Before now, Microsoft helped fund OpenAI’s rapid growth and used early access to its systems to build new tools across Windows, Office, Azure and other products.

Under the new agreement, Microsoft will remain OpenAI’s main cloud partner, but it will no longer have sole rights to host or distribute OpenAI technology.

That means OpenAI can now reach customers already using other cloud providers, instead of asking them to move to Microsoft Azure first.

Even so, OpenAI products are still expected to launch first on Azure unless Microsoft cannot, or chooses not to, support them.

Microsoft will also keep a non-exclusive licence to OpenAI’s intellectual property until 2032.

Another key change concerns money as Microsoft will no longer pay OpenAI a share of revenue from its own AI-related products. At the same time, OpenAI will continue paying Microsoft a 20% revenue share until 2030, though that amount now has a fixed upper limit.

Following the announcement, Microsoft shares fell about 1% in premarket trading on Monday, while Amazon and Alphabet, Google’s parent company, edged higher.

This means Microsoft has lost a strategic advantage, while its competitors now have a stronger path to offer OpenAI products through their own cloud services.

Still, aside from the exclusive deal, Microsoft is deeply tied to OpenAI. The software company owns about 27% of OpenAI, a stake estimated to be worth around $225 billion after OpenAI’s corporate restructuring last year.

The two companies have faced limitations in recent months, with reports in March saying Microsoft had considered going to court over a proposed $50 billion cloud deal involving Amazon and OpenAI that could have conflicted with earlier exclusivity terms.

There were also signs of stress inside OpenAI. Internal discussions reportedly revealed frustration that the old arrangement limited sales opportunities, especially among companies already committed to AWS or Google Cloud.

For OpenAI, the new structure provides room to expand faster and sell across more platforms.

For Microsoft, the deal removes exclusivity but secures long-term access to OpenAI technology while putting clearer limits on future payments.

For customers, it means more choice and less pressure to rely on a single cloud provider.

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.

The Competition and Markets Authority said on Tuesday it will take a fresh look at Microsoft’s approaches, months after deciding not to act on earlier findings.

This time, the regulator is considering whether to give Microsoft “strategic market status” in business software, and this would allow closer oversight and direct intervention.

At the centre of the case is how Microsoft links its software, including Windows Server and Microsoft 365, to its own cloud platform. Regulators have noted that customers face extra costs when they try to run these tools on rival services.

That, they say, makes it harder for businesses to switch providers or spread workloads across different clouds.

Companies want flexibility and when pricing or licensing regulations get in the way, it limits choice and raises expenses.

The UK cloud market is tough. Amazon and Microsoft each control about 30 to 40% of the sector, covering services such as storage, processing and networking.

Google follows with a much smaller share of around 5 to 10%. Earlier findings from the regulator said this level of concentration was already affecting competition.

The CMA noted that both Microsoft and Amazon have recently taken steps to ease some of the pressure. These include reducing certain fees tied to moving data between platforms and improving how systems work together. Still, the watchdog expects more changes in the coming months.

CMA chief executive Sarah Cardell said the regulator is acting in a “flexible, pragmatic way to deliver real impact, as quickly as possible for UK customers”.

She added: “Cloud remains central to our approach – we’ve seen real progress through our engagement with Microsoft and Amazon to drive meaningful improvements on egress fees and interoperability and we expect more action from them over the coming months.”

Microsoft says the cloud licensing adjustments it has agreed to focus on data transfers, switching between providers and system compatibility.

Its vice chairman and president, Brad Smith, said: “The changes address the CMA’s commitment to ensuring that UK customers can continue to move, deploy, and operate their workloads in the clouds of their choice with confidence, flexibility, and ever-reduced friction.”

Amazon, for its part, said the steps it has taken formalise its support for customer choice, including the ability to run services across multiple cloud platforms.

Beyond the UK, regulators in both the European Union and the United States are examining similar issues in cloud computing. The focus is largely the same, reviewing whether large providers are using their position in software and infrastructure to limit competition.

