With this, Dell could add more than $80 billion to its market value.

The company reported first-quarter revenue of $43.8 billion for its 2027 fiscal year, far ahead of analyst expectations of about $35 billion.

Earnings also came in stronger than expected, with adjusted earnings per share reaching $4.86 compared with forecasts of roughly $2.94. Net income climbed 256% year-on-year to $3.44 billion.

The strongest growth came from Dell’s Infrastructure Solutions Group, the division responsible for servers and data-centre systems. Revenue in that business jumped 181% to $29 billion as companies continued spending heavily on AI infrastructure.

Dell noted that AI server sales alone reached $16.1 billion during the quarter, up 757% from a year earlier.

The company also booked $24.4 billion in new AI server orders, pushing its backlog to $51.3 billion. That means Dell still has tens of billions of dollars’ worth of systems waiting to be delivered over the coming quarters.

Investors focused heavily on the growing backlog because it gives Dell unusual visibility into future demand at a time when many technology companies still find it difficult to predict how long the AI spending wave will last.

Following the results, Dell raised its full-year revenue forecast to between $165 billion and $169 billion, up from earlier guidance of $138 billion to $142 billion.

The company now expects AI server revenue to hit roughly $60 billion this year, compared with its previous estimate of $50 billion.

Adjusted earnings per share guidance also increased to $17.90 from $12.90.

Dell’s recent growth has been tied to Nvidia, whose graphics processors power most of the company’s AI systems. The results came only days after Nvidia itself reported record data-centre revenue of $75.2 billion, up 92% from a year earlier.

Together, the numbers from both companies point to aggressive spending on AI infrastructure by major technology firms and cloud providers.

Dell has benefited from orders linked to companies including Alphabet, Amazon and CoreWeave, as well as large AI data-centre projects in Europe.

The company has also expanded its partnership with Nvidia through Project Helix, an initiative designed to help businesses build and deploy AI systems more quickly.

The latest earnings added to signs that demand for enterprise AI infrastructure remains strong across the industry. Lenovo recently reported strong AI server growth, while Super Micro Computer continues expanding manufacturing for GPU-based servers.

Technology companies are expected to spend hundreds of billions of dollars on AI data centres this year as competition around AI services intensifies.

Before the recent shares surge, Dell spent years being seen mainly as a PC and storage company. Now, investors view it as one of the major suppliers benefiting from the global vision to build AI infrastructure.

Microsoft has been working towards matching all of its hourly electricity use with renewable energy purchases within the next five years.

That goal, set in 2020, stood out at the time because it went beyond annual offsets and focused on real-time energy use. Now, people familiar with internal discussions say the company is weighing whether to delay or drop it.

The discussion comes as Microsoft spends heavily on infrastructure to support artificial intelligence. Like Amazon and Alphabet, it is building large data centres to run services such as Copilot and its Azure cloud platform.

These facilities require vast amounts of electricity, and demand is rising faster than earlier projections suggested.

Some of the newer sites under development are expected to draw several gigawatts of power. To put that in context, one gigawatt can supply roughly 750,000 homes in the United States. Meeting that level of demand with renewable sources alone is proving difficult, especially within tight timelines.

Energy supply is now a practical concern. Renewable projects take years to plan and build. By contrast, natural gas plants and nuclear facilities can be brought online more quickly, and companies are turning to them to avoid delays.

Microsoft has already taken steps in that direction. In 2024, it reached an agreement with Constellation Energy to help restart a unit at the Three Mile Island nuclear plant in Pennsylvania. The deal shows how the company is balancing its climate targets with immediate energy needs.

The pressure is not limited to Microsoft. Across the sector, emissions have continued to rise despite public commitments to cut them. That gap is drawing attention from regulators and investors, who are watching closely as companies expand their AI operations.

For now, Microsoft has not commented publicly on the reported review. What is clear is that the scale of AI is changing earlier assumptions. The company set one of the most ambitious clean energy goals in the industry. Whether it can still meet it on time is now uncertain.

Against this backdrop, Arista Networks, a global cloud networking company, in partnership with MART Networks and Resourcery Plc, hosted “Efficiency Meets Performance – The Arista Advantage” on Tuesday at the Radisson Blu Anchorage Hotel.

The event brought together telecom operators, financial institutions, and other technology experts, to discuss how to build faster, more reliable networks while keeping costs under control, with particular attention on reducing energy use in a power-constrained market.

Speaking at the event, Arista’s Territory Account Manager for West Africa, Jide Olagbenro, said demand for efficient infrastructure is increasing as organisations look to balance performance with the cost of operation.

