Artificial intelligence Archives | Page 6 of 659

Study says AI is rewiring global trade and reshaping economic power

A new Allianz Research report argues that AI is transforming global trade, supply chains, digital infrastructure, and geopolitical influence.

The report says AI growth increasingly depends on global semiconductor production, cloud infrastructure, hyperscale data centres, and cross-border digital services. It also argues that trade is increasingly shaped by who controls AI infrastructure, data flows, and cloud capacity.

Allianz Research says exports of AI-enabling goods rose from USD 1 trillion in 2014 to USD 3.8 trillion in 2025, accounting for 15% of global trade and far outpacing overall goods trade growth. Asia dominates the supply side, accounting for 65% of global AI-related exports and seven of the top ten exporters, led by China, Taiwan, and Hong Kong.

The report also highlights the United States’ role as a centre of hyperscale AI infrastructure. It says the US has tripled its AI-related imports since 2023 and is home to 5,427 operational data centres, equivalent to 45% of the global total.

Europe faces a different challenge. According to Allianz Research, the region has less than 10GW of operational data-centre capacity, compared with 60GW in the US, while US hyperscalers already control 35% of European computing capacity and are consolidating a 70% share of the cloud market. The report points to fragmented regulation, complex permitting processes, grid connection delays, limited funding, and the absence of a domestic hyperscaler as factors that reinforce European dependence.

The study also warns that AI diffusion could widen EU-US service imbalances by requiring recurring payments to American AI providers and cloud platforms. In a high-adoption scenario, annual payments by eurozone users to US AI services providers could rise from EUR 2.7 billion to EUR 34 billion, according to the report.

Allianz Research concludes that AI governance, industrial policy, export restrictions, subsidies, and digital trade regulation are becoming central components of global economic competition. Governments are increasingly treating semiconductors, cloud infrastructure, data centres, and AI services as strategic assets linked to national security, economic resilience, and geopolitical influence.

Why does it matter?

The report frames AI as a trade and industrial policy issue, not only a technology story. Its findings suggest that control over semiconductors, cloud infrastructure, data centres, and AI services could shape which economies capture AI-driven productivity gains and which become more dependent on foreign platforms, supply chains, and infrastructure. For Europe, the key concern is a possible double dependence on US cloud and AI services and Asian hardware supply chains.

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WhatsApp introduces private AI chat mode for Meta AI conversations

WhatsApp has introduced a new private mode for conversations with Meta AI that limits storage and retention of chat data. According to Meta, conversations are designed to disappear after chats end and are not stored on company servers.

WhatsApp head Will Cathcart said the feature responds to user demand for more private AI interactions involving sensitive topics. Meta CEO Mark Zuckerberg described the feature as an AI product designed without persistent server-side conversation logs.

Professor Alan Woodward of the University of Surrey reportedly raised concerns about how disappearing conversations could affect accountability and investigations into harmful AI interactions. According to reports, critics argued that limited data retention could complicate review processes in cases involving harm or misuse.

Meta stated that the feature will initially support text-based interactions and include safeguards intended to block harmful or illegal requests. The announcement comes amid Meta’s broader expansion of AI-related products and infrastructure investments.

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Google says AI Mode surpasses one billion monthly users

Google said its AI Mode feature has surpassed one billion monthly active users globally. The figures were published in a company blog post marking one year since the feature’s launch.

According to Google, AI Mode query volumes have more than doubled each quarter since launch. Google described AI Mode as combining traditional search functions with conversational AI interactions.

The company also reported increasing use of voice and image-based search features in the United States. Google said image-based searches and planning-related AI Mode queries have grown significantly in recent months.

The company also highlighted growth in exploratory and idea-oriented search queries. The update was released ahead of Google I/O 2026 and reflects Google’s broader focus on AI-integrated search experiences.

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Taiwan says power supply ready for AI growth

Taiwan’s Ministry of Economic Affairs said the country is prepared to meet increasing electricity demand linked to the AI data centre expansion. The comments followed remarks by Nvidia CEO Jensen Huang regarding the growing energy requirements of AI infrastructure development. Huang stated that sufficient power availability would be important for continued AI-related economic growth.

Construction of Nvidia’s planned Taiwan headquarters at Taipei’s Beitou–Shilin Technology Park is scheduled to begin this week.

According to officials, four gas-fired power plants are expected to gradually enter operation by the end of 2026, adding approximately 5.2 gigawatts of electricity capacity. Additional public and private power generation projects are also planned between 2027 and 2031.