Within that surge, the drive between Google and Microsoft has become one to pull focus on, not just for technology leadership, but for how artificial intelligence (AI) turns into profitable business, especially with committed spending.

Two Companies, Two Directions

Even before you look deeper, you’d notice both companies are building similar systems, but you’d see the difference in how those systems are used.

Google is pushing its models into products people already use every day, including Search, Android, and YouTube. Its Gemini platform has crossed 750 million monthly users, giving it reach that few competitors can match.

Microsoft is taking a different route which is more structured. Its Copilot tools are built into Word, Excel, Teams and other workplace software. The idea is to make businesses pay for productivity.

That difference is where we place our attention. Google has scale, while Microsoft has pricing.

The Competition is Infrastructure

It is easy to focus on apps and chat interfaces, but that is not where the case is being decided.

It is in infrastructure you’d find the competition; data centres, chips, and computing power.

Alphabet, Google’s parent company, plans to spend $175 billion to $185 billion in 2026 alone, largely on servers, networking and AI capacity.

Microsoft is also increasing spending, with its capital expenditure expected to move towards $100 billion or more, driven by demand for cloud and AI services.

This level of investment changes the nature of the industry. AI is not just software, it is capital-intensive, closer to energy or telecoms than traditional tech.

I would put it this way, whoever controls compute, controls the market.

Products: Gemini vs Copilot

The difference in strategy becomes better to grasp at the product level.

Google’s Gemini is built for wide use, sitting inside search results, mobile devices and developer tools. Updates have been frequent, with new versions released through 2025 and early 2026 to improve reasoning and performance.

Microsoft’s Copilot is more targeted, focusing on workplace tasks, writing documents, analysing spreadsheets, and summarising meetings.

But adoption?

Microsoft has around 15 million paid Copilot users, a small share of its Microsoft 365 base of hundreds of millions.

That gap stresses the fact that interest in AI tools is high. Paying for them is still limited.

Cloud: Where the Money Actually Comes From

The revenue engine is behind the scenes. Google Cloud has been expanding, with revenue growth close to 48% year-on-year, driven largely by demand for AI workloads.

Microsoft Azure is however a larger business, with strong growth tied directly to AI usage and enterprise demand.

This is where the competition becomes tougher because companies are not just using AI tools, they are renting computing power to run them.

Cloud turns AI into something billable.

Spending is Increasing Faster Than Returns

There is, nonetheless, an imbalance.

Microsoft is targeting $25 billion in AI-related revenue by 2026, supported by Copilot and Azure services.

Google is already seeing profits in advertising and cloud from its AI rollout.

But both are spending far ahead of what they are earning.

Even within Microsoft’s ecosystem, only a small percentage of users are paying for AI features, despite heavy investment and promotion.

So when does this start paying off?

It is Important to note that Investors are not ignoring the risk.

Google’s decision to increase spending has already triggered mixed reactions in the market, even as its core business stands strong.

Microsoft is facing a different issue, which is adoption. Copilot is growing, but not at a pace that fully justifies the scale of investment yet.

So the market is in a strange position, believing in the long-term potential, but watching the short-term numbers carefully.

Here the Bigger Question Comes

This has gone beyond a competition between two companies. Will the current level of investment produce the kind of productivity being promised?

The comparison with past technology cycles is unavoidable. Large amounts of capital are being deployed ahead of proven returns. That does not automatically mean a bubble, but it does introduce risk.

Right now, demand for computing power is strong, but what we don’t know is whether that demand will remain strong enough to justify the infrastructure being built.

Who is Ahead?

The answer depends on how you measure it.

Google is ahead when it comes to reach. Its products touch billions of users, and its AI systems are already embedded into everyday digital activity.

Microsoft comes top in structure. It has a clearer path to monetisation through enterprise software and cloud services.