“Power is a real issue here,” he said. “You don’t want devices that consume too much energy. That is one of the reasons customers are turning to Arista.”

He added that the company’s solutions are already in use across key sectors in Nigeria, including financial services and large-scale industrial operations, emphasising the growing acceptance in the region.

“We are seeing strong adoption in this market,” he said. “But we need to keep working closely with our partners to expand that reach.”

Arista’s Regional Sales Director for sub-Saharan Africa, Marius Keown, pointed to the company’s global footprint, noting that its technology underpins some of the world’s largest cloud and content platforms.

“Some of the biggest platforms in the world run on our network,” he said. “They would not invest at that level if the technology did not perform.”

He further noted that the company’s growth has been driven largely by engineering focus rather than aggressive marketing. “We focus on building solid technology and letting the results speak.”

Ify Chukwuma, head of Business Development, sub-Saharan Africa at Resourcery Plc Group, highlighted the importance of aligning technology with business needs, drawing on the company’s long-standing presence in Nigeria.

“We’ve been in business for 40 years. That tells you we understand this market,” she said. “What we do is align technology with business needs and deliver solutions that are cost-effective and intelligent.”

She added that partnerships are essential to delivering large-scale infrastructure projects. “We can’t do this alone. That is why we partner with global players like Arista, to bring value to customers and give them peace of mind.”

Esther Oyedokun, country manager at MART Networks, said distribution, training and local support are key to successful deployment across African markets.

“Our goal is simple, to empower businesses with the right technology,” she said. “We don’t just supply products, we provide training, pre-sales and post-sales support, and ensure our partners are fully equipped.”

She noted that access to local stock and technical expertise helps reduce delays and improve service delivery.

On the technical side, Faith Oladapo, product manager for Enterprise Networking at MART Networks, a distributor for Arista Networks, said energy efficiency is becoming a practical concern for operators managing Nigeria’s data centres.

“Our switches can reduce power consumption by up to 30%,” she said. “At first, that may not seem like much, but in a data centre environment, over time, it becomes significant.”

She added that a unified software system across Arista’s products simplifies deployment and reduces licensing complexity.

“We use a single operating system across our products. That makes deployment easier and reduces costs.”

Oladapo also pointed to adequate distribution management as a way to reduce the circulation of unsupported products in the market.

“One of the problems in the market is the spread of unsupported or counterfeit products,” she said. “We manage distribution carefully to ensure customers get genuine, fully supported solutions.”

The company’s near-term focus in Nigeria will be on building local capacity. “We are investing in training partners and engineers, because they are the ones driving adoption on the ground,” Oladapo said.

Efficiency has become an indispensable factor as demand for digital services grows, and organisations place greater emphasis on infrastructure that delivers performance without increasing operational stress.

Arista and its partners are therefore placing priority on delivering networks that combine speed, reliability and lower energy use, across data centres and other sectors, while supporting the scale required by Nigeria’s expanding digital economy.

The programme is expected to begin on Wednesday and comes as demand for digital infrastructure increases across Africa.

Growth in cloud services, artificial intelligence workloads and enterprise data storage has increased requirements on operators to find engineers who can run critical systems.

Experts in the sector say new facilities are opening, but skilled workers remain in short supply.

“There’s a lot of recycling of the same people across companies,” said Adebola Adefarati, Rack Centre’s head of marketing and communications. “People move from one data centre or telco to another, and it becomes a closed loop. The industry has to start creating new talent.”

Rack Centre said many operators still depend on internal training because experienced workers are limited. The problem is bigger in Africa, where specialised training is scarce and trained staff are usually hired away by foreign firms.

According to the company, engineers who can manage infrastructure in Nigeria are especially attractive abroad because they already understand how to work under difficult conditions such as unstable grid power and high temperatures.

“Once people gain experience running reliable systems in Nigeria, they become prime targets,” Adefarati said. “We’ve seen a number of our own people leave for opportunities abroad.”

Rather than compete for the same workers, Rack Centre said it wants to help build a larger talent pipeline for the industry.

Data centres usually run with small teams, but those teams need specialised knowledge. Staff must manage power systems, cooling equipment, network hardware, monitoring tools and emergency response systems around the clock.

The first group will take in between 15 and 20 trainees. Rack Centre said only some may join the company after graduation, while others could move into jobs with telecom firms and other data centre operators.

Participants will receive classroom training, technical certifications and practical experience inside a live operating facility. One certification track will be delivered with Schneider Electric’s training platform. The full programme will run for about four to five months.

Rack Centre said it will fully cover the estimated $2,500 cost per participant.

