India's e-commerce websites outpace apps as shopping habits evolve: Report

by Hansraj Agrawal | Jul 3, 2026 | Technology

India’s e-commerce story has long been synonymous with mobile apps. From Flipkart‘s “app-only” experiment to Amazon‘s push for lightweight Android apps, the assumption across the industry was simple: the smartphone app would remain the primary gateway to online shopping. Market intelligence firm Sensor Tower’s State of E-commerce 2026 report suggests that assumption is beginning to change.

According to the report, India recorded nearly 58 billion e-commerce website visits over the past 12 months, the highest globally, while website traffic grew 28 per cent year-on-year, ahead of every other major market. At the same time, mobile app downloads have largely plateaued, indicating that future growth may increasingly come from the web rather than new app users.

Why are websites becoming more important for e-commerce

The report suggests consumers are increasingly beginning their shopping journey on the web instead of directly opening shopping apps.

The data reflects this shift. Globally, fashion e-commerce websites recorded 53.7 per cent year-on-year growth in visits, while unique visitors increased 64.3 per cent year-on-year in Q1 2026. By comparison, mobile app downloads for fashion platforms grew just 6.1 per cent, while total time spent on apps declined 5.2 per cent. According to Sensor Tower, this suggests consumers are increasingly using websites for product discovery and research, even though apps remain important for repeat purchases.

Unlike apps, websites are easier to discover through Google Search, creator links, affiliate platforms and social media, allowing brands to reach users before asking them to install an application.

Why is India leading the global shift?

India is not only seeing higher traffic. It is leading the world.

According to the Sensor Tower report, India generated nearly 58 billion e-commerce website visits over the past 12 months, ahead of mature markets such as the US, Japan, Germany and the UK. E-commerce website visits in India also grew 28 per cent year-on-year during the same period, the fastest among major markets. Meanwhile, e-commerce app downloads in India between Q2 CY2025 and Q1 CY2026 grew only 6 per cent.

During Q1 CY2026 alone, India averaged nearly 1.4 billion monthly visits to fashion e-commerce websites, the highest globally.

The report also noted that traffic to India’s fashion e-commerce websites increased 98.3 per cent year-on-year, nearly doubling from a year earlier. Pakistan recorded faster growth at 109.3 per cent, but from a much smaller base, while Brazil and Türkiye grew 51 per cent and 57.8 per cent, respectively.

Similarly, in Q1 CY2026, India led the global beauty e-commerce category in both scale and growth. Average monthly website visits approached 350 million, while traffic surged 116 per cent year-on-year, making India the primary growth engine for the category.

What does this mean for e-commerce companies?

The findings point to a broader strategic shift. Instead of treating websites as secondary storefronts, retailers are increasingly building parallel web and app strategies. This trend is reflected in a case study on Nykaa included in the Sensor Tower report.

According to the case study, Nykaa ranked first globally in both beauty app monthly active users and beauty website unique visitors during Q1 2026. Within India, it also led both categories, ahead of Purplle and Tira. Sensor Tower noted that the company’s website audience and mobile user base have both expanded steadily since 2023, indicating that growth is coming from both channels rather than one replacing the other.

The report also noted that Nykaa crossed 40 million website unique visitors during the November 2025 shopping season while simultaneously recording more than 21 million monthly active users on its mobile app. This suggests retailers are increasingly building complementary web and app ecosystems instead of relying on a single platform.

How is social commerce changing online shopping?

The Nykaa case study also illustrates how customer acquisition is changing.

According to Sensor Tower, referrals from Wishlink to Nykaa’s website increased 58 per cent during Q1 2026, while Instagram referrals rose 25.6 per cent. At the same time, inbound traffic from Amazon declined 11.4 per cent, while traffic flowing from Nykaa to Amazon fell 15.8 per cent.

The report said this indicates consumers are increasingly discovering products through creators, affiliate platforms and social media rather than traditional marketplace searches.

