Google Faces New Antitrust Trial after Ruling Declaring Search Engine a Monopoly

The Google sign is shown on one of the company's office buildings in Irvine, California, US, October 20, 2020. REUTERS/Mike Blake
The Google sign is shown on one of the company's office buildings in Irvine, California, US, October 20, 2020. REUTERS/Mike Blake
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Google Faces New Antitrust Trial after Ruling Declaring Search Engine a Monopoly

The Google sign is shown on one of the company's office buildings in Irvine, California, US, October 20, 2020. REUTERS/Mike Blake
The Google sign is shown on one of the company's office buildings in Irvine, California, US, October 20, 2020. REUTERS/Mike Blake

One month after a judge declared Google's search engine an illegal monopoly, the tech giant faces another antitrust lawsuit that threatens to break up the company, this time over its advertising technology.

The Justice Department, joined by a coalition of states, and Google each made opening statements Monday to a federal judge who will decide whether Google holds a monopoly over online advertising technology, The AP reported.

The regulators contend that Google built, acquired and maintains a monopoly over the technology that matches online publishers to advertisers. Dominance over the software on both the buy side and the sell side of the transaction enables Google to keep as much as 36 cents on the dollar when it brokers sales between publishers and advertisers, the government contends in court papers.

They allege that Google also controls the ad exchange market, which matches the buy side to the sell side.

“It's worth saying the quiet part out loud,” Justice Department lawyer Julia Tarver Wood said during her opening statement. “One monopoly is bad enough. But a trifecta of monopolies is what we have here.”

Google says the government's case is based on an internet of yesteryear, when desktop computers ruled and internet users carefully typed precise World Wide Web addresses into URL fields. Advertisers now are more likely to turn to social media companies like TikTok or streaming TV services like Peacock to reach audiences.

In her opening statement, Google lawyer Karen Dunn said, “We are one big company among many others, competing millisecond by millisecond for every ad impression.”

Revenue has actually declined in recent years for Google Networks, the division of the Mountain View, California-based tech giant that includes such services as AdSense and Google Ad Manager that are at the heart of the case, from $31.7 billion in 2021 to $31.3 billion in 2023, according to the company's annual reports.

The trial that began Monday in Alexandria, Virginia, over the alleged ad tech monopoly was initially going to be a jury trial, but Google maneuvered to force a bench trial, writing a check to the federal government for more than $2 million to moot the only claim brought by the government that required a jury.

The case will now be decided by US District Judge Leonie Brinkema, who was appointed to the bench by former President Bill Clinton and is best known for high-profile terrorism trials including that of Sept. 11 defendant Zacarias Moussaoui. Brinkema, though, also has experience with highly technical civil trials, working in a courthouse that sees an outsize number of patent infringement cases.

The Virginia case comes on the heels of a major defeat for Google over its search engine, which generates the majority of the company's $307 billion in annual revenue. A judge in the District of Columbia declared the search engine a monopoly, maintained in part by tens of billions of dollars Google pays each year to companies like Apple to lock in Google as the default search engine presented to consumers when they buy iPhones and other gadgets.

In that case, the judge has not yet imposed any remedies. The government hasn't offered its proposed sanctions, though there could be close scrutiny over whether Google should be allowed to continue to make exclusivity deals that ensure its search engine is consumers' default option.

Peter Cohan, a professor of management practice at Babson College, said the Virginia case could potentially be more harmful to Google because the obvious remedy would be requiring it to sell off parts of its ad tech business that generate billions of dollars in annual revenue.

“Divestitures are definitely a possible remedy for this second case,” Cohan said “It could be potentially more significant than initially meets the eye.”

In the Virginia trial, the government's witnesses are expected to include executives from newspaper publishers including The New York Times Co. and Gannett, and online news sites that the government contends have faced particular harm from Google's practices.