Google and Microsoft are strong when it comes to AI, both are spending heavily, but neither has fully solved the same problem, which is turning scale into sustained profit.

So, let’s not look at who builds the better model between Google and Microsoft or who comes top in AI spending, but who can turn artificial intelligence into a reliable business before the cost of building it becomes harder to justify.

That is where this growth will be decided.

The newspaper said the incidents resulted from errors involving Amazon’s own tool, known as Kiro. In one case in mid-December, AWS customers experienced a 13-hour interruption.

Engineers had allowed the tool to carry out certain system changes. It then decided to “delete and recreate the environment”, the report said, which led to the disruption.

AWS disputed that account.

In an emailed response to Reuters, a company spokesperson said the disruption was brief and blamed it on user error. “This brief event was the result of user error-specifically misconfigured access controls, not AI.”

The spokesperson added that the interruption was “an extremely limited event” affecting a single service in one of AWS’s two mainland China regions. It did not impact compute, storage, database, AI technologies, or any other AWS services, the company said.

The December incidents follow an outage in October that disrupted Amazon’s cloud operations globally. That earlier failure affected Amazon’s own services and several high-profile apps, including Reddit, Roblox and Snapchat.

AWS is the cloud division of Amazon and supports a large share of the internet’s infrastructure. Because of that reach, even short interruptions can affect millions of users and businesses.

Both Amazon Web Services outages in December have drawn attention because they involved automation tools that can act with limited human input.

Cloud providers have been expanding the use of such systems to manage complex infrastructure. At the same time, customers expect stability and clear accountability when problems occur.

Competitors including Microsoft Azure and Google Cloud are also developing automated tools to manage their platforms.

AWS maintains that the December disruption resulted from misconfigured access controls, not from the coding tool acting on its own.

The collaboration is set to redefine how iconic brands such as Dove, Vaseline, and Hellmann’s engage with consumers in an increasingly digital and “agentic” commerce landscape.

The move signals a major shift for Unilever as it migrates its data and cloud infrastructure to Google Cloud to build an AI-first digital backbone.

Building an ‘AI-First’ Digital Backbone

Under the agreement, Unilever will leverage Google’s enterprise AI platform, Vertex AI, to develop new capabilities in brand discovery and marketing.

The goal is to move beyond traditional advertising toward conversational and agentic experiences, where intelligent systems interact with consumers and execute complex business tasks.

By transitioning its integrated data platform to Google Cloud, Unilever aims to:

• Accelerate Demand Generation: Respond to market shifts with higher agility by turning raw data into actionable insights.
• Deploy Agentic Workflows: Implement intelligent systems capable of managing complex processes across the value chain.
• Modernize Marketing: Utilize AI-augmented tools for better measurement and consumer conversion.

Redefining Value through Technology

The partnership highlights the growing importance of “sovereign” data and specialized AI models in the Fast-Moving Consumer Goods (FMCG) sector.

Willem Uijen, Unilever’s chief supply chain and operations officer, noted that technology is no longer a support function but the core of value creation.

“As brands are increasingly discovered and chosen in environments shaped by AI, we must lead this shift. This collaboration… ensures Unilever is agile, fit for the future, and equipped to unlock value at every level,” Uijen stated.

Tara Brady, president of Google Cloud EMEA, added that the deployment of models like Gemini will create a “system of intelligence” that reasons and learns, setting a new standard for consumer engagement.

The Three Pillars of Collaboration

The five-year roadmap is built on three strategic areas designed to maintain Unilever’s competitive edge:

Agentic Commerce: Building next-gen marketing capabilities to stay ahead of shifting consumer habits.

Integrated Cloud Foundation: Transitioning key enterprise applications to Google Cloud for scalable AI deployment.

Advanced AI Adoption: Combining Unilever’s CPG expertise with Google’s pioneering tech to sustain long-term growth.

This partnership is a clear indicator that the CPG industry is moving away from traditional push marketing toward AI-driven pull commerce.