Are shopping apps losing relevance?

The report does not suggest that apps are losing relevance. Instead, it points to a maturing mobile ecosystem alongside a rapidly expanding web channel.

Globally, e-commerce app downloads have largely stabilised after reaching record levels in 2024 and 2025. In Q1 2026, general marketplace app downloads declined 5.3 per cent year-on-year, while time spent remained broadly flat with a 0.4 per cent increase, suggesting users continue to engage deeply with shopping apps even as new user acquisition slows.

At the same time, website unique visitors for general marketplaces increased 10.9 per cent year-on-year, even as total website visits remained broadly unchanged, suggesting more people are visiting these sites at least once, even if each visitor is browsing less frequently than before.

The report also shows that the world’s largest platforms continue to invest across both channels. Amazon remains the largest cross-platform e-commerce platform globally, while Temu ranked second in both mobile monthly active users and website unique visitors. SHEIN, meanwhile, recorded 70 per cent year-on-year growth in website unique visitors, even though its web audience remains smaller than its mobile user base.

The data suggests that the next phase of e-commerce growth is unlikely to be a battle between apps and websites. Instead, retailers will increasingly use websites to attract shoppers and apps to retain them.

How could AI change the future of online shopping?

The report largely reflects how consumers shop today. But the next phase of e-commerce may be shaped as much by AI agents as by people.

Google’s recently announced Gemini Intelligence points in that direction. Rather than simply answering questions, Gemini is being designed to complete multi-step shopping tasks across Android apps. If an app cannot complete the task, Gemini can continue the workflow inside Chrome using its Auto Browse capability, allowing it to compare products, navigate websites, fill forms, add items to shopping carts and complete purchases after user approval.

This suggests that the distinction between apps and websites could become less important for users, but more important for retailers.

An AI agent is unlikely to care whether it is interacting with a native application or a browser. It will simply choose whichever route allows it to complete the task most efficiently.

That could reinforce the hybrid strategy already emerging in Sensor Tower’s data.

Instead of treating websites as secondary channels, retailers may increasingly need to optimise both their app and web experiences so AI systems can discover products, compare prices, access inventory and complete transactions, regardless of where the journey begins.

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EU upholds Google Android fine: Why the ruling matters beyond Europe

by Hansraj Agrawal | Jul 3, 2026 | Technology

More than three billion people use Android smartphones, but few stop to think about the business agreements that determine which apps appear on their devices the moment they switch them on. Those agreements have now become the centre of one of the biggest antitrust battles in the technology industry. After an eight-year legal fight, Europe’s highest court has upheld a €4.1 billion ($4.8 billion) fine against Google, ruling that the company used Android’s dominance to strengthen its position in online search and web browsing.

While the ruling is unlikely to have a significant financial impact on Google, its implications go well beyond the €4.1 billion fine. The judgment strengthens Europe’s push to hold Big Tech accountable and is likely to serve as an important reference point for competition regulators worldwide, including in India. As governments take a closer look at the growing influence of digital platforms, the decision could shape future rules governing mobile operating systems, app stores, digital marketplaces and even AI-powered services.

Here’s a closer look at what the case was about, why the EU ruled against Google, and what the verdict means for consumers, smartphone makers, competitors and India’s evolving digital competition landscape.

What is the case about?

According to Reuters, the dispute dates back to 2018, when the European Commission accused Google of abusing Android’s dominant position in the smartphone market. Android powers the majority of smartphones globally. While Android itself is open source, manufacturers that wanted access to Google’s popular apps, especially the Google Play Store, had to agree to certain conditions.

According to EU regulators, Google imposed three major restrictions:

Phone makers had to pre-install Google Search and Google Chrome if they wanted to include the Play Store.

Manufacturers were discouraged or prevented from selling devices running modified versions of Android, known as Android forks.

Google allegedly made payments to some manufacturers and mobile network operators to exclusively pre-install Google Search.