“The issue is not that people aren’t studying engineering,” Adefarati said. “It’s that they’re not trained to work on systems that must run 100% of the time. Data centres are different. You’re dealing with redundant power, precision cooling, and real-time fault detection in a highly sensitive environment.”

The company said operating in Nigeria brings added pressure. Cooling systems must work efficiently in extreme heat, while power infrastructure must cope with an unreliable national grid.

Rack Centre is also developing the programme with the Africa Data Centres Association, which is working towards training up to 1,000 professionals over the next two years.

The initiative also aims to improve gender balance in the sector. Women are still underrepresented in many technical operations roles, and Rack Centre said it wants at least one-third of each cohort to be female.

“Data centres are often seen as hardware,” Adefarati said. “But their success is fundamentally about people.”

For retailers and digital platforms, these are some of the most commercially significant days of the year. What bargain-hunting consumers don’t see is the behind-the-scenes AI and infrastructure that’s responsible for keeping these experiences running smoothly, or not. 

“At Africa Data Centres, we regularly see how moments of extreme demand test the limits of the digital infrastructure supporting modern retail platforms and AI-driven services,” Adil El Youssefi, CEO at Africa Data Centres, said.

Every step of the digital shopping experience is carefully curated, with search engines pushing relevant products, recommendation systems personalising offers in real time, pricing algorithms adjusting dynamically, fraud detection models screening transactions instantly, and AI-powered customer service tools handling thousands of queries simultaneously. 

However, the quest to improve customer experience and drive revenue introduces a new infrastructure challenge. When millions of users arrive at once, AI workloads spike, placing immense pressure on the infrastructure supporting them. 

Without the right foundation, even the most sophisticated digital platforms can struggle to cope. The same goes for the infrastructure that houses them.

The infrastructure stress of peak demand

Peak demand creates a very different operational environment compared with normal daily workloads. 

During major retail events, e-commerce platforms frequently report traffic spikes of three to five times normal levels. Data from Capitec, for instance, shows that South Africa’s Black Friday weekend alone generated 55 million transactions valued at R25.3 billion. And that’s just one institution.

Each additional customer interaction triggers several AI processes in the background, which, when multiplied across millions of interactions, generate significant compute demand. 

Research from the International Energy Agency suggests that AI-driven data centre workloads are already contributing to rapid increases in power consumption globally, with demand expected to grow sharply as AI adoption accelerates.

For infrastructure operators, this translates into higher power needs, greater heat output, and dramatically increased data movement across networks during peak periods. If these are lacking, performance begins to degrade: latency increases, applications slow down, or services simply become unavailable. 

For businesses, that can translate directly into millions in lost revenue, while slow or unreliable platforms during major promotions can quickly erode trust and drive shoppers elsewhere.

Designing for performance under load

Maintaining consistent AI performance during peak demand, without sacrificing reliability, needs infrastructure designed specifically for these conditions. 

From ADC’s experience supporting high-performance digital environments, four elements consistently prove critical:

1. High-density compute capacity; the powerful GPU clusters capable of processing large volumes of requests simultaneously without bottlenecks. 
2. Power systems engineered for stability under sudden increases in demand, incorporating redundant power distribution and surge-handling capabilities.
3. Advanced cooling systems to deal with the significant rise in heat generation as servers operate at high volumes, maintain stable operating temperatures, and prevent thermal throttling, where hardware automatically reduces performance to avoid overheating.
4. High-bandwidth, low-latency data pipelines capable of moving vast amounts of information quickly and reliably to ensure that recommendation engines, search platforms, and pricing models respond instantly, even when demand surges.

Peak performance is an infrastructure challenge

With digital commerce expanding, high-demand events will only grow more intense, transforming peak performance from a software or cloud-scaling challenge into an infrastructure challenge.

Businesses are quickly recognising that the reliability of their AI infrastructure during peak demand times depends on the physical infrastructure supporting them. When infrastructure is designed to handle these demands, AI systems can deliver the consistent performance customers expect when it matters most.

In the digital economy, this is often the difference between revenue growth and missed opportunity, which is why infrastructure readiness should form part of AI strategy discussions at board level.

The company confirmed on Thursday that it will not proceed with the British phase of the project for now, saying work will resume only when conditions support long-term investment.

Stargate UK, developed with Nvidia and British developer Nscale, was announced in September 2025 as part of a plan to expand global data centre capacity.

The project was expected to deploy up to 31,000 AI chips and strengthen the country’s ability to run its own artificial intelligence systems.

That capacity, usually called sovereign compute, allows a country to manage sensitive data and AI workloads locally instead of relying on overseas providers.

OpenAI said in a statement: “We see huge potential for the UK’s AI future. AI compute is foundational to that goal, we continue to explore Stargate UK and will move forward when the right conditions such as regulation and the cost of energy enable long-term infrastructure investment.”

