Capacity development

Google says AI power users drive UK productivity gains

Workplace AI adoption in the UK has more than doubled over the past year, reaching 73%, according to a new Google report. However, the benefits remain uneven, with a small group of advanced users seeing significantly stronger career outcomes than the wider workforce.

The report categorises workers into four groups: AI Spectators, who have not yet engaged with the technology; Experimenters, who use basic AI functions; Practitioners, who use AI regularly; and AI Trailblazers, who apply it in advanced and innovative ways.

Although AI Trailblazers account for just 15% of users, they report significantly better outcomes, including faster promotions, larger pay increases and substantial weekly time savings.

The report found that advanced users outperform other workers across several indicators, including promotions, performance reviews and salary growth. However, differences in adoption across age, gender and geography suggest that unequal access to AI skills could widen existing labour market disparities.

Google argues that closing this gap will require greater investment in AI literacy, organisational support and workplace culture. Initiatives such as national upskilling programmes and diagnostic tools are intended to help workers progress from basic experimentation to more advanced AI use, supporting broader productivity growth.

Why does it matter? 

The findings suggest that simply adopting AI is not enough to generate widespread economic benefits. The greatest productivity and career gains are concentrated among workers who integrate AI deeply into their daily work, highlighting the importance of skills development and organisational support.

The report also points to a growing policy challenge. If access to advanced AI skills continues to vary across demographic groups and regions, AI could widen existing inequalities in the labour market. Expanding AI literacy and helping more workers move beyond basic use may therefore be as important as increasing adoption itself.

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South Korea boosts AI funding to strengthen global competitiveness

South Korea’s National Assembly has approved a supplementary budget of 1.9067 trillion won for the AI sector, increasing the government’s original proposal by 61.8 billion won to strengthen the country’s global AI competitiveness. The Ministry of Science and ICT said the funding would be used to swiftly advance initiatives aimed at strengthening national AI competitiveness and positioning the country among the world’s top three AI leaders.

The funding is focused on three priorities: expanding AI computing infrastructure, advancing next-generation AI models and developing world-class talent. The largest allocation, 1.6341 trillion won, will be used to secure 10,000 advanced GPUs by the end of the year, alongside the leasing of a further 3,000 GPUs from the private sector to expand access.

A further 213.6 billion has been allocated to the proposed World Best LLM Project, under which five leading domestic AI teams will receive up to three years of support, including access to GPUs, high-quality datasets and specialist personnel. The Ministry will also launch the AI Pathfinder Project, offering grants of up to 2 billion won annually to attract leading international AI researchers.

Science and ICT Minister Yoo Sang-im said the funding comes at a pivotal moment as countries intensify competition for AI leadership. He said the government would pursue an all-out effort spanning advanced technology, talent development and AI adoption to establish South Korea among the world’s top three AI powers.

Why does it matter?

The supplementary budget demonstrates how governments are increasingly treating AI as strategic national infrastructure rather than simply an innovation policy issue. By investing simultaneously in computing capacity, foundation models and talent, South Korea is seeking to strengthen its long-term competitiveness in a global race increasingly defined by access to GPUs and skilled researchers.

The initiative also highlights that leadership in AI depends on more than financial investment alone. Competition for advanced chips and world-class talent has become increasingly intense, meaning the success of South Korea’s strategy will depend on how quickly it can translate funding into deployable infrastructure, cutting-edge research and commercial innovation.

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India launches WhatsApp chatbot for public health services

India’s Union Health Minister Jagat Prakash Nadda has launched Ayushman Sarathi, a WhatsApp chatbot developed by the National Health Authority to provide round-the-clock access to services under the Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY), the country’s government-funded health insurance scheme.

Built on secure API integrations with the PM-JAY digital platform, the chatbot enables beneficiaries to check their eligibility, apply for and download Ayushman Cards, complete electronic Know Your Customer (eKYC) verification, link their Aadhaar identity, view treatment history, locate empanelled hospitals and access other PM-JAY services directly through WhatsApp.

Users can also register, track and withdraw grievances, request callbacks, view wallet balances, and submit feedback after hospital discharge. According to the Ministry of Health and Family Welfare, the chatbot is intended to improve accessibility, transparency and beneficiary engagement while reducing reliance on physical visits and call centres.

The chatbot also supports feedback collection and grievance management, providing health authorities with additional insight into service delivery while helping monitor PM-JAY implementation across India.