The Commission argued these practices made it extremely difficult for rival search engines, browsers and app ecosystems to compete, even if consumers technically had the option to download alternatives later. It concluded that Google had used Android to protect its search business rather than allowing fair competition.

Google disagreed, saying Android had increased competition by giving manufacturers a free operating system that allowed them to compete with Apple’s iPhone ecosystem. The company also argued that users could easily install competing apps if they wished.

Why did the EU reject Google’s argument?

The European Union’s courts accepted that Android is open source but said Google’s commercial agreements went beyond simply offering free software.

The judges agreed with regulators that Google’s contracts effectively ensured that most Android phones came with Google Search and Chrome as default options. Since many consumers rarely change default settings, these agreements helped Google preserve its already dominant position in internet search.

The court also said restricting manufacturers from selling devices based on modified Android versions reduced innovation by limiting competing operating systems. In other words, the issue was not Android itself but the business conditions attached to using Google’s ecosystem.

Why is this judgment significant?

After several rounds of appeals, Europe’s highest court dismissed Google’s final challenge, confirming the reduced €4.1 billion fine.

The ruling is one of the strongest examples of governments taking action against the market power of Big Tech. For years, regulators worried that companies such as Google, Apple, Amazon and Meta could use their dominance in one market to gain unfair advantages in another.

The Android case establishes an important principle.

The ruling reinforces the European Union’s long-standing efforts to curb anti-competitive practices by large technology companies. According to Reuters, the Android case is one of several antitrust actions the EU has brought against Google over the past decade, alongside cases involving Google Shopping and AdSense. The decision also comes as the bloc enforces the Digital Markets Act (DMA), which imposes additional obligations on major digital platforms designated as “gatekeepers”.

What changes for Google now?

Although the judgment relates to Google’s past Android business practices, its impact is expected to shape how the company and the wider technology industry operate going forward. The ruling strengthens the European Union’s position that dominant digital platforms cannot use one successful product to unfairly promote another, setting an important precedent for future competition cases.

Some of the key implications include:

Greater scrutiny of Google’s Android agreements: Future licensing agreements between Google and smartphone manufacturers are likely to face closer examination to ensure they do not unfairly favour Google’s own apps and services.

More flexibility for device makers: Smartphone manufacturers could gain greater freedom to customise Android, decide which apps to pre-install, choose default search engines and browsers, and partner with alternative service providers without restrictive contractual conditions.

Bigger opportunity for rivals: Competing search engines, web browsers and app stores may find it easier to secure placement on Android devices, creating a more level playing field and giving consumers greater choice.

Reference point for regulators: The ruling is expected to serve as an important reference for competition authorities investigating similar business practices by large technology companies. It could also influence future regulatory action involving app stores, mobile operating systems, AI services and other digital platforms.

What does this mean for smartphone manufacturers and users?

The ruling could gradually reshape the Android ecosystem by giving smartphone manufacturers greater flexibility while also expanding choices for consumers. Companies such as Samsung, Xiaomi, Oppo, Vivo and Motorola have traditionally relied on Google’s Android ecosystem and licensing agreements, which influenced the apps and services pre-installed on their smartphones.

If similar regulatory principles continue to be enforced, manufacturers could gain more freedom to:

Customise Android with their own user interface and software experience.

Pre-install their own apps and services instead of Google’s by default.

Partner with alternative search engines and browser providers.

Explore competing app stores and software ecosystems, where regulations permit.

For users, the impact is likely to be gradual rather than immediate. Most Android devices will continue to ship with Google’s services because they remain widely used and trusted. However, over time, consumers could benefit from:

More choice during device setup, with users potentially being offered alternative search engines instead of Google by default.

Greater variety in pre-installed apps and browsers, giving smartphone makers more flexibility in the services they offer.

Increased competition among app stores, which could provide users with more options for downloading apps.