For Unilever, the move to Google Cloud isn’t just a technical upgrade; it’s a defensive and offensive play to ensure its brands remain visible as AI agents, rather than humans, start making more purchasing decisions in the future.

With many companies looking for stronger safeguards after recent internet disruptions exposed weaknesses in single-cloud setups, the launch comes just in time.

Both firms said the service allows customers to build secure, high-capacity connections between Amazon Web Services (AWS) and Google Cloud in minutes. Before now, many organisations waited weeks to complete the same process due to the technical and approval delays tied to cross-cloud circuits.

Just over a month ago, AWS suffered a major outage on October 20 that spread through its US-East-1 region. A faulty update to DynamoDB’s API triggered DNS failures across the zone, breaking more than 113 AWS services and knocking out platforms such as Snapchat, Reddit, Coinbase and Alexa. 

Analysts estimate the disruption costs U.S. companies between $500 million and $650 million. For many firms, the incident revealed the risk of placing all operations on a single cloud provider.

In response, interest in multicloud resilience has grown. The new service blends AWS’ Interconnect–multicloud with Google Cloud’s Cross-Cloud Interconnect. The aim is to remove friction for organisations that want systems running across several clouds without slow setup cycles or unpredictable routing.

AWS vice president of network services, Robert Kennedy, said the development points to a major shift in how cloud platforms interact. “This collaboration between AWS and Google Cloud represents a fundamental shift in multicloud connectivity.”

Google Cloud also noted the benefit for companies moving large volumes of data between providers. Its vice president and general manager of cloud networking, Rob Enns, stated that the joint framework is meant to simplify workload mobility. Salesforce is one of the early adopters of the new model, according to Google.

Cloud competition is highly intense. AWS continues to top the global market with roughly 29–30% share, while Microsoft Azure holds about 20% and Google Cloud has climbed toward 13%. 

In the third quarter alone, the cloud infrastructure market was valued at around $107 billion, controlled largely by these three companies.

Heavy investment in infrastructure is expected to continue. Increasing demand for artificial intelligence is pushing cloud providers to expand data centres, improve capacity and strengthen network routes. 

AWS recently committed to a multi-year $38 billion partnership with OpenAI, offering access to large clusters of Nvidia GPUs. Google and Microsoft are making similar bets, as AI workloads remain one of the biggest drivers of cloud growth.

In working together on a cross-cloud standard, Amazon and Google have taken an unusual step. The two companies are long-standing competitors, but the new partnership shows a shared interest in reducing latency and making multicloud operations easier for enterprise customers. 

For large users like Salesforce, the ability to deploy cross-cloud links in minutes rather than weeks may prove decisive as businesses seek more resilient infrastructure after recent outages.

The deal, announced Monday, gives OpenAI access to hundreds of thousands of Nvidia GPUs hosted on Amazon’s cloud and is a realignment in the power dynamics of the global tech industry.

The partnership allows OpenAI to immediately begin deploying workloads on AWS infrastructure, which will scale up through 2026 with room for expansion into 2027 and beyond. 

Amazon’s specialised EC2 UltraServers will connect Nvidia’s most advanced processors, H100 and Blackwell chips, through high-speed networks designed for low latency and maximum performance.

For OpenAI, the agreement is part of a goal to build 30 gigawatts of computing capacity, backed by a $1.4 trillion investment plan that highlights the sheer cost of sustaining frontier AI research. 

CEO Sam Altman stressed the scale of the challenge, saying, “Scaling frontier AI requires massive, reliable compute. Our partnership with AWS strengthens the broad compute ecosystem that will power this next era and bring advanced AI to everyone.”

Amazon’s cloud chief, Matt Garman, described the move as a turning point for both companies: “As OpenAI continues to push the boundaries of what’s possible, AWS’s best-in-class infrastructure will serve as a backbone for their AI ambitions.” 