Why does it matter?

The launch reflects India’s continued expansion of digital public services by integrating government programmes into widely used consumer platforms. Delivering PM-JAY services through WhatsApp could make it easier for millions of beneficiaries to access healthcare information and administrative services without visiting government offices or contacting call centres.

The initiative also illustrates how digital public infrastructure is reshaping healthcare delivery. By combining secure digital identity, online service access and feedback mechanisms, the chatbot aims to improve efficiency, transparency and user engagement while supporting better monitoring of one of the world’s largest public health insurance programmes.

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Chief AI Officers to lead AI adoption across Australian government

Australian public service agencies are formalising the appointment of Chief AI Officers (CAIOs) to guide the safe, strategic and coordinated use of AI across government.

Under the APS AI Plan, all non-corporate Commonwealth entities must appoint a senior leader as Chief AI Officer by 30 June 2026. Corporate Commonwealth entities and Commonwealth companies are strongly encouraged to make similar appointments.

The role is intended to help agencies adopt and use AI, particularly generative AI, as the technology reshapes government operations, public service delivery and internal processes.

Chief AI Officers will complement, rather than replace, AI Accountable Officials. While Accountable Officials focus on governance, compliance and risk management, CAIOs will lead strategic adoption, organisational transformation and AI capability building.

The government said CAIOs should provide strategic leadership rather than focus primarily on technical implementation. Their responsibilities include identifying high-value AI use cases, building staff capability, championing responsible adoption and ensuring AI is deployed safely and effectively.

CAIOs will work across technology, data, policy, cybersecurity, privacy and human resources functions, while collaborating with counterparts across the Australian Public Service and the Department of Finance’s AI Delivery and Enablement team.

Chief AI Officers will also collaborate across the Australian Public Service, including with other CAIOs and the AI Delivery and Enablement function in the Department of Finance.

The government said AI should be viewed as a general-purpose capability rather than a conventional technology upgrade, reflecting its potential to transform multiple areas of public-sector work.

The CAIO role is intended to help agencies move from experimentation to more systematic and responsible adoption. It is also designed to support a whole-of-organisation view of AI risks and opportunities.

The AI Delivery and Enablement team has developed an information pack to support agencies in appointing CAIOs, along with a blog for newly appointed leaders.

A wide range of agencies have already appointed Chief AI Officers. The published list includes major departments, regulators, integrity bodies, health and research agencies, cultural institutions, security agencies and service delivery organisations.

A wide range of organisations have already appointed CAIOs, including major government departments, regulators, law enforcement bodies, research organisations and service delivery agencies such as the Department of Finance, Home Affairs, Treasury, the Australian Federal Police, Services Australia and the Australian Electoral Commission.

The appointments of Chief AI Officers reflect a broader effort to coordinate AI adoption across government while maintaining attention to safety, privacy, cybersecurity, governance and public value.

Why does it matter?

Australia’s initiative reflects a broader shift from experimental AI projects to coordinated, organisation-wide adoption across the public sector. By establishing dedicated AI leadership roles, the government is seeking to embed strategic oversight while ensuring that innovation is balanced with governance, privacy, cybersecurity and public accountability.

The creation of Chief AI Officers also highlights the growing recognition that AI adoption is an organisational transformation challenge rather than solely a technical one. As governments integrate AI into public services, dedicated leadership is becoming increasingly important to coordinate implementation, build capability and ensure AI delivers public value responsibly.

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MIT develops AI system to improve robot understanding

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have developed a system that helps robots interpret vague human instructions while using significantly less training data.

The approach, called Masked Inverse Reinforcement Learning (Masked IRL), uses two large language models to clarify tasks and identify the details that matter for safe robot movement.

One model expands ambiguous instructions based on user demonstrations. A second model filters out irrelevant information and highlights factors the robot should include in its motion plan.

The system can help robots understand unstated preferences, such as avoiding a laptop while delivering a coffee mug or keeping a safe distance from a person during a task.

MIT said Masked IRL correctly identified users’ unstated preferences up to 15% more often than comparable methods. Researchers also found that it required nearly five times less demonstration data to learn new tasks.

The approach was tested in simulated environments and on a real robotic arm. The robot completed tasks it had not seen during training, including moving a cup towards a person while avoiding a computer and handing over an object while staying away from nearby obstacles.

