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New Zealand issues AI guidance to speed up regulatory work

New Zealand’s Ministry for Regulation in New Zealand has issued guidance encouraging public regulators to adopt AI for low-risk administrative tasks while maintaining human oversight and accountability. The guidance highlights low-risk uses, including case triage, prioritisation, and structured data validation. The framework is designed to help public agencies work faster while maintaining accountability and human oversight.

Officials stressed that AI should support rather than replace human judgement in regulatory decision-making. The document states that legal interpretation and final accountability must remain with human decision-makers, particularly in high-risk or complex cases.

The guidance also warns that introducing AI into poorly designed regulatory systems could amplify existing inefficiencies rather than resolve them.

The framework presents AI adoption as a strategic governance issue rather than solely a technical upgrade. Regulators are encouraged to establish clear objectives, safeguards, and accountability mechanisms, including transparency, fairness, privacy protections, and alignment with Te Tiriti o Waitangi principles.

Why does it matter?

New Zealand’s approach highlights a wider global shift where governments are using AI to improve public sector efficiency, but only within tightly defined boundaries. The focus on low-risk uses and human oversight reflects a growing view that automation can improve efficiency without replacing legal accountability.

The guidance also underscores a structural reality: AI can amplify existing strengths or weaknesses in regulatory systems. Countries that fail to modernise risk scaling inefficiencies, while strong oversight can help AI improve consistency, transparency and service delivery.

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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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Canada launches AI learning initiative for federal public servants

Canada’s School of Public Service is organising the Learning Week on Artificial Intelligence, an initiative aimed at strengthening AI understanding across the federal public service.

The programme is linked to the Government of Canada’s AI Strategy for the Federal Public Service 2025–2027.

The AI learning programme is open to public servants at all levels and across the country. The initiative includes live events, virtual sessions, self-paced learning tools, and practical demonstrations related to AI technologies.

According to organisers, the programme aims to improve awareness of AI-related opportunities, challenges, and skills within the public service.

The initiative also aligns with broader public service priorities involving digital transformation, productivity, and process modernisation.

Sessions will examine potential applications of AI in areas including policy development, service delivery, and internal administrative functions.

The programme is intended to support responsible AI adoption and prepare public servants in Canada for organisational and operational changes linked to AI technologies.

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South Korea launches tripartite committee on AI and labour

South Korea’s Economic, Social and Labor Council (ESLC), a presidential advisory body, has launched a tripartite committee to examine the impact of AI on labour and workplaces. The committee brings together labour, business, government, and public interest representatives for a year-long dialogue on AI-related workplace changes.

The committee held its first meeting in Seoul and will examine how AI adoption may affect employment patterns and industrial workplaces. The 17-member body is chaired by former presidential jobs secretary Hwang Deok-soon and includes labour, business, government and public interest representatives.

According to the ESLC, discussions will focus on AI adoption, changes to jobs and work tasks, worker data collection, and support measures linked to workforce transitions. The initiative is expected to include expert consultations and workplace assessments examining practical uses of AI technologies.

The launch comes amid broader public debate about automation, humanoid robotics, and potential labour-market disruption linked to AI technologies. ESLC Chair Kim Ji-hyung said the discussions aim to balance technological development, industrial competitiveness, and labour market stability in South Korea.

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International Labour Organization warns AI could reshape labour markets across the Arab region

The International Labour Organization (ILO) and the United Nations Economic and Social Commission for Western Asia (ESCWA) have examined how AI may reshape labour markets and employment patterns across the Arab region.

The organisations released a report exploring how AI adoption may transform jobs, productivity, and workforce dynamics by 2035. According to the report, outcomes will depend on policy choices related to skills development, labour protections, and social support systems.

The report outlines three possible scenarios ranging from inclusive AI-driven growth to increased inequality linked to insufficient labour protections and workforce adaptation measures.

One projected strong AI-driven economic growth, combined with large-scale investment in workforce transition and retraining programmes.

Another warned that rapid technological adoption without sufficient social safeguards could deepen inequality and displace large numbers of lower- and middle-skilled workers.

A third scenario envisaged a more gradual AI integration, supported by coordinated policy reforms and inclusive labour-market strategies.

The report identifies sectors such as healthcare, education, logistics, tourism, and digital services as areas where AI-related employment opportunities may emerge. At the same time, the organisations noted that automation could reduce demand for some routine and clerical occupations.

ILO Regional Director for Arab States Ruba Jaradat said AI technologies are already affecting workplaces across public administration and service sectors in the region. She added that nearly one-quarter of occupations may experience either displacement or technological augmentation linked to generative AI systems.

The analysis also highlighted widening skills mismatches between education systems and labour market demands, with some countries facing gaps ranging from 40% to 70%. The report also highlights the importance of investment in lifelong learning, labour market institutions, social protection, and AI governance frameworks.

The discussions took place during a preparatory session linked to the Arab Forum for Sustainable Development, where policymakers, labour organisations, and international experts examined how AI may affect youth employment, women workers, and lower-skilled populations across the region.

Why does it matter?

ILO highlights how developing and emerging economies may experience AI transitions differently depending on infrastructure, education systems, governance capacity, and investment levels. Policymakers across the Arab region are now under increasing pressure to modernise labour systems while ensuring that AI adoption supports inclusive growth instead of deepening social inequality.

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Meta reportedly cuts 8,000 jobs as AI investment and restructuring accelerate globally

Meta is reportedly cutting about 8,000 jobs globally as part of a restructuring aimed at reducing costs while increasing spending on AI infrastructure and products.

According to media reports, the cuts represent about 10% of Meta’s workforce and are intended, in part, to offset the cost of the company’s expanding AI investments. The reductions are expected to affect engineering and product teams in particular, with employees in several regions notified as the restructuring begins.