“Google extracted extraordinary fees at the expense of the website publishers who make the open internet vibrant and valuable,” government lawyers wrote in court papers. “As publishers generate less money from selling their advertising inventory, publishers are pushed to put more ads on their websites, to put more content behind costly paywalls, or to cease business altogether.”

Google disputes that it charges excessive fees compared to its competitors. The company also asserts the integration of its technology on the buy side, sell side and in the middle assures ads and web pages load quickly and enhance security. And it says customers have options to work with outside ad exchanges.

Google says the government's case is improperly focused on display ads and banner ads that load on web pages accessed through a desktop computer and fails to take into account consumers' migration to mobile apps and the boom in ads placed on social media sites over the last 15 years.

The government's case “focuses on a limited type of advertising viewed on a narrow subset of websites when user attention migrated elsewhere years ago,” Google's lawyers wrote in a pretrial filing. “The last year users spent more time accessing websites on the ‘open web,’ rather than on social media, videos, or apps, was 2012.”

The trial, which is expected to last several weeks, is taking place in a courthouse that rigidly adheres to traditional practices, including a resistance to technology in the courtroom. Cellphones are banned from the courthouse, to the chagrin of a tech press corps accustomed at the District of Columbia trial to tweeting out live updates as they happen.

Even the lawyers, and there are many on both sides, are limited in their technology. At a pretrial hearing Wednesday, Google's lawyers made a plea for more than the two computers each side is permitted to have in the courtroom during trial. Brinkema rejected it.

“This is an old-fashioned courtroom,” she said.



Google, Meta, TikTok Hit by EU Consumer Complaints about Handling of Financial Scams

FILE PHOTO: The logo of Meta is seen during the Viva Technology conference dedicated to innovation and startups at Porte de Versailles exhibition center in Paris, France, June 12, 2025. REUTERS/Benoit Tessier/File Photo
FILE PHOTO: The logo of Meta is seen during the Viva Technology conference dedicated to innovation and startups at Porte de Versailles exhibition center in Paris, France, June 12, 2025. REUTERS/Benoit Tessier/File Photo
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Google, Meta, TikTok Hit by EU Consumer Complaints about Handling of Financial Scams

FILE PHOTO: The logo of Meta is seen during the Viva Technology conference dedicated to innovation and startups at Porte de Versailles exhibition center in Paris, France, June 12, 2025. REUTERS/Benoit Tessier/File Photo
FILE PHOTO: The logo of Meta is seen during the Viva Technology conference dedicated to innovation and startups at Porte de Versailles exhibition center in Paris, France, June 12, 2025. REUTERS/Benoit Tessier/File Photo

Alphabet's Google, Meta Platforms and TikTok were hit with complaints from European Union consumer groups on Thursday for allegedly failing to protect users from financial scams on their platforms, putting them at risk of regulatory fines.

The move highlights growing pressure worldwide on Big Tech to do more to address the negative impacts of social media, particularly for children and vulnerable users.

The complaints, filed by the European Consumer Organisation (BEUC) and 29 of its members in 27 European countries, were submitted to the European Commission and national regulators under the Digital Services Act, which requires large online platforms to do more to tackle illegal and harmful content, Reuters reported.

"Meta, TikTok and Google not only fail to proactively remove fraudulent ads but also do little when being notified about such scams," BEUC Director General Agustin Reyna said in a statement.

"If they fail to address the financial scams circulating on their platforms, fraudsters will continue to reach millions of European consumers daily, leaving people at risk of losing hundreds to thousands of euros to fraud," he said. Google and Meta rejected the complaints and said they work proactively to protect their users.

A Google spokesperson said: "We strictly enforce our ad policies, blocking over 99% of violating ads before they ever run. Our teams constantly update these defences to stay ahead of scammers and protect people."

Meta said it found and removed over 159 million scam ads last year, 92% before anyone reported them. "We invest in advanced AI, tools, and partnerships to stop them," a spokesperson said.