The ministry said Taiwan’s experience supporting energy-intensive semiconductor industries has informed existing infrastructure planning. Officials stated that anticipated energy demand from AI-related industries had already been incorporated into long-term planning processes.

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Vietnam introduces mandatory labels for AI-generated content

Vietnam will require disclosure labels for certain AI-generated and AI-edited content from May under a new government decree aimed at improving online transparency.

Under Decree 142/2026/ND-CP, organisations and individuals using AI systems must disclose when content has been created or altered by AI in ways that could affect perceptions of authenticity.

The rules apply to AI-generated or AI-edited audio, image, and video content, particularly material imitating real people or realistic events. Particularly, it applies to content that imitates the appearance or voice of real people or recreates real-life events in a convincing manner. According to the decree, disclosures must be clear, visible, and recognisable before or during user access to the content.

The decree states that disclosures designed to obscure the AI-generated nature of content will not satisfy the requirements. Anyways, several exemptions are included. Several exemptions are included, such as technical quality improvements that do not materially alter content.

The framework also excludes certain AI-assisted editing functions, including spelling correction, translation, summarisation, and grammar editing, where original meaning is preserved. Additional exemptions apply to internal organisational use and controlled research or testing environments not intended for public release. At the end, content produced during research, development or testing activities in controlled environments and not released to the public is also an exemption.

Authorities said disclosures may take different forms depending on content type, including labels, captions, interface notices, or audio announcements. Labels may appear directly on content, in titles, captions and descriptions, through platform interfaces or even as audio announcements. Films and artistic productions may include disclosures in opening sections, end credits or supporting materials.

Responsibility for compliance will apply both to parties generating AI content and those distributing it publicly. Parties generating or editing AI content must provide the information needed for labelling, while those publishing the material to the public must ensure disclosure rules are followed.

Vietnam’s Ministry of Science and Technology is expected to publish additional technical guidance related to the implementation of the disclosure framework. Officials said the guidance would not create additional administrative procedures or business conditions or obligations beyond those already outlined in the decree.

Why does it matter?

The decree reflects broader international efforts to improve transparency around AI-generated media as synthetic content becomes more realistic and widely accessible. Disclosure requirements are increasingly being explored by governments as a way to address misinformation risks, impersonation concerns, and public trust in digital content.

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Greece launches public AI literacy guide for citizens

Greece’s Ministry of Digital Governance and Artificial Intelligence has launched ‘Artificial Intelligence for All’, a public guide designed to improve understanding and use of AI tools.

The guide was developed through cooperation between leading AI scientists, the Ministry of Digital Governance and Artificial Intelligence, the National Council for Research, Technology and Innovation, and the Special Secretariat for Long-Term Planning. The guide is available free of charge through the digital platform of the Special Secretariat for Artificial Intelligence and Data Governance.

According to the ministry, the initiative aims to support digital education, responsible AI use, and a broader understanding of AI systems.

The material introduces basic concepts related to AI and large language models through practical examples and simplified explanations. The guide explains how AI systems can process different forms of data and generate outputs, including recommendations, summaries, and digital content.

The project forms part of Greece’s broader digital strategy focused on digital skills development and public familiarity with emerging technologies.

Officials also highlighted collaboration with the members of the Greek scientific community in Greece and abroad, with the objective of making advanced technological tools more accessible to the wider population.

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Environmental group raises concerns over AI data centre emissions in Scotland

Environmental charity APRS has criticised the Scottish Government over how greenhouse gas emissions linked to hyperscale AI data centres are assessed within existing planning and climate frameworks.

According to APRS, earlier lifecycle emissions assessments focused primarily on broadband and smaller-scale digital infrastructure before the recent expansion of generative AI-related facilities.

The concerns are linked to a proposed 212MW AI data centre project in Edinburgh, currently involved in a planning appeal process.

APRS argued that the term ‘green data centre’ lacks a clear policy definition in relation to large-scale AI infrastructure projects. The organisation said Scotland does not yet have a dedicated policy framework addressing hyperscale AI data centres.

APRS stated that multiple large-scale data centre proposals are currently under consideration across Scotland. The group warned that growing electricity demand linked to data centre expansion could have implications for energy planning and climate objectives.

APRS also called for updated lifecycle emissions assessments and revised planning guidance for hyperscale AI infrastructure projects.

Why does it matter?