Researchers plan to make the system more dynamic by adding cameras, enabling robots to identify relevant objects and ignore distractions in their surroundings visually.

Why does it matter?

Masked IRL could make robots easier to deploy in homes, offices, factories and care environments by reducing the amount of human training needed. The system also addresses a core safety challenge in robotics: people often give vague instructions and leave important preferences unstated. Better interpretation of human intent could help robots work more safely around people, objects and changing environments.

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South Korea unveils national AI infrastructure strategy

South Korea’s Ministry of Science and ICT has announced a comprehensive whole-of-government strategy to expand the country’s AI computing infrastructure and strengthen national AI capabilities.

The strategy is built around three pillars: expanding AI computing infrastructure, developing next-generation AI models, and accelerating AI adoption across public services. To strengthen computing capacity, the government aims to secure 18,000 high-performance GPUs by the first half of 2026, with 10,000 acquired through a public-private National AI Computing Centre and another 8,000 deployed as part of a sixth national supercomputer.

To advance domestic AI development, the government plans to launch a flagship initiative provisionally named the ‘World’s Best LLM’ project. Selected AI teams will receive dedicated access to computing resources, datasets and research funding. A Global AI Challenge will also be launched to attract leading domestic and international researchers, with winners offered startup support or positions within flagship AI projects.

Talent development is another key pillar. South Korea plans to expand its AI Frontier Labs beyond New York into Europe and other regions, establish AI Transformation graduate schools through industry-university partnerships and offer competitive salaries, research funding and relocation support to attract leading international AI experts.

The third pillar focuses on deploying domestically developed AI models across public services, including healthcare, education, the legal system, public administration, disaster management and content creation.

Why does it matter?

South Korea’s strategy reflects a growing global shift towards treating AI as strategic national infrastructure rather than simply a commercial technology. By combining investments in computing capacity, foundation models, talent development and public-sector deployment, the government is pursuing a comprehensive approach to strengthening technological competitiveness and digital sovereignty.

The plan also illustrates how competition in AI increasingly extends beyond model development alone. Access to high-performance computing, skilled researchers and coordinated industrial policy is becoming just as important as algorithmic innovation, with governments playing a more active role in shaping national AI ecosystems.

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UNESCO advances AI ethics training in Mexico’s judiciary

UNESCO has delivered the first specialised in-person training programme on the ethical use of AI for judicial professionals in Mexico City, aiming to support the responsible adoption of AI across the country’s justice system.

More than 50 civic judges, mediators and public defenders took part in the programme, which focused on ensuring AI supports judicial processes in Mexico while respecting transparency, accountability and human rights.

The programme introduced participants to the opportunities and risks associated with AI in judicial decision-making while providing practical guidance on applying ethical safeguards in courts and public institutions.

The training was based on UNESCO’s Recommendation on the Ethics of Artificial Intelligence, adopted by all UNESCO Member States in 2021, and incorporated the organisation’s newly published Guidelines for the Use of AI Systems in Courts and Tribunals.

The initiative forms part of a broader UNESCO and European Commission project supporting countries in implementing AI governance frameworks through capacity building, technical assistance and policy tools.

Participants were also introduced to UNESCO’s practical governance tools, including the Readiness Assessment Methodology, the Ethical Impact Assessment framework and Global Toolkit on AI and the Rule of Law for the Judiciary.

UNESCO emphasised that although AI is increasingly being incorporated into judicial and administrative processes, human oversight must remain central. The organisation said well-trained judicial professionals are essential to ensuring AI improves access to justice without replacing human judgement or undermining fundamental rights.

Why does it matter?

As AI becomes more common in courts and public administration, effective governance depends not only on regulation but also on the ability of judges and other legal professionals to understand the technology’s capabilities, limitations and risks. Training programmes such as this can help ensure AI supports judicial work without compromising due process, transparency or fundamental rights.

The initiative also demonstrates UNESCO’s broader approach to AI governance, combining international ethical principles with practical implementation tools. By equipping judicial institutions with guidance, assessment frameworks and technical expertise, the organisation aims to help countries translate high-level AI principles into everyday public-sector practice.

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Türkiye steps into quantum race with strategic roadmap

Türkiye has published an updated quantum technology roadmap, setting out 85 priority technology topics across quantum computing, quantum sensing and quantum communication.

