Capacity development Archives | Digital Watch Observatory

Greece launches platform to track public service requests in real time

Greece has launched politis.gov.gr, a new digital platform that allows citizens to track the progress of requests submitted to public administration services in real time. The initiative forms part of the government’s wider digital transformation agenda and aims to strengthen trust between citizens and the state.

Using their TaxisNet credentials, citizens can monitor applications submitted from 1 June 2026 onwards through the new platform. Users can view the current processing stage of a request, identify the responsible department, access contact details and review estimated completion timelines. Automatic notifications are also sent via email whenever a case is registered or updated.

Government officials described the platform as part of a broader cultural shift towards greater transparency and accountability in public administration. Instead of requiring citizens to repeatedly contact services for updates, the system provides a transparent digital record of every stage of the process. Authorities say the platform can reduce administrative burdens while improving accountability and the quality of public services.

The platform also creates a centralised view of a citizen’s interactions with public services, offering a complete history of cases and transactions with the state. According to the Ministry of Digital Governance and Artificial Intelligence, the platform represents another step towards a more efficient, citizen-centred and digitally enabled public sector.

Why does it matter?

Governments across Europe are increasingly using digital technologies to improve public service delivery and strengthen trust in public institutions. Providing citizens with real-time visibility into administrative processes can reduce uncertainty, improve transparency and limit the need for repeated interactions with government offices.

The platform also reflects Greece’s broader digital transformation efforts, which aim to streamline public administration, reduce bureaucracy and improve the overall user experience of government services.

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UK project tests how legal data can support AI use in government

The UK Government Digital Service has highlighted data maturity as a key requirement for preparing public sector data for AI use.

The findings come from a project conducted with The National Archives, part of GDS’s wider work to ensure public sector data is managed as a strategic national asset.

During a discovery phase completed in April 2026, the organisations assessed whether legal data, including legislation and case law, could be prepared for AI applications. The work focused on governance, data quality, organisational readiness, and the risks of exposing government data to AI systems, rather than building a specific AI tool.

GDS found that The National Archives’ legal data is already close to AI-ready, thanks to high data quality, strong leadership, relevant skills, and mature governance practices. It said that good data alone is not enough; public sector organisations also need the right people, processes, and culture to use data safely, ethically, and responsibly.

The project also identified the evaluation and validation of AI-generated outputs as a significant future opportunity for the government. GDS said public bodies could add value by developing tools and standards to assess whether AI outputs are trustworthy, rather than replicating services already developed by major technology companies.

The next phase will explore how data maturity can reduce the risks of using AI with public sector data. It will also examine technologies such as the Model Context Protocol, an open-source standard for connecting AI applications to external systems, including databases, tools, and documents.

Why does it matter?

The project shows that AI readiness in government depends on more than deploying new tools. Public bodies need high-quality data, strong governance, clear accountability, and the ability to evaluate AI-generated outputs before relying on them in services that affect citizens and businesses. The work also points to a useful role for government: setting standards for trustworthy AI outputs, rather than simply building public-sector versions of commercial AI products.

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Dutch study explores how to scale AI across government organisations

Dutch research organisation TNO has conducted an exploratory study examining how AI applications can be scaled across government organisations in the Netherlands. The study was commissioned by the Ministry of the Interior and Kingdom Relations because AI offers opportunities for public sector services and operations.

The study supports the Netherlands’ Digitalisation Strategy, which calls for a more proactive government role in the development and adoption of AI. One option under consideration is an AI scaling facility that would support the reuse and further development of successful AI applications, helping deploy them more quickly and across a wider range of organisations.

According to the study, scaling AI is not a linear or one-size-fits-all process. Depending on their goals, context, and partnerships, organisations may follow different approaches, including scaling within one organisation, replicating solutions across similar organisations, adapting them to new sectors or tailoring broad solutions to local needs.

TNO identifies seven approaches to AI scaling: scaling in, scaling out, scaling beyond, scaling together, scaling down, scaling up and scaling deep. The strategies cover internal adoption, cross-organisational reuse, sectoral adaptation, collaborative development, localisation, policy and standards work, and cultural or behavioural change inside organisations.

A related ‘Conversation starter’ has also been developed to help organisations assess AI scaling initiatives at the outset. The recommendations include treating scaling as a strategic decision, selecting an approach aligned with intended outcomes, addressing governance and organisational culture, reusing existing solutions where possible, investing in AI literacy and documentation, clarifying ownership and funding arrangements, and regularly assessing whether scaling remains desirable, feasible and legally appropriate.

Why does it matter?

Many governments are moving beyond AI experimentation and focusing on how successful projects can be deployed at scale. However, expanding AI use across public institutions often involves organisational, governance and cultural challenges that extend beyond technology itself.

The Dutch study highlights the need for structured approaches to AI adoption, emphasising reuse, collaboration and institutional capacity. Its findings could help governments accelerate AI deployment while maintaining accountability, effectiveness and compliance with legal requirements.

