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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UNESCO summit backs ethical AI governance in Latin America and the Caribbean

Representatives from more than 20 Latin American and Caribbean countries have met in Santo Domingo for a regional summit on AI ethics and governance.

The Third Ministerial and High-Level Authorities Summit on the Ethics of Artificial Intelligence in Latin America and the Caribbean took place on 25 and 26 June in the Dominican Republic. It was organised by UNESCO, the Dominican Republic’s Government Office of Information and Communication Technologies (OGTIC), and CAF – Development Bank of Latin America and the Caribbean.

The summit brought together ministers, senior government officials, multilateral organisations, academics, private-sector representatives and civil society to strengthen regional cooperation and accelerate the implementation of public policies aligned with the UNESCO Recommendation on the Ethics of Artificial Intelligence.

UNESCO said the meeting builds on earlier summits held in Santiago in 2023 and Montevideo in 2024, as well as ongoing work to develop a shared regional roadmap for responsible AI governance.

Anne Lemaistre, Director of the UNESCO Regional Office in Havana, said AI presents significant opportunities but also challenges that require coordinated regional action.

Raquel Peña, Vice President of the Dominican Republic, said the region had decided to come together to address one of the greatest challenges of the time. She said the task is to harness AI’s potential while upholding the principles that should guide its development and use.

Peña also reaffirmed the Dominican Republic’s commitment to a human-centred approach to AI. She said AI must be developed and governed with ethics, responsibility, and a profoundly human vision.

Christian Asinelli, Corporate Vice President of Strategic Programming at CAF, said Latin America and the Caribbean should play a stronger role in shaping global AI governance rather than simply adapting to international developments.

Raúl Fuentes, European Union Ambassador to the Dominican Republic, said the EU wants to work with the region on practical solutions as well as shared principles. He said the AI component of the EU-Latin America and the Caribbean Digital Alliance is supporting knowledge exchange, innovation, sovereignty, and a human-centred approach.

During the summit, Dominican authorities announced the forthcoming adoption of a national Artificial Intelligence Code of Ethics, developed with input from government, academia, civil society and the private sector, and aligned with international standards.

Edgar Batista, Director General of OGTIC, said the initiative reinforces the Dominican Republic’s commitment to digital transformation centred on public value. He said the country will contribute actively to the development of regional standards for digital governance.

Delegations are discussing AI governance, institutional capacity, responsible innovation, and regional cooperation. The talks aim to support ethical and regulatory frameworks for safe, inclusive, and trustworthy technological development.

The Dominican Republic will also assume the Pro Tempore Presidency of the regional mechanism, reinforcing its role in promoting ethical, inclusive and sustainable AI governance across Latin America and the Caribbean.

Why does it matter?

The summit reflects growing efforts by Latin American and Caribbean countries to develop a shared approach to AI governance based on ethics, inclusion and sustainable development. Regional cooperation can help governments build institutional capacity, align regulatory approaches and ensure AI policies reflect local priorities rather than relying solely on frameworks developed elsewhere.

The meeting also highlights the increasing importance of regional voices in global AI governance. By grounding discussions in UNESCO’s Recommendation on the Ethics of Artificial Intelligence and strengthening collaboration among governments, international organisations and other stakeholders, the region is seeking to play a more active role in shaping international norms for trustworthy AI.

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ECB highlights gap between AI adoption and productivity

Firms across the euro area are increasingly adopting AI, but only a small share are integrating it deeply enough to generate meaningful productivity gains. Data from the European Central Bank’s SAFE survey shows that although more than 70% of firms report using AI in some form, only 7% have integrated it deeply into their core operations.

Firms that use AI intensively are more likely to embed it in core business processes rather than limiting it to routine or experimental tasks. They are also more likely to innovate, expand their product offerings and align AI investments with long-term growth strategies.

Competitive pressure is also driving deeper AI adoption, particularly among established firms responding to technologically advanced rivals. However, skills shortages, legacy systems and financing constraints continue to limit many companies’ ability to scale AI effectively.

Why does it matter? 

The findings suggest that simply adopting AI is not enough to generate significant economic benefits. Productivity gains appear to depend on integrating AI into core business functions, innovation strategies and long-term investment plans rather than using it only for isolated or experimental tasks.

The survey also highlights structural challenges facing Europe’s digital transformation. Without investment in skills, financing and modern digital infrastructure, many firms may struggle to move beyond basic AI adoption, potentially widening the productivity gap between AI leaders and businesses that lack the resources to scale the technology.

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China’s latest supercomputer strengthens AI ambitions

China has regained the world’s leading position in supercomputing after the LineShine system became the fastest computer in the latest TOP500 ranking, replacing the US’s El Capitan at the top of the list.

The achievement marks China’s return to first place for the first time since 2017 and highlights the growing strategic importance of high-performance computing in the AI era.

Unlike many recent AI-focused supercomputers that rely heavily on graphics processing units (GPUs), LineShine achieves exascale performance using conventional central processing units (CPUs).

Beyond topping benchmark rankings, the system is expected to support scientific research, advanced simulations, climate modelling, pharmaceutical development and the training of increasingly sophisticated AI models.

The announcement also reflects the broader ambition of China to strengthen technological leadership while presenting its innovation ecosystem as a contributor to global technological development.

Europe also remains a major player in high-performance computing. Four European systems rank among the world’s ten fastest supercomputers, while the EU continues to invest in AI factories, next-generation supercomputing infrastructure and collaborative research centres.

The growing investment in supercomputers reflects how computing infrastructure is increasingly being treated as a strategic asset alongside semiconductors, cloud infrastructure and advanced data centres.

As governments increasingly link AI capabilities with economic competitiveness, scientific leadership and national security, access to world-class computing resources is becoming one of the defining factors shaping the global technology balance.

Why does it matter?

The latest TOP500 ranking underline that computing capacity is becoming a defining factor in AI development and scientific competitiveness. As frontier AI models require ever-greater computational resources for training and inference, access to world-class supercomputers is emerging as a strategic advantage alongside semiconductor manufacturing and cloud infrastructure.

China’s return to the top of the rankings also highlights the geopolitical dimension of high-performance computing. At the same time, continued European investment in AI factories and supercomputing infrastructure reflects a broader effort to strengthen technological sovereignty and reduce dependence on external computing resources as countries compete for leadership in AI and advanced research.

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