Reports also indicate that around 7,000 employees are being reassigned to new AI-focused teams, while thousands of open roles have been closed. The restructuring reflects Meta’s effort to redirect resources towards AI products, infrastructure and agent-based tools across its platforms.

In Ireland, reports said around 350 jobs were affected, representing a significant share of Meta’s local workforce. The company has not publicly confirmed all regional figures, but said affected employees and authorities had been notified.

The cuts come as Meta prepares for a major increase in AI-related capital expenditure. Reports say the company expects spending to rise sharply in 2026 as it builds infrastructure for AI models, personalised assistants and other AI-powered features across Facebook, Instagram, WhatsApp and its wider product ecosystem.

Staff concerns have also emerged around the pace of restructuring, internal communication and workplace monitoring linked to AI development. Reports cited employee unease over plans to monitor computer activity as part of AI training practices.

Why does it matter?

Meta’s restructuring shows how major technology companies are reallocating labour and capital around AI. The reported job cuts are not only a cost-saving exercise, but part of a wider shift in which companies are redirecting resources towards AI infrastructure, automation and agentic systems. The development also highlights a growing tension in the tech sector: AI is being presented as a long-term growth engine, while workers face uncertainty over how that transition will reshape roles, teams and investment priorities.

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Singapore and Google strengthen collaboration on AI innovation and digital governance

Google and Singapore’s Ministry of Digital Development and Information have announced an expanded National AI Partnership designed to accelerate the deployment of frontier AI technologies across the country’s economy and public sector.

The initiative builds on earlier collaboration between Google and Singapore’s digital authorities and aims to support healthcare innovation, scientific research, workforce development, enterprise transformation, and AI governance. Officials said the partnership aligns with Singapore’s National AI Strategy and broader ambitions to position the country as a global AI hub.

A major focus of the collaboration involves healthcare and life sciences. Google DeepMind is exploring AI co-clinician systems with Singapore’s public healthcare sector, examining how AI agents could support doctors and patients throughout medical treatment and decision-making processes.

Google DeepMind will also collaborate with the National Research Foundation to train researchers on agentic AI systems designed to accelerate scientific discovery. Additional partnerships with the Agency for Science, Technology and Research will focus on AI-enabled research and secure cloud-based scientific analysis tools.

The agreement also expands AI deployment in education. Google and Singapore’s Ministry of Education plan to strengthen educator training programmes and integrate AI-powered teaching support tools across schools. Officials said the partnership aims to improve digital learning capabilities while supporting broader AI workforce readiness initiatives.

Singapore and Google additionally announced plans to collaborate on AI safety, governance, and cybersecurity frameworks. A joint initiative involving Cyber Security Agency of Singapore and other agencies is examining how AI agents interact with real-world digital systems and how governance rules should evolve around autonomous AI technologies.

Officials described the partnership as part of a wider effort to deploy frontier AI responsibly while supporting economic growth, public services, and digital transformation.

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New Zealand outlines public service reforms focused on digital systems and AI

New Zealand has announced public service reforms aimed at improving efficiency, reducing duplication and expanding digital systems across government operations.

Public Service Minister Paul Goldsmith outlined plans to streamline departments and expand the use of digital systems and AI in public administration. The government said the reforms respond to public sector growth that has increased in recent years.

The programme sets a target of returning the core public service to around 55,000 employees by 2029, reversing growth that saw staffing rise from approximately 47,000 in 2017 to more than 65,000 in 2023. According to officials, projected savings are intended to support areas including healthcare, education, infrastructure, and security.

Critics, including the Public Service Association, have raised concerns that the reforms could weaken service delivery and that AI and restructuring may not adequately replace experienced workers, warning of potential disruption across essential public services.

Why does it matter?

The reform reflects a shift towards ‘digital-first state capacity’, where governments attempt to maintain or improve service delivery while constraining headcount growth through automation, AI integration and organisational consolidation.

The approach signals an increasing reliance on data-driven and AI-enabled systems to offset labour intensity in back-office functions, while reallocating fiscal resources towards frontline services and infrastructure.

At the same time, it raises structural questions about institutional resilience, transition costs of large-scale digitisation, and whether productivity gains from AI can realistically substitute for experienced human capacity in complex public service environments.

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Australia’s WGEA outlines AI transparency rules for internal use

Australia’s Workplace Gender Equality Agency has published an AI transparency statement outlining how it uses AI internally, in line with the Digital Transformation Agency’s Policy for the Responsible Use of AI in Government.

The agency uses AI to enhance workplace productivity and support internal service delivery processes, including case management, in a controlled and human-centred manner. It does not use AI for statutory decision-making, compliance determinations, auditing outcomes or enforcement actions.

Internally, AI helps staff manage and respond to enquiries using approved information sources. All outputs are reviewed and approved by WGEA staff before use, and AI-generated material remains advisory only.

The agency does not use AI systems to interact directly with the public or make decisions affecting individuals without human involvement. External communications are reviewed and issued by WGEA staff.

The statement notes that AI does not change WGEA’s accountability for the accuracy, quality or appropriateness of information provided. The agency also monitors usage levels, outcomes and reporting mechanisms to ensure systems operate as intended and align with responsible AI principles.

WGEA designated its Chief Operating Officer as the accountable official on 19 December 2024. The role is responsible for ensuring AI use complies with relevant legislation, whole-of-government policy and internal governance arrangements.

Why does it matter?

The statement shows how public bodies are beginning to formalise transparency around internal AI use, even when systems are not used for direct public interaction or decision-making. By limiting AI to advisory functions, requiring human review and naming an accountable official, WGEA is setting out a practical governance model for low-risk public-sector AI use.

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