More room for innovation, as fewer restrictions could make it easier for rival software providers and developers to reach Android users.

Despite these potential changes, Google’s apps and services are expected to remain a common feature on Android smartphones, as many manufacturers are likely to continue offering them based on consumer demand rather than contractual requirements.

Why does this matter to India?

The EU ruling carries particular significance for India, one of the world’s largest smartphone markets, where Android dominates the mobile ecosystem. According to Counterpoint Research, cited by Reuters, more than 95 per cent of smartphones in India run on Android, making Google’s business practices highly relevant for smartphone manufacturers, app developers and millions of users.

Additionally, the European Union’s findings closely mirror those reached by India’s competition watchdog in 2022. In October that year, the Competition Commission of India (CCI) imposed a Rs 1,337.76 crore penalty on Google after concluding that the company had abused its dominant position across multiple markets in the Android mobile device ecosystem.

The CCI found that Google’s licensing agreements, including the Mobile Application Distribution Agreement (MADA), Anti-Fragmentation Agreement (AFA), Android Compatibility Commitment (ACC) and Revenue Sharing Agreements (RSA), ensured that Google Search, Chrome and other Google services were pre-installed and prominently placed on Android devices. According to the regulator, these agreements gave Google a significant competitive advantage while limiting market access for rival search services, web browsers and other digital platforms.

The CCI found that manufacturers seeking to license the Google Play Store were required to pre-install Google’s entire Google Mobile Services (GMS) suite, including Search, Chrome, YouTube, Maps and Gmail. The Commission held that this mandatory bundling imposed unfair conditions on device manufacturers and denied rival apps comparable market access. It also criticised Google’s anti-fragmentation agreements, saying they restricted manufacturers from developing or selling devices based on Android forks, limiting technical development and consumer choice.

A key finding of the CCI, which closely mirrors the EU ruling, was that Google’s licensing agreements helped protect and strengthen its dominant position in online search. According to the regulator, the agreements ensured a continuous flow of search queries to Google, supporting its advertising business while limiting opportunities for competing search services.

To restore competition, the CCI directed Google to delink Play Store licensing from the mandatory installation of its apps, stop imposing anti-fragmentation obligations, allow manufacturers greater freedom over app pre-installation and placement, let users choose their default search engine during device setup, and permit alternative app stores and sideloading.

What other antitrust actions has India taken?

India has stepped up scrutiny of large technology companies in recent years, with the Competition Commission of India taking action against several digital platforms over alleged anti-competitive practices.

Google Play Billing case (2022): In a separate order, the CCI fined Google Rs 936.44 crore for abusing its dominant position through the Google Play Store’s billing policies. The Commission held that Google’s requirement for developers to use its billing system was unfair and directed the company to allow greater flexibility in payment options.

Google Smart TV case (2021): The CCI ordered an investigation into Google’s agreements with smart TV manufacturers over the licensing of the Android TV operating system, alleging that the arrangements could restrict competition. Google later offered commitments, which the CCI accepted in 2025, bringing the case to a close.

Digital Competition Bill: Beyond individual cases, India is considering a Digital Competition Bill that would regulate large digital platforms designated as “systemically significant digital enterprises”. Inspired in part by the EU’s Digital Markets Act, the proposed law aims to prevent anti-competitive conduct before it harms the market rather than relying solely on lengthy investigations after violations occur.

What’s next?

The case represents a shift in how governments view digital competition. Instead of accepting that technology giants naturally dominate markets, regulators are increasingly asking whether that dominance is being reinforced through unfair business practices.

For consumers, the immediate impact may be limited. Most people will continue using Android devices much as they do today. But over time, the ruling could lead to greater choice, more innovation and increased opportunities for competing apps and services.

For Google, the company still commands enormous influence in mobile software. Yet the judgment signals that regulators are no longer willing to overlook practices that make it harder for rivals to compete. And for countries such as India, where digital markets are expanding rapidly, the case offers another important legal precedent as policymakers shape the next generation of competition rules for the technology industry.

