies such as 'Bring Your Own Power (and Cooling)' are likely to be part of ongoing energy autonomy plans. 4. Digital twin-driven design and operations With increasingly dense AI workloads and more powerful GPUs also comes a demand to deploy these complex AI factories with speed. Using AI-based tools, data centres can be mapped and specified virtually - via digital twins - and the IT and critical digital infrastructure can be integrated, often as prefabricated modular designs, and deployed as units of compute, reducing time-to-token by up to 50%. This approach will be important to efficiently achieving the gigawatt-scale buildouts required for future AI advancements. 5. Adaptive, resilient liquid cooling AI workloads and infrastructure have accelerated the adoption of liquid cooling, but, conversely, AI can also be used to further refine and optimise liquid cooling solutions. Liquid cooling has become mission-critical for a growing number of operators, but AI could provide ways to further enhance its capabilities. AI, in conjunction with additional monitoring and control systems, has the potential to make liquid cooling systems smarter and even more robust by predicting potential failures and effectively managing fluid and components. This trend should lead to increasing reliability and uptime for high value hardware and associated data/workloads. For more from Vertiv, click here.

Sabey's Manhattan facility becomes AI inference hub

Sabey Data Centers, a data centre developer, owner, and operator, has said that its New York City facility at 375 Pearl Street is becoming a hub for organisations running advanced AI inference workloads. The facility, known as SDC Manhattan, offers dense connectivity, scalable power, and flexible cooling infrastructure designed to host latency-sensitive, high-throughput systems. As enterprises move from training to deployment, inference infrastructure has become critical for delivering real-time AI applications across industries. Tim Mirick, President of Sabey Data Centers, says, "The future of AI isn't just about training; it's about delivering intelligence at scale. Our Manhattan facility places that capability at the edge of one of the world's largest and most connected markets. "That's an enormous advantage for inference models powering everything from financial services to media to healthcare." Location and infrastructure Located within walking distance of Wall Street and major carrier hotels, SDC Manhattan is among the few colocation providers in Manhattan with available power. The facility has nearly one megawatt of turnkey power available and seven megawatts of utility power across two powered shell spaces. The site provides access to numerous network providers as well as low-latency connectivity to major cloud on-ramps and enterprises across the Northeast. Sabey says it offers organisations the ability to deploy inference clusters close to their users, reducing response times and enabling real-time decision-making. The facility's liquid-cooling-ready infrastructure supports hybrid cooling configurations to accommodate GPUs and custom accelerators. For more from Sabey Data Centers, click here.

Europe races to build its own AI backbone

Recent outages across global cloud infrastructure have once again served as a reminder of how deeply Europe depends on foreign hyperscalers. When platforms run on AWS or services protected by Cloudflare fail, European factories, logistics hubs, retailers, and public services can stall instantly. US-based cloud providers currently dominate Europe’s infrastructure landscape. According to market data, Amazon, Microsoft, and Google together control roughly 70% of Europe’s public cloud market. In contrast, all European providers combined account for only about 15%. This share has declined sharply over the past decade. For European enterprises, this means limited leverage over resilience, performance, data governance, and long-term sovereignty. This same structural dependency is now extending from cloud infrastructure directly into artificial intelligence and its underlying investments. Between 2018 and 2023, US companies attracted more than €120 billion (£104 billion) in private AI investment, while the European Union drew about €32.5 billion (£28 billion) over the same period. In 2024 alone, US-based AI firms raised roughly $109 billion (£81 billion), more than six times the total private AI investment in Europe that year. Europe is therefore trying to close the innovation gap while simultaneously tightening regulation, creating a paradox in which calls for digital sovereignty grow louder even as reliance on non-European infrastructure deepens. The European Union’s Apply AI Strategy is designed to move AI out of research environments and into real industrial use, backed by more than one billion euros in funding. However, most of the computing power, cloud platforms, and model infrastructure required to deploy these systems at scale still comes from outside Europe. This creates a structural risk: even as AI adoption accelerates inside European industry, much of the strategic control over its operation may remain in foreign hands. Why industrial AI is Europe’s real monitoring ground For any large-scale technology strategy to succeed, it must be tested and refined through real-world deployment, not only shaped at the policy level. The effectiveness of Europe’s AI push will ultimately depend on how quickly new rules, funding mechanisms, and technical standards translate into working systems, and how fast feedback from practice can inform the next iteration. This is where industrial environments become especially important. They produce large amounts of real-time data, and the results of AI use are quickly visible in productivity and cost. As a result, industrial AI is becoming one of the main testing grounds for Europe’s AI ambitions. The companies applying AI in practice will be the first to see what works, what does not, and what needs to be adjusted. According to Giedrė Rajuncė, CEO and co-founder of GREÏ, an AI-powered operational intelligence platform for industrial sites, this shift is already visible on the factory floor, where AI is changing how operations are monitored and optimised in real time. She notes, “AI can now monitor operations in real time, giving companies a new level of visibility into how their processes actually function. I call it a real-time revolution, and it is available at a cost no other technology can match. Instead of relying on expensive automation as the only path to higher effectiveness, companies can now plug AI-based software into existing cameras and instantly unlock 10–30% efficiency gains.” She adds that Apply AI reshapes competition beyond technology alone, stating, “Apply AI is reshaping competition for both talent and capital. European startups are now competing directly with US giants for engineers, researchers, and investors who are increasingly focused on industrial AI. From our experience, progress rarely starts with a sweeping transformation. It starts with solving one clear operational problem where real-time detection delivers visible impact, builds confidence, and proves return on investment.” The data confirms both movement and caution. According to Eurostat, 41% of large EU enterprises had adopted at least one AI-based technology in 2024. At the same time, a global survey by McKinsey & Company shows that 88% of organisations worldwide are already using AI in at least one business function. “Yes, the numbers show that Europe is still moving more slowly,” Giedrė concludes. “But they also show something even more important. The global market will leave us no choice but to accelerate. That means using the opportunities created by the EU’s push for AI adoption before the gap becomes structural.”

