The web is shifting from human-readable pages to machine-mediated experiences with AI impacting the future of the open web. What comes next may be less open—but potentially more useful.

TL;DR — What You Need To Know

• AI is reshaping web navigation: Google’s AI Overviews and similar tools provide direct answers, reducing the need to visit individual websites.
• Agentic AI is on the rise: Autonomous AI agents are beginning to perform tasks like browsing, shopping, and content creation on behalf of users.
• Monetisation models are evolving: Traditional ad-based revenue is declining, with microtransactions and stablecoins emerging as alternative monetisation methods.
• The open web faces challenges: The shift towards AI-driven interactions threatens the traditional open web model, raising concerns about content diversity and accessibility.

The Rise of Agentic AI

The traditional web, characterised by human users navigating through hyperlinks and search results, is undergoing a transformation. AI-driven tools like Google’s AI Overviews now provide synthesised answers directly on the search page, reducing the need for users to click through to individual websites.

This shift is further amplified by the emergence of agentic AI—autonomous agents capable of performing tasks such as browsing, shopping, and content creation without direct human intervention. For instance, Opera’s new AI browser, Opera Neon, can automate internet tasks using contextual awareness and AI agents.

These developments suggest a future where AI agents act as intermediaries between users and the web, fundamentally altering how information is accessed and consumed.

Monetisation in the AI Era

The traditional ad-based revenue model that supported much of the open web is under threat. As AI tools provide direct answers, traffic to individual websites declines, impacting advertising revenues.

In response, new monetisation strategies are emerging. Microtransactions facilitated by stablecoins offer a way for users to pay small amounts for content or services, enabling creators to earn revenue directly from consumers. Platforms like AiTube are integrating blockchain-based payments, allowing creators to receive earnings through stablecoins across multiple protocols.

This model not only provides a potential revenue stream for content creators but also aligns with the agentic web’s emphasis on seamless, automated interactions.

The Future of the Open Web

The open web, once a bastion of free and diverse information, is facing significant challenges. The rise of AI-driven tools and platforms threatens to centralise information access, potentially reducing the diversity of content and perspectives available to users.

However, efforts are underway to preserve the open web’s principles. Initiatives like Microsoft’s NLWeb aim to create open standards that allow AI agents to access and interact with web content in a way that maintains openness and interoperability.

The future of the web may depend on balancing the efficiency and convenience of AI-driven tools with the need to maintain a diverse and accessible information ecosystem.

What Do YOU Think?

As AI impacts the future of the open web, we must consider how to preserve the values of openness, diversity, and accessibility. How can we ensure that the web remains a space for all voices, even as AI agents become the primary means of navigation and interaction?

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OpenAI’s next model isn’t chasing headlines—it’s building a smoother, smarter user experience with fewer interruptions the launch of GPT-5 unified tools.

TL;DR — What You Need To Know

• GPT-5 aims to unify OpenAI’s tools, reducing the need for switching between models
• The Operator screen agent is due for an upgrade, with a push towards becoming a desktop-level assistant
• Token usage continues to rise, suggesting growing AI utility and infrastructure demand
• Benchmarks are losing their relevance, with real-world use cases taking centre stage
• OpenAI believes AI won’t replace humans but may reshape human labour roles

A more cohesive AI experience, not a leap forward

While GPT-4 dazzled with its capabilities, GPT-5 appears to be a quieter force, according to OpenAI’s VP of Research, Jerry Tworek. Speaking during a recent Reddit Q&A with the Codex team, Tworek described the new model as a unifier—not a disruptor.

“We just want to make everything our models can currently do better and with less model switching,” Tworek said. That means streamlining the experience so users aren’t constantly toggling between tools like Codex, Operator, Deep Research and memory functions.

For OpenAI, the future lies in integration over invention. Instead of introducing radically new features, GPT-5 focuses on making the existing stack work together more fluidly. This approach marks a clear departure from the hype-heavy rollouts often associated with new model versions.