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Proprietary and open-weight AI are emerging as two competing approaches to artificial intelligence. Understand how they differ in technology, deployment, costs, business models and enterprise adoption.

by Hansraj Agrawal | Jul 3, 2026 | Technology

In an artificial intelligence (AI)-driven economy, the key question is how firms build systems that are safe, compliant, scalable and, above all, cost-effective.

Recently, US-based AI software firm Palantir’s chief executive, Alex Karp, criticised the token-based pricing model used by OpenAI and Anthropic, arguing that enterprises are being pushed towards expensive AI usage. His comments reflect a growing concern that the cost of using frontier AI models can rise rapidly as usage scales, particularly for organisations deploying AI across large teams and high-volume workflows.

That debate reflects a broader split in the AI industry. Some companies, including OpenAI, Google and Anthropic, keep their most advanced models proprietary and sell access through application programming interfaces (APIs) and subscriptions. Others, such as DeepSeek and Alibaba, are releasing powerful open-weight models that businesses can download, customise and deploy on their own infrastructure.

The divide is reshaping enterprise AI adoption, software development and future technology spending. It is becoming increasingly significant as the performance gap between leading AI models narrows.

As Stanford University’s AI Index Report 2026 notes: “At the technical frontier, leading models are now nearly indistinguishable from one another. Open-weight models are more competitive than ever.”

What separates proprietary AI from open-weight AI?

The debate between proprietary and open-weight AI is both philosophical and commercial. It centres on who controls the underlying technology and how widely it should be made available.

Proprietary, or closed, AI refers to models whose internal workings, model weights and training processes remain under the control of the developer. Users typically interact with these systems through APIs, chatbots or enterprise software, while the provider manages the infrastructure, updates and feature releases.

Companies such as Anthropic follow this model, while OpenAI and Google are primarily associated with proprietary systems, even though both have also released some open-weight models. In many cases, usage is billed on a token basis, meaning customers pay according to the amount of text processed or generated.

Open-weight AI takes a different approach. Developers publicly release the trained model weights — the numerical parameters that determine how an AI model generates responses — allowing organisations to download and run the models independently. Although these models are often described as “open source”, the term is frequently used loosely.

Many prominent models, including those from DeepSeek and Alibaba, provide access to model weights without releasing the complete training data, source code or datasets required to recreate the model from scratch. As a result, they are more accurately described as open-weight rather than fully open-source AI.

The distinction matters because it determines who retains control after a model is released. Proprietary AI leaves ongoing control with the developer. Fully open-source AI makes the code, weights and training materials broadly available. Open-weight AI sits somewhere in between, releasing the model weights but not necessarily the source code or training data, allowing organisations to adapt models within the terms of the licence.

How do the two approaches work?

The differences between proprietary and open-weight AI become clearer when viewed through how organisations deploy them.

With proprietary AI, the model typically runs on infrastructure operated by the provider. Customers send requests through APIs or web-based interfaces, with computation performed in remote data centres. The provider controls software updates, performance improvements, security patches and access to new capabilities. Customers generally have limited ability to modify the underlying model beyond configuration options or prompt engineering.

Open-weight AI allows organisations to download the trained model weights and deploy them on their own servers, private cloud environments or third-party cloud infrastructure. Because the model weights are available, organisations can operate the model independently.

This also gives organisations greater flexibility. They can fine-tune models using their own data, optimise them for specific industries or workflows, decide when to install updates, and integrate them more deeply into existing software environments. Instead of paying continuously for every AI request, the primary cost shifts to computing infrastructure, including graphics processing units (GPUs), storage and system management.

The result is a different operating model. Proprietary AI functions primarily as a cloud-based service, while open-weight AI increasingly resembles enterprise software that organisations deploy and manage themselves.

How do the business models differ?

The technical differences underpin two contrasting approaches to monetisation.