Study finds consumer GPUs can cut AI inference costs

A peer-reviewed study has found that consumer-grade GPUs, including Nvidia’s RTX 4090, can significantly reduce the cost of running large language model (LLM) inference. The research, published by io.net - a US developer of decentralised GPU cloud infrastructure - and accepted for the 6th International Artificial Intelligence and Blockchain Conference (AIBC 2025), provides the first open benchmarks of heterogeneous GPU clusters deployed on the company’s decentralised cloud platform. The paper, Idle Consumer GPUs as a Complement to Enterprise Hardware for LLM Inference, reports that clusters built from RTX 4090 GPUs can deliver between 62% and 78% of the throughput of enterprise-grade H100 hardware at roughly half the cost. For batch processing or latency-tolerant workloads, token costs fell by up to 75%. The study also notes that, while H100 GPUs remain more energy efficient on a per-token basis, extending the life of existing consumer hardware and using renewable-rich grids can reduce overall emissions. Aline Almeida, Head of Research at IOG Foundation and lead author of the study, says, “Our findings demonstrate that hybrid routing across enterprise and consumer GPUs offers a pragmatic balance between performance, cost, and sustainability. "Rather than a binary choice, heterogeneous infrastructure allows organisations to optimise for their specific latency and budget requirements while reducing carbon impact.” Implications for LLM development and deployment The research outlines how AI developers and MLOps teams can use mixed hardware clusters to improve cost-efficiency. Enterprise GPUs can support real-time applications, while consumer GPUs can be deployed for batch tasks, development, overflow capacity, and workloads with higher latency tolerance. Under these conditions, the study reports that organisations can achieve near-H100 performance with substantially lower operating costs. Gaurav Sharma, CEO of io.net, comments, “This peer-reviewed analysis validates the core thesis behind io.net: that the future of compute will be distributed, heterogeneous, and accessible. "By harnessing both data-centre-grade and consumer hardware, we can democratise access to advanced AI infrastructure while making it more sustainable.” The company also argues that the study supports its position that decentralised networks can expand global compute capacity by making distributed GPU resources available to developers through a single, programmable platform. Key findings include: • Cost-performance ratios — Clusters of four RTX 4090 GPUs delivered 62% to 78% of H100 throughput at around half the operational cost, achieving the lowest cost per million tokens ($0.111–0.149). • Latency profiles — H100 hardware maintained sub-55ms P99 time-to-first-token even at higher loads, while consumer GPU clusters were suited to workloads tolerating 200–500ms tail latencies, such as research, development environments, batch jobs, embeddings, and evaluation tasks.