Operator: from browser control to desktop companion

One of the most interesting pieces in this puzzle is Operator, OpenAI’s still-experimental screen agent. Currently capable of basic browser navigation, it’s more novelty than necessity. But that may soon change.

An update to Operator is expected “soon,” with Tworek hinting it could evolve into a “very useful tool.” The goal? A kind of AI assistant that handles your screen like a power user, automating online tasks without constantly needing user prompts.

The update is part of a broader push to make AI tools feel like one system, rather than a toolkit you have to learn to assemble. That shift could make screen agents like Operator truly indispensable—especially in Asia, where mobile-first behaviour and app fragmentation often define the user journey.

Integration efforts hit reality checks

Originally, OpenAI promised that GPT-5 would merge the GPT and “o” model series into a single omnipotent system. But as with many grand plans in AI, the reality was less elegant.

In April, CEO Sam Altman admitted the challenge: full integration proved more complex than expected. Instead, the company released o3 and o4-mini as standalone models, tailored for reasoning.

Tworek confirmed that the vision of reduced model switching is still alive—but not at the cost of model performance. Users will still see multiple models under the hood; they just might not have to choose between them manually.

Tokens and the long road ahead

If you think the token boom is a temporary blip, think again. Tworek addressed a user scenario where AI assistants might one day process 100 tokens per second continuously, reading sensors, analysing messages, and more.

This perspective reflects a strategic bet on infrastructure. OpenAI isn’t just building smarter models; it’s betting on broader usage. Token usage becomes a proxy for economic value—and infrastructure expansion the necessary backbone.

Goodbye benchmarks, hello real work

When asked to compare GPT with rivals like Claude or Gemini, Tworek took a deliberately contrarian stance. Benchmarks, he suggested, are increasingly irrelevant.

Instead, OpenAI is doubling down on real-world tasks as the truest test of model performance. The company’s ambition? To eliminate model choice altogether. “Our goal is to resolve this decision paralysis by making the best one.”

The human at the helm

Despite AI’s growing power, Tworek offered a thoughtful reminder: some jobs will always need humans. While roles will evolve, the need for oversight won’t go away.

For Asia’s fast-modernising economies, that might be a signal to double down on education, critical thinking, and human-centred design. The jobs of tomorrow may be less about doing, and more about directing.

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As Apple courts Alibaba for its iPhone AI partnership in China, U.S. lawmakers see more than just a tech deal taking shape.

TL;DR — What You Need To Know

• Apple has reportedly selected Alibaba’s Qwen AI model to power its iPhone features in China
• U.S. lawmakers and security officials are alarmed over data access and strategic implications
• The deal has not been officially confirmed by Apple, but Alibaba’s chairman has acknowledged it
• China remains a critical market for Apple amid declining iPhone sales
• The partnership highlights the growing difficulty of operating across rival tech spheres

Apple Intelligence meets the Great Firewall

Apple’s strategic pivot to partner with Chinese tech giant Alibaba for delivering AI services in China has triggered intense scrutiny in Washington. The collaboration, necessitated by China’s blocking of OpenAI services, raises profound questions about data security, technological sovereignty, and the intensifying tech rivalry between the United States and China. As Apple navigates declining iPhone sales in the crucial Chinese market, this partnership underscores the increasing difficulty for multinational tech companies to operate seamlessly across divergent technological and regulatory environments.

Apple Intelligence Meets Chinese Regulations

When Apple unveiled its ambitious “Apple Intelligence” system in June, it marked the company’s most significant push into AI-enhanced services. For Western markets, Apple seamlessly integrated OpenAI’s ChatGPT as a cornerstone partner for English-language capabilities. However, this implementation strategy hit an immediate roadblock in China, where OpenAI’s services remain effectively banned under the country’s stringent digital regulations.