For providers of proprietary AI, the model itself is the commercial product. Revenue is generated through API consumption, premium chatbot subscriptions, enterprise licensing agreements and access to advanced capabilities. As customer usage increases, recurring revenue generally rises in parallel because organisations continue paying for every interaction with the model.

The open-weight ecosystem follows a different commercial logic. While the model itself may be released free of charge or under an open licence, companies generate revenue from the surrounding services rather than the model alone.

These include managed cloud hosting, enterprise deployment services, technical support, model fine-tuning, security features and software tools that simplify implementation. Cloud providers also benefit from increased demand for computing resources, while hardware companies supplying GPUs and AI accelerators stand to gain as more organisations choose to operate models themselves.

In this ecosystem, value shifts away from ownership of the model towards the infrastructure, software and services that enable organisations to deploy AI at scale. The model becomes a foundation on which businesses build commercial offerings rather than the sole product being sold.

Why are enterprises paying attention to open-weight AI?

If proprietary models are perceived to have an advantage, the competitive landscape is narrowing, according to Stanford University’s AI Index Report 2026.

The report found that the US-China AI model performance gap has effectively closed, with US and Chinese models trading the lead multiple times since early 2025. In February 2025, DeepSeek-R1 briefly matched the top US model, and by March 2026, Anthropic’s leading model held a margin of just 2.7 per cent. The report also noted that while the US still produces more top-tier AI models and higher-impact patents, China leads in publication volume, citations, patent output and industrial robot installations.

The emergence of increasingly capable open-weight models is prompting organisations to reassess how they deploy AI.

One of the principal attractions is long-term cost efficiency. For organisations processing millions of AI requests, operating a model on dedicated infrastructure can become more economical than paying recurring API charges. The economics depend on workload size and infrastructure utilisation, but the potential savings become increasingly significant at scale.

Data governance is another consideration. Running AI models internally also gives organisations greater control over proprietary information, an important factor for sectors such as finance, healthcare and government, where regulatory requirements and confidentiality obligations are stringent.

Open-weight models also offer greater opportunities for customisation. Businesses can fine-tune models for industry-specific terminology, internal knowledge bases and specialised workflows that may not be adequately supported by general-purpose proprietary systems. Because organisations control deployment, these models can often be integrated more closely with existing enterprise software and operational processes.

At the same time, adopting open-weight AI introduces new responsibilities. Organisations must manage infrastructure, cybersecurity, software updates and model maintenance. They also require engineering expertise to deploy, optimise and monitor these systems effectively. For many businesses, the additional operational complexity may offset some of the financial benefits.

Even so, proprietary AI retains important advantages. Providers generally deliver the latest capabilities first, manage infrastructure and security, offer integrated developer tools and enterprise support, and continuously improve their models without requiring customers to maintain them. For organisations seeking a plug-and-play solution, these advantages can outweigh the higher operating costs.

Why does proprietary AI still lead?

Despite growing interest in open-weight models, proprietary AI continues to dominate many of the industry’s most demanding applications.

That leadership, however, is becoming less clear-cut. Stanford University’s AI Index Report 2026 notes that leading frontier models are now “nearly indistinguishable” across many technical evaluations, with open-weight models becoming increasingly competitive.

The report also cautions that measuring progress is becoming more difficult. Many established AI benchmarks are approaching saturation, frontier developers are publishing fewer technical details, and independent testing does not always corroborate performance claims made by model developers. As a result, competitive advantage is increasingly determined not only by benchmark scores, but also by deployment options, ecosystem maturity, developer tools and total cost of ownership.

What could this battle mean for AI’s future?

The competition between proprietary and open-weight AI is unlikely to produce a single winner. Instead, the industry may evolve much as previous computing platforms have, with multiple business models coexisting.