The roadmap was developed through the Quantum Focus Technology Network (OTAĞ), coordinated by the Presidency of the Republic of Türkiye, Secretariat of Defence Industries. The process involved 305 experts from 123 institutions and organisations, including civilian and military stakeholders.

The roadmap classifies the 85 proposed technology topics into 34 near-term and 51 long-term priorities. Technologies were assessed using an analytical prioritisation method that considered Türkiye’s needs, existing capabilities, infrastructure, and end user requirements.

The strategy focuses on building domestic capability in quantum computing, sensing and communication by strengthening research infrastructure, developing skilled human capital and expanding cooperation between universities, industry, research centres and public institutions.

Priority steps include postgraduate programmes in quantum engineering and hardware technologies, researcher exchange and internship schemes, international research partnerships and critical infrastructure such as nanofabrication, cryogenic testing, precision measurement laboratories and sensor packaging.

The roadmap forms part of Türkiye’s wider effort to build a coordinated quantum ecosystem and improve its international competitiveness in a field with implications for cybersecurity, secure communications, advanced sensing and future computing.

Why does it matter?

Quantum technologies could reshape encryption, secure communications, sensing, navigation and high-performance computing. Türkiye’s roadmap is important because it turns quantum capability-building into a structured national programme with defence and strategic-technology relevance. By aligning universities, public institutions, industry and research centres around shared priorities, Türkiye is trying to reduce dependence on foreign technologies and position itself earlier in a field where global leadership is still being contested.

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Amazon announces $48 billion investment in India by 2030

Amazon has announced an additional $13 billion investment to expand AI and cloud infrastructure in India, bringing its planned investment in the country to $48 billion between 2026 and 2030.

The company said the new funding will expand AWS data centre capacity in Mumbai and Hyderabad, giving startups, enterprises and government organisations access to AI chips, managed AI services, cloud technologies and developer tools.

The announcement builds on a $35 billion investment across Amazon’s businesses in India announced in 2025. Amazon said its cumulative investments in India from 2010 to 2030 now stand at more than $88 billion.

Beyond AI and cloud infrastructure, Amazon said it will continue investing in its e-commerce and logistics network. The company plans to launch more than 20 new fulfilment centres and over 100 last-mile delivery stations across India this year, with a focus on faster deliveries in smaller cities.

Amazon said it has digitised 12 million small businesses in India, supported 2.8 million jobs, enabled more than $20 billion in cumulative e-commerce exports and trained more than 10 million people in cloud skills.

The company said its long-term priorities in India include AI-led digitisation, export growth and job creation.

Why does it matter?

Amazon’s investment highlights India’s growing role as a major market for AI infrastructure, cloud services and digital commerce. Expanding AWS capacity in Mumbai and Hyderabad could strengthen access to AI compute and cloud tools for businesses, startups and public-sector organisations. The announcement also shows how global technology companies are linking data centre investment with national priorities such as small-business digitisation, skills development, exports and job creation.

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Moldova tightens rules on AI in university theses

Moldova has approved a national framework regulation on academic integrity in higher education, introducing common rules on plagiarism, unauthorised use of AI and other forms of academic fraud.

The regulation, approved by the government and developed by the Ministry of Education and Research, sets a single framework that all higher education institutions in Moldova will be required to implement.

Under the new rules, students will have to declare whether they used AI in their academic work and explain how they used it. The ministry said the framework is intended to increase transparency and strengthen responsibility in the use of digital tools.

Acceptable AI use may include support functions such as proofreading, formatting or organising material, while core academic work, including analysis, interpretation and conclusions, must remain the student’s own intellectual contribution.

The regulation also classifies academic integrity violations by severity, with sanctions ranging from rewriting assignments to suspension or expulsion. Academic staff and supervisors may also face disciplinary measures if they fail to enforce integrity rules.

The framework forms part of Moldova’s wider effort to strengthen trust in higher education, including the planned use of a national anti-plagiarism system for bachelor’s and master’s theses.

Why does it matter?

Moldova’s rules show how universities are moving from informal guidance on generative AI towards enforceable academic integrity frameworks. Requiring students to disclose AI use can help distinguish between acceptable assistance and improper authorship, while preserving the value of independent analysis and critical thinking. The approach also reflects a wider education-policy challenge: institutions need to adapt assessment and integrity systems without banning useful digital tools entirely.

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