The debate highlights a widening policy gap between the rapid expansion of AI infrastructure and existing environmental planning frameworks. Many national climate assessments were created before the emergence of hyperscale generative AI systems, meaning governments may be underestimating the energy, emissions, and resource demands associated with large-scale AI deployment.

It also demonstrates how AI is no longer only a digital or technological policy challenge, but increasingly an environmental, infrastructure, and energy governance issue.

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New OECD measure compares AI and job capabilities

The OECD has published a new framework designed to assess how closely current AI capabilities align with the requirements of different occupations.

The paper, ‘The OECD AI Exposure Measure‘, maps OECD AI Capability Indicators to occupations and introduces an AI Capability Gap Index. According to the OECD, the framework is intended to support analysis of potential AI impacts on work, skills, education, and labour-market policy.

The framework compares AI capabilities with occupational requirements across nine domains: language, social interaction, problem-solving, creativity, metacognition and critical thinking, knowledge, learning and memory, vision, manipulation, and robotic intelligence. Occupations with smaller capability gaps are considered more exposed to current AI capabilities, while larger gaps indicate a greater distance between AI systems and occupational requirements.

The OECD emphasised that the measure is not intended as a prediction of automation or job loss. It measures potential exposure to current AI capabilities, while actual labour-market effects will also depend on adoption, costs, task structure, regulation, organisational uptake, and social choices.

The report found that occupations involving routine information processing and administrative tasks currently show the highest levels of AI exposure. Office and administrative support occupations record the lowest total gap index, followed by production, food preparation and serving, and sales-related occupations.

Occupations relying more heavily on judgement, social interaction, interpretation, and non-standardised physical activity showed larger capability gaps.

The paper also noted that different forms of AI may affect occupations differently depending on whether work relies more on reasoning, communication, robotics, or physical interaction.

The OECD said the framework could support future task-level analysis, scenario modelling, and country-specific assessments of AI-related labour-market change. Future work may extend the approach to task-level analysis, scenario applications, macroeconomic modelling, and country-level assessments.

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Singapore pushes trusted AI governance with KPMG AI centre

Singapore’s Ministry of Digital Development and Information has highlighted trust and accountability as key factors in AI adoption during the launch of KPMG’s new Trusted AI Centre of Excellence. Minister of State Jasmin Lau said governments and businesses should ensure AI adoption benefits workers, citizens, and smaller enterprises alongside larger organisations.

The new centre will focus on AI governance, monitoring systems, and AI-related assurance processes as organisations deploy increasingly advanced AI models. KPMG said it is using AI tools internally across audit, tax, and advisory services before broader deployment to clients.

Singapore also reiterated its goal of strengthening its role in regional AI governance and standards development. Officials highlighted efforts involving ASEAN cooperation, AI testing capabilities, and governance initiatives such as AI Verify. According to officials, transparency, explainability, and accountability will remain important factors influencing public confidence in AI systems.

The discussions also reflected broader concerns about AI-related economic disruption, governance challenges, and public trust. Officials noted that businesses and workers continue to face uncertainty regarding AI governance, compliance, and the economic effects of AI adoption.

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European Patent Office expands AI use in patent examination

The European Patent Office (EPO) has presented new AI-related initiatives aimed at supporting quality and efficiency within the European patent system during the latest meeting of the SACEPO Working Party on Quality.

The online gathering brought together 71 representatives from around the world to discuss examination standards, AI integration and long-term improvements to patent procedures. EPO President António Campinos described quality as a central element of the European patent system during the meeting.

The EPO also provided updates on its Quality Action Plan 2026, including examiner training, access to prior-art information, and examination harmonisation efforts. Officials also discussed insights drawn from quality audits and decisions issued by the Boards of Appeal.

Participants discussed the increasing use of AI-supported tools within the patent-granting process. According to the EPO, AI systems are being developed to assist with tasks including pre-search procedures, drafting support, legal queries, and preparation of oral proceedings documentation.

Participants also highlighted the importance of confidentiality, accountability, and human oversight in AI-supported systems.

The EPO stated that final patent examination decisions remain under human responsibility in line with its human-centric AI policy. The meeting additionally examined broader adoption of AI tools across patent and legal sector workflows, quality assurance and secure handling of sensitive intellectual property information.

Why does it matter?

The integration of AI into patent examination highlights how intellectual property systems are adapting to growing technological complexity and increasing volumes of patent applications worldwide. Faster and more consistent examination processes could strengthen innovation ecosystems across Europe, particularly in AI, semiconductors, biotechnology and digital industries.

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