The decision is a setback for the UK government as Prime Minister Keir Starmer has made artificial intelligence central to his economic plans and wants Britain to attract more global tech investment.

Officials insist talks are still ongoing. A spokesperson said the government is “continuing to work with OpenAI and other leading AI companies to strengthen UK compute capacity”.

At the same time, they pointed to more than £100 billion in private investment that has flowed into the UK’s AI sector since 2024.

The cost of energy is also a big issue. Britain has some of the highest electricity prices in Europe, and large data centres require vast amounts of power to run and cool advanced chips. Regulation is another concern, especially those around data use and copyright.

OpenAI has been expanding its data centre footprint in other regions. Its Stargate programme includes projects in the United States, Norway and the United Arab Emirates. The first major campus is already underway in Texas.

The pause in the UK also comes as the company strengthens its focus. It has scaled back some side efforts and is concentrating more on core services like ChatGPT.

Competition is increasing, with companies such as Anthropic and Google pushing ahead with their own systems.

Despite the Stargate project delay, OpenAI says it will continue discussions with the UK government, including plans to support public services with its technology.

For now, the project is on hold, with no timeline for when work might begin.

The funding round was led by VoLo Earth Ventures, which focuses on climate-related technologies. The company said the investment will help it grow its team, build its platform and strengthen talks with large technology firms.

Spending on data centres is expected to reach nearly $700 billion this year, driven largely by AI workloads. At the same time, energy use from these facilities is projected to double by 2028.

Refiant is trying to tackle that problem by making AI models smaller and less power-hungry. The company said it has already compressed a 120 billion parameter model so it can run on a standard laptop. Normally, such a model would require far more powerful hardware.

According to the company, the compressed version runs on a MacBook Pro with 12GB of memory. It keeps between 95% and 99% of its original performance. It can also run alongside another model on the same device.

Sid Gutta, co-founder of Refiant, said: “AI’s growing energy footprint is one of the most urgent and underappreciated challenges in the climate space. The industry’s default answer is to build more data centres and consume more power. Ours is to make the AI itself dramatically more efficient.”

The company, based in California, said it tested energy use inside a Faraday cage to ensure accurate readings. Under those conditions, the system reached about 3,000 tokens per kilowatt-hour.

That is up to 100 times more efficient than running the same model in a traditional data centre.

In practical terms, the energy used for one AI task on standard infrastructure could handle about 100 similar tasks using Refiant’s approach.

The founders argue that improving efficiency is a better long-term path than expanding infrastructure. Running AI locally on smaller machines could also help organisations avoid sending data to large cloud providers, which usually means higher costs and less management.

Recent developments from Google have pointed in a similar direction. Its TurboQuant compression method reduced memory needs significantly, reinforcing interest in making models leaner rather than simply scaling hardware.

Dr Viroshan Naicker, co-founder of Refiant, said: “The AI industry is spending hundreds of billions scaling infrastructure when the real breakthrough is the ability to do more with radically less. Nature doesn’t build by brute force. Evolution optimises. We’ve applied that principle to AI, and the results speak for themselves.”

The company believes its work could also help businesses balance AI adoption with environmental targets.

Mathew Haswell, another co-founder, said: “Those two mandates don’t have to be in tension. AI adoption and sustainability commitments can coexist, but only if the technology itself becomes more efficient. 

“Organisations shouldn’t have to choose between deploying AI and meeting their energy targets – and they shouldn’t have to send their data halfway around the world to do it.”

Joseph Goodman, managing partner at VoLo Earth Ventures, added: “AI’s biggest constraint isn’t demand, it’s energy. What’s been missing is a fundamentally more efficient way to compute.

“Refiant’s architecture replaces brute-force scaling with a far more efficient, nature-inspired approach that lowers energy use while increasing capability. That’s the kind of breakthrough needed to make AI sustainable on a global scale.”

Refiant said it is already in discussions with several multinational firms. It plans to push its technology further, with a focus on stronger compression, longer context handling and better tracking of how models operate.

Intel said on Thursday that Google will continue using its Xeon processors across a wide range of workloads.

This includes inference and general computing, as companies move from training AI models to running them in real-world applications.

That transition is changing demand. More firms now need chips that can handle steady, heavy workloads rather than short bursts of training. CPUs are becoming more important again, especially for inference tasks and memory-heavy operations.

Google will also adopt Intel’s latest Xeon 6 processors. These chips are designed to improve efficiency and handle larger volumes of data.

According to the companies, they are already being used in Google Cloud’s C4 virtual machines, where they deliver significant cost improvements when running open-source AI models.