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Ireland launches fund for fact-checking and anti-disinformation training

Ireland’s media regulator, Coimisiún na Meán, has launched a funding call to support training in fact-checking, prebunking and debunking for journalists and media professionals during 2026.

The programme is aimed at graduate, early-career and mid-career professionals working in news and current affairs. Eligible activities include training courses, mentorship programmes, internships and collaborative projects designed to strengthen fact-checking and verification skills.

The fund forms part of the regulator’s Media Skills and Development Programme and supports objectives outlined in Ireland’s National Counter Disinformation Strategy. Applications are open to academic institutions, accredited bodies and representative organisations, including partnerships involving media organisations.

Minister for Culture, Communications and Sport Patrick O’Donovan said the initiative would help strengthen professional skills and support high-quality journalism. Applications are open until 2 July 2026, with all funded activities to be delivered in Ireland during 2026.

Why does it matter?

Fact-checking, verification and disinformation response skills are becoming increasingly important as journalists navigate rapidly evolving information environments shaped by social media, generative AI and coordinated influence campaigns.

By investing in professional training, Ireland aims to strengthen media resilience, support evidence-based reporting and enhance the capacity of news organisations to identify and counter misleading or false information.

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Cambridge researchers test AI-designed vaccine in human trial

Researchers at the University of Cambridge have developed an experimental vaccine using AI, marking what they describe as the first human test of a vaccine component designed entirely by AI. The experimental approach aims to provide broad protection against entire families of viruses, including coronaviruses with pandemic potential.

The AI system analysed genetic data from multiple coronaviruses and designed a ‘super-antigen’ intended to help the immune system recognise and respond to a broad range of viral variants, including those that may emerge through future mutations. An initial trial involving 39 volunteers focused primarily on safety, while a larger follow-up study is planned to evaluate immune responses and effectiveness in greater detail.

Researchers say the approach could help vaccine development keep pace with rapidly evolving threats, including influenza, emerging COVID-19 variants and viruses with the potential to spread from animals to humans. The team is also exploring similar AI-designed vaccines for influenza, bird flu, and Ebola-like viral haemorrhagic fevers, where current protection options remain limited.

Researchers describe the findings as an early but significant step towards using AI to accelerate vaccine design and strengthen preparedness for future disease outbreaks. The study highlights growing expectations that AI may become a central tool in global pandemic prevention strategies.

Why does it matter?

Traditional vaccine development often focuses on responding to specific pathogens after they emerge. By contrast, AI-assisted design could help researchers develop vaccines that provide protection against entire families of viruses before outbreaks occur.

If successful, the approach could shorten development timelines, improve preparedness for future pandemics and support efforts to address rapidly evolving infectious diseases. The research also highlights the growing role of AI in scientific discovery and biomedical innovation.

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OECD launches AI Policy Toolkit for governments

The Organisation for Economic Co-operation and Development (OECD) has launched the AI Policy Toolkit, a practical guide intended to help governments translate AI principles into policy action. Released by the OECD under the Global Partnership on Artificial Intelligence, the first version is designed as a non-prescriptive resource for policymakers working across the AI policy cycle.

Building on the OECD AI Principles, the toolkit is intended to help governments identify policy priorities, compare international approaches and adapt guidance to national circumstances. The platform incorporates AI-powered semantic search to help users identify relevant policy examples and practical approaches drawn from real-world experience.

The OECD developed the AI Policy Toolkit through co-creation with end-users across regions, including targeted interviews and workshops in Southeast Asia, Latin America, and Africa. Policymakers, industry representatives and experts helped shape the platform around implementation challenges, including balancing innovation and regulation, addressing infrastructure gaps and supporting AI adoption in sectors such as agriculture, education and healthcare.

According to the OECD, the development process highlighted two key lessons: AI policy is heavily influenced by national context, institutional capacity and levels of digital maturity, while challenges such as advanced AI risks and linguistic and cultural representation often require international cooperation. Contributors included governments and organisations from Costa Rica, Italy, France, South Korea, Japan, the United Kingdom, the European Union, the French Development Agency, and the Inter-American Development Bank.

The OECD says the toolkit will continue to evolve through feedback, additional policy examples, and expanded coverage of emerging issues, including sector-specific guidance, infrastructure, and regulatory approaches. The OECD said the toolkit’s broader objective is to help governments move from high-level AI principles to practical implementation while managing risks and promoting trustworthy AI.

Why does it matter?

Many governments have adopted AI principles and strategies, but translating these commitments into practical policies remains a challenge. The OECD’s toolkit seeks to bridge that gap by providing policymakers with implementation guidance, real-world examples and policy options tailored to different national contexts.

The initiative also reflects growing recognition that effective AI governance requires both domestic policymaking capacity and international cooperation, particularly as countries confront shared challenges related to advanced AI systems, infrastructure needs and regulatory approaches.

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New Zealand’s NCSC warns frontier AI could amplify cybersecurity risks

New Zealand’s National Cyber Security Centre (NCSC) has issued guidance to help government agencies prepare for the cybersecurity implications of frontier AI systems. The advisory notes that frontier AI models may enable more advanced automation, reasoning and decision-making capabilities than previous generations of AI systems.