Faced with this market-specific challenge, Apple initiated discussions with several Chinese AI leaders to identify a compliant local partner capable of delivering comparable functionality to Chinese consumers. The shortlist reportedly included major players in China’s burgeoning AI sector:

• Baidu, known for its Ernie Bot AI system
• DeepSeek, an emerging player in foundation models
• Tencent, the social media and gaming powerhouse
• Alibaba, whose open-source Qwen model has gained significant attention

While Apple has maintained its characteristic silence regarding partnership details, recent developments strongly suggest that Alibaba’s Qwen model has emerged as the chosen solution. The arrangement was seemingly confirmed when Alibaba’s chairman made an unplanned reference to the collaboration during a public appearance.

Washington’s Mounting Concerns

The revelation of Apple’s China-specific AI strategy has elicited swift and pronounced reactions from U.S. policymakers. Members of the House Select Committee on China have raised alarms about the potential implications, with some reports indicating that White House officials have directly engaged with Apple executives on the matter.

Representative Raja Krishnamoorthi of the House Intelligence Committee didn’t mince words, describing the development as “extremely disturbing.” His reaction encapsulates broader concerns about American technological advantages potentially benefiting Chinese competitors through such partnerships.

Greg Allen, Director of the Wadhwani A.I. Centre at CSIS, framed the situation in competitive terms:

The concerns expressed by Washington officials and security experts include:

1. Data Sovereignty Issues: Questions about where and how user data from AI interactions would be stored, processed, and potentially accessed
2. Model Training Advantages: Concerns that the vast user interactions from Apple devices could help improve Alibaba’s foundational AI models
3. National Security Implications: Worries about whether sensitive information could inadvertently flow through Chinese servers
4. Regulatory Compliance: Questions about how Apple will navigate China’s content restrictions and censorship requirements

In response to these growing concerns, U.S. agencies are reportedly discussing whether to place Alibaba and other Chinese AI companies on a restricted entity list. Such a designation would formally limit collaboration between American and Chinese AI firms, potentially derailing arrangements like Apple’s reported partnership.

Commercial Necessities vs. Strategic Considerations

Apple’s motivation for pursuing a China-specific AI solution is straightforward from a business perspective. China remains one of the company’s largest and most important markets, despite recent challenges. Earlier this spring, iPhone sales in China declined by 24% year over year, highlighting the company’s vulnerability in this critical market.

Without a viable AI strategy for Chinese users, Apple risks further erosion of its market position at precisely the moment when AI features are becoming central to consumer technology choices. Chinese competitors like Huawei have already launched their own AI-enhanced smartphones, increasing pressure on Apple to respond.

The situation is further complicated by China’s own regulatory environment, which requires foreign technology companies to comply with data localisation rules and content restrictions. These requirements effectively necessitate some form of local partnership for AI services.

A Blueprint for the Decoupled Future?

Whether Apple’s partnership with Alibaba proceeds as reported or undergoes modifications in response to political pressure, the episode provides a revealing glimpse into the fragmenting global technology landscape.

As digital ecosystems increasingly align with geopolitical boundaries, multinational technology firms face increasingly complex strategic decisions:

• Regionalised Technology Stacks: Companies may need to develop and maintain separate technological implementations for different markets
• Partnership Dilemmas: Collaborations beneficial in one market may create political liabilities in others
• Regulatory Navigation: Operating across divergent regulatory environments requires sophisticated compliance strategies
• Resource Allocation: Developing market-specific solutions increases costs and complexity

Looking Forward

For now, Apple Intelligence has no confirmed launch date for the Chinese market. However, with new iPhone models traditionally released in autumn, Apple faces mounting time pressure to finalise its AI strategy.

The company’s eventual approach could signal broader trends in how global technology firms navigate an increasingly bifurcated digital landscape. Will companies maintain unified global platforms with minimal adaptations, or will we see the emergence of fundamentally different technological experiences across major markets?

As this situation evolves, it highlights a critical reality for the technology sector: in an era of intensifying great power competition, even seemingly routine business decisions can quickly acquire strategic significance.

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