Comparable patterns have emerged before. Microsoft’s Windows and Linux developed distinct ecosystems for different user groups. Apple’s iOS and Google’s Android adopted contrasting approaches to software control and openness. Cloud computing also evolved into a mix of fully managed services and self-managed infrastructure, allowing organisations to choose the model that best suited their requirements.

Artificial intelligence appears to be following a similar trajectory. Consumers may continue to favour proprietary AI assistants that offer ease of use, integrated experiences and continual feature updates. Enterprises, meanwhile, are likely to adopt a broader mix of proprietary and open-weight models depending on their requirements for cost, customisation, security and regulatory compliance.

Ultimately, the industry’s defining competition may not be over which company builds the most capable AI model. It may instead be over which approach to ownership, deployment and monetisation becomes the dominant foundation for the next generation of computing. Rather than replacing one another, proprietary and open-weight AI are likely to coexist, serving different needs across an increasingly diverse AI ecosystem.

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Mukesh Ambani, Mittals join global AI panel led by ITU, Salesforce

by Hansraj Agrawal | Jul 3, 2026 | Technology

Mukesh Ambani, chairman and managing director of Reliance Industries, and telecom magnate Sunil Bharti Mittal are among four Indian business leaders named founding members of the newly launched AI for Good Global Commission, a high-level international initiative formed to expand access to artificial intelligence (AI).

The commission was announced on Thursday by Rwanda President Paul Kagame, Salesforce Chair and Chief Executive Officer Marc Benioff, and International Telecommunication Union (ITU) Secretary-General Doreen Bogdan-Martin.

It brings together more than 40 leaders from governments, businesses, and international organisations.

The Indian representatives on the founding panel also include Lakshmi N Mittal, executive chairman, ArcelorMittal, and Vishal Talwar, president of FedEx Dataworks and executive vice-president, chief digital and information officer at FedEx Corporation.

Other members include Nvidia founder and chief executive Jensen Huang, Microsoft vice-chair and president Brad Smith, Amazon president and chief executive Andy Jassy, Qualcomm chief executive Cristiano Amon, Pfizer chairman and chief executive Albert Bourla, and Google and Alphabet executive James Manyika.

According to the announcement, the commission seeks to bring together leaders involved in building AI technologies, deploying them at scale, shaping policy, and representing communities to develop responsible AI solutions across sectors and geographies, while ensuring participation from developing countries.

“One thing is certain: technology is supposed to be a force for good, and we have a responsibility to use it accordingly,” Kagame, who will serve as co-chair of the commission, said in a statement. “Let us work together to reduce inequality, and allow more and more of our citizens to benefit from the good AI can deliver to all of us.”

Benioff said the opportunities created by AI must be supported by trust. “The promise of AI is built on not only incredible opportunities for the growth of our economy, but on the foundation of trust that is required for our shared success,” he said.

The organisers said a key focus of the commission will be addressing digital divides, citing that 2.2 billion people remain offline globally and are unable to access AI-driven advancements.

Bogdan-Martin, who will serve as vice-chair, said broad collaboration would be necessary to ensure the technology benefits people worldwide.

“No organization can single-handedly put AI at the service of all humanity,” she said, adding, “It will take collective leadership and the combined expertise of partners from across sectors to ensure AI benefits all people, everywhere.”

The AI for Good Global Commission builds on the work of the ITU-UNESCO Broadband Commission for Sustainable Development. Its inaugural meeting is scheduled to take place during the AI for Good Global Summit 2026 in Geneva from July 7 to July 10.

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AI agent tech progressing slower than expected, says Mark Zuckerberg

by Hansraj Agrawal | Jul 3, 2026 | Technology

Meta Chief Executive Mark Zuckerberg acknowledged shortcomings in the company’s sweeping restructuring at an internal town hall on Thursday, saying the systems known as AI agents had not progressed as quickly as he had expected, according to a recording heard by Reuters.

Zuckerberg added that a company reorganization ‌that included major job cuts was not as “clean” as it could have been and that executives had miscalculated on the timing of the changes.