TikTok said it takes action against violations, adding that scams are an industry-wide challenge while bad actors constantly adapt their tactics.

The consumer groups, meanwhile, said they reported nearly 900 ads suspected of breaching EU laws between December last year and March this year but the platforms only took down 27% of the ads and 52% of the reports were rejected or ignored.

The groups urged regulators to investigate whether the companies were complying with the rules and to impose fines for breaches.

DSA fines can reach as much as 6% of a company's global annual turnover.


SDAIA Outlines Comprehensive Data Quality Journey to Support National AI Initiatives

The Saudi Authority for Data and Artificial Intelligence (SDAIA)
The Saudi Authority for Data and Artificial Intelligence (SDAIA)
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SDAIA Outlines Comprehensive Data Quality Journey to Support National AI Initiatives

The Saudi Authority for Data and Artificial Intelligence (SDAIA)
The Saudi Authority for Data and Artificial Intelligence (SDAIA)

The Saudi Data and Artificial Intelligence Authority (SDAIA) highlighted data quality as a critical foundation for enhancing information reliability, boosting performance, and enabling accurate business decisions, as part of its efforts during the Year of Artificial Intelligence 2026 to raise awareness about data importance.

The authority noted that high data quality serves as the cornerstone for sustainable national trust, integrated digital services, operational savings, entrepreneurship, and readiness for artificial intelligence applications, SPA reported.

SDAIA stated that the data quality journey spans five phases, beginning with a creation phase, where data is entered according to standardized criteria.

This is followed by a storage and organization phase to structure data and eliminate duplication, and an integration and sharing phase, which assesses quality before data is reused.

The journey continues through an analysis and use phase, where report accuracy is tied directly to source quality, and culminates in a continuous improvement phase, which utilizes analysis and user feedback to constantly refine data sets.

SDAIA called on organizations to adopt comprehensive data quality practices and strictly adhere to national regulations and standards. This includes integrated data quality planning, prioritizing initial assessments, developing data rules, and establishing clear performance indicators to measure improvement.

The authority also emphasized the importance of conducting periodic reviews and enabling users to report quality problems, which will ultimately maximize the efficiency of digital services and AI applications across the Kingdom.


Dell to Asharq Al-Awsat: AI in Saudi Arabia Enters Production, Not Experimentation Phase

Mohammed Amin, Senior Vice President for Central Eastern Europe, Middle East, Türkiye and Africa at Dell Technologies
Mohammed Amin, Senior Vice President for Central Eastern Europe, Middle East, Türkiye and Africa at Dell Technologies
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Dell to Asharq Al-Awsat: AI in Saudi Arabia Enters Production, Not Experimentation Phase

Mohammed Amin, Senior Vice President for Central Eastern Europe, Middle East, Türkiye and Africa at Dell Technologies
Mohammed Amin, Senior Vice President for Central Eastern Europe, Middle East, Türkiye and Africa at Dell Technologies

Saudi Arabia became a focal point of discussion in the “Dell Technologies World 2026” in Las Vegas this week about the next phase of artificial intelligence.

The question is no longer just about the size of investment in infrastructure or national capacity building, but about the difference the Kingdom can make in a global market transitioning from AI experimentation to its operational deployment within institutions.

In exclusive remarks to Asharq Al-Awsat, Michael Dell, Chairman and CEO of Dell Technologies, stated that what the company sees in Saudi Arabia is a “deep commitment to modernizing the Kingdom,” highlighting its significant energy resources and Dell's collaboration with Humain and other companies in the Kingdom, in addition to a regional facility through which the company works to “aggregate these capabilities and build infrastructure for customers in the region.”

He added that every country today is going through a phase of re-understanding what the transition towards AI means, and how citizens and industries can be empowered to drive the economy forward. In the same session, Dell described Saudi Vision 2030 as “highly ambitious,” and the ambition for AI under this vision as “impressive.”