UK Chancellor urged to use AI for economic growth

UK Chancellor Rachel Reeves has been urged to use the opportunity afforded by AI to ‘Make Britain Great Again’. The news comes as the Government announced that thousands of new AI jobs and billions of pounds of investment will be poured into the next parliament to help stimulate economic growth. New AI Growth Zones Amongst the package of measures proposed for the budget today include a new AI Growth Zone in South Wales, which will create more than 5,000 new jobs for local communities over the next decade, and a further £137 million to support key scientists to drive breakthroughs and develop new drugs, cures, and treatments. Patrick Sullivan, CEO of think tank Parliament Street, argued that with limited options at the budget, only AI can ‘Make Britain Great Again’. He claims, “With limited options due to Labour’s absurd manifesto pledge to rule out income tax rises, the Chancellor is now forced to cobble together a quick fix solution to fill a black hole which is entirely of her own making. "However, the one saving grace is the advent of mass AI adoption, a technology that will bring mass savings at a time when the Government needs it most. “This is Labour’s chance to show that it gets private enterprise and recognises that by supporting tech talent, AI can truly Make Britain Great Again.” Tech expert Graeme Stewart, Head of Public Sector at Check Point Software, says, “The case for investing billions in AI to drive growth and reboot the economy is clear, yet little has been said about the cyber and regulatory risks associated with mass adoption. “Whether it’s attacks on the NHS, nurseries, or local councils, cyber criminals have already proven that nothing in the public sector is off limits. That’s why it’s vital the Chancellor’s AI rollout is backed up with a robust action plan for protecting critical national infrastructure and minimising cyber risk. "We also need to hear more about the Government’s plans to protect the public and private sector from the new wave of AI-enabled cyber-attacks, which require a cohesive national strategy.” Graeme continues, “Mastering AI to drive growth is the right thing to do, but this approach must always go hand-in-hand with the necessary cyber strategy, to ensure the government stays one step ahead of the increasingly lethal cyber threat.” Kenny MacAulay, CEO of Acting Office, a software platform for accounting practices, adds, “With businesses still reeling from the £25 billion National Insurance increase, the Chancellor has a tough task ahead to win the back trust from the private sector. "Proposals for a nationwide AI rollout and investment in infrastructure can help kickstart economic growth, but only alongside a clear action plan to get businesses hiring again. “The industry needs to embrace the opportunities that AI can bring, in terms of centralising technology investment and improving customer service.”

UK Government unveils major AI investment package

The UK Government has announced a comprehensive package of AI-focused reforms and investments to accelerate national renewal, boost economic growth, and cement the UK’s position as a global leader in artificial intelligence. The new investment places AI at the centre of the UK’s Modern Industrial Strategy, unlocking billions in private investment and enabling new opportunities for businesses, researchers, and local communities across the country. AI Growth Zones A new AI Growth Zone in South Wales, developed with Vantage Data Centers and Microsoft, will receive £10 billion in private investment and create more than 5,000 jobs over the next decade. Spanning multiple sites along the M4 corridor, including the former Ford Bridgend Engine Plant, the zone will serve as a major hub for AI infrastructure, research, and advanced digital industries. Each AI Growth Zone will benefit from £5 million in government support to help local businesses adopt AI technologies and develop specialised skills in their workforce. Sachin Agrawal, Managing Director for Zoho UK, comments, "The UK’s bold commitment to harnessing artificial intelligence for national renewal is both timely and visionary. This investment represents a crucial step towards ensuring the benefits of AI and data innovation are distributed fairly across the country. "For businesses, the real opportunity lies not only in adopting AI tools, but in developing the skills, governance, and readiness to apply them responsibly at scale. Keeping data privacy at the centre of any AI strategy creates the right foundation to make informed decisions and adopt AI responsibly. "AI literacy and strong data protection standards will be essential to ensure initiatives are credible and built for long‑term impact. Structured implementation, starting with clearly defined pilot programmes underpinned by automation, governance, and security, will help businesses move beyond experimentation and ensure AI drives sustainable competitive advantage. "With the right guidance and accountability in place, AI can support transformative growth across the UK.” To keep UK firms at the front of global AI capability, the Government is launching a new programme to expand free and low-cost compute access. Up to £250 million will be deployed to help British researchers and startups train models and pursue scientific breakthroughs. Alongside this, a new advance market commitment, worth up to £100 million, will allow the Government to act as an early customer for UK AI hardware startups, supporting domestic chip innovation and ensuring British-designed hardware plays a role in future data centre deployments.