Zuckerberg and other Meta executives have been seeking to moderate some of the organizational changes introduced earlier this year, without fundamentally changing course. The company laid off about 10% of its global workforce and reassigned roughly 7,000 employees to AI-focused teams in May, moves that prompted employee pushback and raised concerns about morale.

The changes were part of a broader restructuring aimed at funding costly investments in artificial intelligence infrastructure and positioning Meta to capitalize on efficiency gains from AI-assisted work. Zuckerberg told employees in May that he did not expect further companywide layoffs this year, though some workers were skeptical.

In retrospect, he said, the “trajectory of the agentic development over at least the last ‌four months hasn’t really accelerated in the way that we expected,” and that the company’s bets on the new structure “haven’t come to fruition yet.” Zuckerberg was referring to AI agents, automated systems that can execute tasks on behalf of a user.

Conversations he was having “with our top people” when they started planning the restructuring in January and February “were that they were worried that we weren’t going to move fast enough to adapt,” ‌Zuckerberg said.

At the time, he said, executives were “super optimistic” about tools like Claude Code from AI startup Anthropic.

Meta is ‌projected to spend as much as $145 billion on AI infrastructure this year, a significant portion of Big Tech’s more than $700 billion outlay ‌on ??the technology.

Zuckerberg said he expects that the social media giant will begin to experience more significant benefits from its AI investments within the next three to six months.

A Meta spokesperson declined to comment on Thursday.

MOUSE-TRACKING SOFTWARE REVIEW

In the same town hall, Meta’s chief technology officer, Andrew Bosworth, said a review of a recent data security incident with the company’s controversial mouse-tracking software indicated that no employee data was included in AI training. Last month, Meta paused the program, which tracks employee mouse movements and digital activity for AI training, while investigating the exposure of sensitive ‌data.

If the company turns the program back on once the review is completed, it will be on an “opt-in” basis, he said.

“For people ‌who are comfortable, that’s great, they can contribute to this kind of great human survey. To people who are not, it is not an issue,” he told employees at the town hall on Thursday.

When Meta first installed the program on U.S. employees’ computers in April, Bosworth told them there was no way to opt out.

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Sony to end PlayStation game discs from 2028, shifts fully to digital

by Hansraj Agrawal | Jul 2, 2026 | Technology

Sony Group Corp. will end production of physical discs for its PlayStation video-game consoles starting in January 2028, going all in on a digital approach that will require consumers to download titles from the company’s online storefront moving forward.

“This is a natural direction for Sony Interactive Entertainment to adapt to consumer trends as the general preference for digital media significantly outpaces physical discs,” the company wrote in a blog post on Wednesday. “This transition will enable us to align more closely with how most of our community prefers to access and play games today.”

The transition will have no impact on games scheduled for release before early 2028, which will still be released on disc, Sony said.

In making this move, the Japanese company becomes the first major console maker to fully abandon physical media. Both Sony and Microsoft Corp. have released less expensive digital-only versions of recent consoles that don’t accept discs, but their primary hardware has continued to accept physical games and Blu-ray media.

Sony said “consumer preferences and the broader entertainment industry continue to shift away from physical discs to digital.” But the announcement immediately drew the furor of gamers on social media, some of whom have spent decades amassing a prized collection of titles across numerous systems. Now, they’ll have no choice but to make the switch to a digital library on Sony’s hardware.

In a separate post on Wednesday, Sony announced the pending closing of its digital stores for the legacy PlayStation 3 console and Vita gaming handheld device.

“PS3 and PS Vita represent an important era in our PlayStation history, so this was not an easy decision for us to make,” the company said, adding that both products are no longer able to keep up with the latest e-commerce systems and payment processing standards.

But that news played directly into the concerns of physical game collectors, showing that digital support will only remain in place for as long as a manufacturer decides. The PS3 was released in 2006, with the Vita following in 2011.

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