The Operation Test

From this point, the real discussion about Saudi Arabia and artificial intelligence begins. The narrative is no longer solely about the volume of investments, the speed of data center construction, or the number of announced national projects.

The challenge of the next test relates to how this national capability can be transformed into operational value within government entities, banks, hospitals, energy and telecommunications companies, and smart cities. It's about how institutions move from AI experiments to systems that operate daily, on real data, within secure environments, and at a predictable cost.

Mohammed Amin, Senior Vice President for Central Eastern Europe, Middle East, Türkiye and Africa at Dell Technologies, places this transformation in a clear context.

In remarks to Asharq Al-Awsat on the sidelines of the conference, he states that the biggest barrier for institutions in Saudi Arabia and the Gulf as they transition from AI experimentation to production is not a single isolated factor, but an interconnected system encompassing infrastructure, governance, skills, cyber resilience, cost, and operating models.

However, he considers “data readiness” to be the primary obstacle. He adds: “Without a reliable and AI-ready data foundation, even the most advanced infrastructure is insufficient, and pilot projects falter before reaching production.”

Mohammed Amin, Senior Vice President for Central Eastern Europe, Middle East, Türkiye and Africa at Dell Technologies

Data Before the Model

This point appears fundamental to Dell's assessment of the Saudi phase, as the company indicates that 96 percent of Saudi institutions now view AI as a key part of their business strategy, according to its research on the state of innovation and AI.

However, this indicator, despite its importance, does not mean that the path to production has become easy. Many institutions still operate through outdated and fragmented systems, distributed data, inconsistent governance, and limited access to reliable real-time data.

According to Amin, the fastest-advancing institutions are those that treat AI “not as a standalone tool, but as a transformation of the entire operating model.”

Here lies the difference between ambition and operational infrastructure. An institution that wants to use AI for customer service, risk management, predictive maintenance, or patient data analysis not only needs a robust model but also requires its data to be discoverable, governed, reliable, and usable by AI systems in a timely manner.

Amin defines AI-ready data as data that is “discoverable, governed, reliable, and usable by AI systems in real-time.” This definition transforms the discussion from a narrow technical question to an institutional one: Does the institution know where its data is, who can use it, and can it be trusted when fed into a model or intelligent agent?

Data from Sensitive Sectors

In the Saudi banking sector, this could mean linking customer, transaction, and risk data across different environments while maintaining compliance and governance. In hospitals, it involves securely organizing clinical and imaging data so that AI can support diagnosis or improve operations without compromising patient privacy. For government entities, it means unifying citizen and operational data while preserving sovereignty and security controls. As for energy companies, it might involve combining operational, sensor, and geographic data to support predictive maintenance and improve performance.

Dell states that updates to its Dell AI Data Platform specifically target this point, by indexing billions of files and linking them into governed data pipelines. The platform includes capabilities such as GPU-accelerated SQL analytics, achieving up to six times faster performance, and vector indexing up to 12 times faster.

These details might seem technical, but they actually determine the speed at which an institution transitions from a limited experiment to a widely operational AI service. The slower data is accessed or the less organized it is, the more the data pipelines themselves become an operational bottleneck. Amin notes that these capabilities help reduce response time, improve accuracy, and expand AI services with higher efficiency.

Local Operating Economics

As AI transitions to more sensitive and continuous workloads, another question emerges: when does private or institution-controlled infrastructure become more suitable than the public cloud? Amin does not present this as a stark choice between cloud and private infrastructure; he believes the public cloud remains important for experimentation, flexibility, and quick access to AI services. However, he adds that there comes a stage where controlled infrastructure becomes “strategically better,” especially when workloads involve sensitive national or financial data, or when response time requirements are critical.

This aligns with what Dell presented at the conference regarding Deskside Agentic AI, a solution aimed at running some AI agents locally on high-performance workstations, rather than relying entirely on cloud programming interfaces.