The announcement immediately lifted Amazon’s stock by 5% in premarket trading, adding roughly $330 billion to its market value, its biggest single-day gain in a decade.

The deal follows OpenAI’s recent restructuring, which ended Microsoft’s exclusive cloud arrangement and freed the company to engage multiple infrastructure partners. Although Microsoft still holds a 27% stake in OpenAI, the company has also signed cloud agreements with Google and Oracle, further diversifying its supply chain and reducing reliance on any single provider.

OpenAI’s new partnership with AWS also reveals the competition among the tech giants to control the world’s AI computing backbone. Companies are stockpiling GPUs, expanding data centres, and betting heavily on infrastructure to train and deploy ever-larger models.

Earlier this year, OpenAI’s models became available on Amazon Bedrock, bringing its technology to millions of AWS customers across sectors such as media, health, and data analytics. 

Monday’s announcement pushes that collaboration to an entirely new scale that could change how global AI systems are built and deployed.

With the world’s biggest tech firms spending at unprecedented levels, analysts say the OpenAI–Amazon partnership represents both ambition and risk. 

The scale of investment required to power AI systems is nearing levels once reserved for national infrastructure projects, leading to concerns that the competition could create the industry’s next financial bubble.

Still, for now, the partnership gives OpenAI what it needs most, raw computing muscle. And for Amazon, it offers a decisive edge in the most lucrative race in modern technology: the vision to power the intelligence of the future.

The platform, built on Google’s Gemini models, aims to strengthen the tech giant’s competitive edge in enterprise AI, as Microsoft, OpenAI, and Anthropic, among others, are not holding back.

Gemini Enterprise functions as a conversational system that enables employees to interact directly with company data, documents, and applications. The goal, Google says, is to make AI a core part of every workflow, not just an add-on. “We’re introducing Gemini Enterprise, designed to bring the full power of Google’s AI to every employee, for every workflow,” the company said during the launch.

The announcement comes as Google Cloud continues to expand, having surpassed a $50 billion annual revenue run rate in the second quarter of 2025. According to the company, about 65% of its cloud customers already use Google’s AI products, including nine of the world’s top ten AI labs.

Gemini Enterprise builds upon Google’s full-stack AI strategy, combining the strength of its infrastructure, foundational models, and research divisions such as Google DeepMind. The platform is powered by a multi-layer system, from the company’s purpose-built Tensor Processing Units (TPUs) and Nvidia GPUs, to its world-leading Gemini models, which have consistently topped global performance benchmarks.

Google describes Gemini Enterprise as “the new front door for AI in the workplace.” It features pre-built AI agents capable of conducting deep research, generating data insights, and automating complex workflows. Through a no-code interface, companies can also create and deploy their own agents, tailored to their specific operations.

Early adopters of the platform include Gap, Klarna, and Figma. Klarna, for instance, is using Gemini’s generative tools to produce personalised lookbooks that have boosted customer orders by 50%. 

In the healthcare sector, HCA Healthcare has deployed a “Gemini-powered Nurse Handoff solution” that simplifies patient information transfers between shifts, a move expected to save millions of hours annually.

Google is also using its own technology internally. Nearly half of all new code at the company is now generated by AI and reviewed by engineers, significantly accelerating development cycles.

The launch further reveals Google’s vision for a connected AI ecosystem. Gemini Enterprise securely links with data across multiple platforms, including Google Workspace, Microsoft 365, Salesforce, and SAP, ensuring enterprise-wide access without compromising governance or security.

To encourage adoption, Google is rolling out Google Skills, a free training platform that will teach users how to build and deploy agents within Gemini Enterprise. The company also introduced Delta, a team of expert AI engineers who will work directly with clients to deploy advanced solutions.

With Gemini Enterprise, Google is embedding AI at the very foundation of how organisations work. “AI is presenting a once-in-a-generation opportunity to transform how you work, how you run your business, and what you build for your customers,” the company stated.