At the same time, both firms are working more closely on infrastructure processing units, known as IPUs.

These chips take over tasks such as networking, storage and security, which are usually handled by CPUs. In moving those jobs away, the CPUs can focus on core computing work.

Intel’s chief executive Lip-Bu Tan said: “Scaling AI requires more than accelerators – it requires balanced systems. CPUs and IPUs are central to delivering the performance, efficiency and flexibility modern AI workloads demand.”

The growing use of agent-based AI systems is also pushing demand higher. These systems carry out multi-step tasks and need more background processing power, which usually falls on CPUs rather than specialised accelerators.

For Intel, this is important as the company lost ground earlier in the AI boom to competitors that focused on graphics processing units. Now, it is trying to recover by strengthening its position in general-purpose and infrastructure computing.

The partnership with Google gives it a strong foothold in cloud computing, where demand for AI services is continually increasing.

Intel is also expanding its efforts elsewhere. It recently said it will join a new AI chip project linked to Elon Musk, working alongside SpaceX and Tesla to support robotics and data centre development.

In manufacturing, the company plans to take full control of its Ireland facility by buying back a stake from Apollo Global Management. The site produces Xeon server processors and is paramount to Intel’s supply chain.

Both Google and Intel are expected to highlight their joint work later this month at Google Cloud Next 2026 in Las Vegas, where they will present updates on AI infrastructure, security and edge computing.

The appointment takes effect immediately. Maxson joins from Schneider Electric, where she served as group CFO.

The company generates more than $45 billion in annual revenue and has seen strong demand linked to data centre growth.

At Oracle, she steps into the role at a time when spending is increasing. The company has been investing heavily in data centres, multicloud systems and AI-ready infrastructure. Demand for those services continues to outpace supply.

Maxson said she would focus on disciplined investment. “I aim to ensure continued disciplined investment for creating lasting value for both customers and shareholders.”

Her background in energy could prove useful. Data centres require large amounts of power, and efficiency has become a growing concern as companies scale AI systems. Oracle has been increasing capacity while managing the cost and complexity that comes with it.

Oracle is growing fast, but that growth is expensive. The company has taken on more debt to support its build-out, and investors are watching closely.

In its latest quarter, Oracle reported its best results in 15 years, with revenue growth above 20%. Even so, its stock has struggled this year. Shares were trading around $146 on April 6, still about 25% below their 52-week high despite a slight rise in early trading.

Investors have pointed to the high debt levels and the cost of scaling AI infrastructure. Competition is also intense, with companies like Microsoft, Amazon and Google continuing to invest heavily in their own cloud platforms.

Maxson, 48, will receive a base salary of $950,000 and is eligible for a performance-based bonus with a target of $2.5 million, according to a regulatory filing.

Her appointment also brings a change in leadership structure. Doug Kehring, who has handled the finance role for the past six months, will step down and return to leading go-to-market operations.

Hilary Maxson will report directly to Oracle CEO Clay Magouyrk, revealing a stronger link between finance and the company’s cloud growth plans.

According to AWS’s official status dashboard update, two facilities in the UAE were directly struck by drones, while one facility in Bahrain sustained physical damage from a nearby drone strike.

The company stated: “These strikes have caused structural damage, disrupted power delivery to our infrastructure, and in some cases required fire suppression activities that resulted in additional water damage.”

This marks one of the first publicly confirmed physical military attacks on a major hyperscale cloud provider’s infrastructure.

The incidents affected the AWS Middle East (UAE) Region (ME-CENTRAL-1) and the AWS Middle East (Bahrain) Region (ME-SOUTH-1), leading to outages and degraded performance for services including EC2, S3, DynamoDB, Lambda, and RDS.

AWS has described the recovery as prolonged and unpredictable due to ongoing regional instability.

Customers have been advised to activate disaster recovery plans and migrate workloads to other AWS regions where possible.

Impact on Businesses and Users

The attacks caused service interruptions for banks, delivery apps, government services, and enterprises across the Gulf that depend on these availability zones.

With data centres becoming strategic targets in modern conflicts, this incident highlights the physical vulnerabilities of cloud infrastructure, even for tech giants like Amazon.

AWS and local authorities have not reported casualties from the strikes.

For African businesses and developers heavily reliant on AWS; common for Nigerian fintechs, startups, and enterprises routing through global cloud providers, this serves as a reminder of geopolitical risks.

Experts recommend multi-region redundancy and regular failover testing to avoid similar disruptions.

Amazon has not released detailed images or extent of damage, citing security reasons.

Recovery efforts were reported as making progress in some areas, but full restoration timelines remain unclear.