The company states that this solution can, in some cases, reach a break-even point with the cost of cloud programming interfaces within three months, and reduce spending by up to 87 percent within two years. Amin interprets these figures from a broader perspective, stating that technology managers in Saudi Arabia must evaluate the economics of AI “over its full lifecycle, not just by focusing on initial infrastructure costs.” The cloud might appear attractive at the outset, but it can become more expensive when running continuous generative or agentic workloads at the scale of a large enterprise.

Processor Efficiency

For Saudi Arabia, this issue is also linked to sectors with regulatory and sensitive natures. Amin acknowledges that the most realistic use cases today are those that deliver clear productive and operational value while maintaining manageable governance.

He points out that private assistants within institutions and workflow in regulated sectors represent a compelling starting point in the Kingdom, due to the strong focus on data security and sovereignty. He also believes that programming assistants are rapidly gaining momentum because they offer direct benefits to development teams.

The transition to production requires not only data and architecture but also infrastructure capable of handling high workload density. In heavy AI environments, processing units are insufficient if data does not move quickly between computing, storage, and applications.

Amin notes that the network design in PowerRack includes a switching capacity exceeding 800 terabits per second per rack, explaining that the practical meaning of this capacity is to eliminate data traffic bottlenecks between GPUs, storage, and applications. The longer GPUs wait for data, the lower the efficiency of infrastructure investment. Conversely, when data moves with low latency, training and inference operations become faster and more effective.

Cooling as a Strategic Factor

This discussion cannot be separated from cooling and power, as AI increases rack density and power requirements within data centers, making cooling a strategic, not just operational, factor.

Amin notes that the ability of Dell PowerCool C7000 to support facility water temperatures up to 40 degrees Celsius means that data centers can operate with higher efficiency in hot climates, reducing reliance on energy-intensive cooling.

In Saudi Arabia, where the government and private sector are investing in sovereign AI infrastructure, he believes that cooling “is no longer merely an operational issue,” but has become linked to scalability, energy efficiency, and long-term viability.

Data and Model Security

Cyber resilience is part of AI readiness; an intelligent system is not reliable if its data is corruptible, its models are exploitable, or its infrastructure is not recoverable. Amin points out that an AI system “is only as reliable as the data and models it operates on,” and a cyberattack that corrupts data or harms a model can have significant consequences.

Therefore, he believes that the maturity of cyber resilience will directly impact the extent to which institutions trust expanding their adoption of AI. Here, Dell offers tools like Cyber Detect, which it claims can detect data corruption resulting from ransomware attacks and accurately identify the last known clean version.

Openness and Sovereignty

With Dell's expanded partnerships with Google, Hugging Face, OpenAI, Palantir, ServiceNow, and SpaceXAI, the company emphasizes that institutions do not want to tie their AI strategy to a single model, cloud platform, or infrastructure package.

This openness, in Amin's view, gives institutions a “choice” and reduces vendor lock-in risks, allowing them to develop their capabilities as technology evolves. This is crucial in a fast-moving market like Saudi Arabia, where integration and interoperability can become strategic advantages in themselves.

When Mohamed Amin was asked about the Saudi sectors that would first require AI-ready infrastructure, he placed government, energy, telecommunications, finance, and smart cities at the forefront, due to the volume of their data, their national importance, and the operational value that AI can unlock.

These sectors are also most closely linked to sovereignty, compliance, and security requirements. Therefore, building a secure and scalable AI infrastructure appears not merely a technical upgrade, but part of institutions' ability to transform the Vision's ambitions into measurable daily operations.

Between Michael Dell's response regarding Saudi Arabia and Mohamed Amin's vision for the region, the picture of the next phase becomes clear. The Kingdom is not entering the AI race merely from the perspective of consumption or experimentation, but from the perspective of building institutional capability.

However, true capability will not be measured solely by the number of data centers or the volume of investment, but by institutions' ability to prepare their data, choose where to run their workloads, manage costs, protect their models and data, and scale their use without losing control or governance.