The guidance describes frontier AI as a dual-use technology, noting that the same capabilities that enhance cyber defence could also enable malicious actors to conduct cyber operations more quickly, at lower cost and on a larger scale. The NCSC warns that frontier AI could amplify risks associated with known vulnerabilities, legacy systems and poor cyber hygiene, creating what it describes as a ‘vulnerability storm’ for organisations.

According to the NCSC, organisations do not need access to the most advanced frontier AI models to strengthen their cyber resilience. Instead, it says effective readiness depends on existing cybersecurity mitigations and practices, including the New Zealand Information Security Manual, the NCSC Cyber Security Framework, Minimum Cyber Security Standards, and Protective Security Requirements.

The advisory urges government entities to treat several actions as immediate priorities, including reviewing compliance with existing standards, confirming executive accountability for frontier AI cyber risk, reviewing NCSC guidance, and identifying material gaps that AI-enabled threat actors could exploit.

The guidance also restates the NCSC Cyber Security Framework’s five functions: guide and govern, identify and understand, prevent and protect, detect and contain, and respond and recover. The advisory highlights a range of baseline cybersecurity measures, including risk management, security awareness, secure configuration, patch management, multi-factor authentication, least-privilege access controls, anomaly detection, data recovery and incident response planning.

Why does it matter?

Frontier AI is expected to increase the speed, scale and sophistication of cyber operations, potentially allowing attackers to identify vulnerabilities, automate exploitation and conduct campaigns more efficiently than before.

Rather than relying solely on new AI-specific defences, New Zealand’s guidance emphasises that strong cybersecurity fundamentals, including patching, access controls, monitoring and incident response, remain the most effective way to reduce risk. The advisory reflects a growing international view that AI is amplifying existing cyber challenges rather than replacing them with entirely new ones.

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Armenia expands AI ecosystem through research, infrastructure and investment

Armenian Prime Minister Nikol Pashinyan said government initiatives have helped position Armenia as an emerging centre for technology and AI, according to remarks reported by state news agency Armenpress. Speaking during the election campaign, Pashinyan highlighted several projects that he said demonstrate the government’s efforts to strengthen Armenia’s technology sector.

Pashinyan highlighted agreements signed with US President Donald Trump last year, including cooperation on AI. He argued that subsequent developments in the sector have validated the government’s approach.

As examples of progress, the Prime Minister cited the establishment of an AI centre at Yerevan State University and the launch of the Eleveight AI data centre. He also linked developments in the sector to increased public investment in science and higher salaries for researchers.

Pashinyan said investment in the defence sector has supported technological development and stated that Armenian defence companies are exporting products internationally. He made the remarks during campaigning ahead of Armenia’s parliamentary elections.

Why does it matter?

Armenia is seeking to expand its role in emerging technologies at a time when countries are increasingly investing in AI infrastructure, research capacity and digital innovation as drivers of economic growth and competitiveness.

The government’s focus on AI cooperation, research institutions and data centre infrastructure reflects broader efforts to strengthen domestic technological capabilities and attract investment in the digital economy.

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Hong Kong launches AI-focused cybersecurity initiatives for 2026

Hong Kong’s Digital Policy Office has announced a series of AI-related cybersecurity initiatives for the second half of 2026, following a briefing on cyber resilience and emerging technology risks. The office said it would focus on improving AI security awareness and digital literacy among both organisations and the public.

Planned initiatives include a Secure AI@Work Enablement Campaign, organised with the Hong Kong Internet Registration Corporation, to help enterprises develop secure and compliant AI ecosystems. The Digital Policy Office will also collaborate with industry on an AI x Cybersecurity Challenge focused on AI-powered threat detection, cyber resilience and cybersecurity skills development.

The office said it would continue enterprise support and practical drills, including an enhanced Cybersec One+, the Cybersecurity Service Providers Connect Programme and the third Hong Kong Cybersecurity Attack and Defence Drill. Hong Kong will also consolidate the Cyber Security Summit Hong Kong and the Cybersecurity Symposium into a single Cybersecurity Symposium and Summit in December.

The Cyber Security and Technology Crime Bureau said the volume of cyber threat intelligence related to threats targeting Hong Kong continues to increase. Its Cyber Security Centre analysed more than 330,000 threat intelligence records during the first quarter of 2026, identifying phishing as the most prevalent threat category.

The bureau said it would deepen international law enforcement cooperation, strengthen intelligence sharing with sectors including critical infrastructure, and use AI and big data to improve cyber threat detection, early warning analysis, and incident response. The Hong Kong Police Force and Cyberport have also established the Smart Policing Joint AI Lab to develop technologies for detecting deepfakes and strengthening network defence capabilities.

Why does it matter?

The initiatives reflect growing efforts by governments to address the cybersecurity implications of wider AI adoption. As organisations increasingly integrate AI into business operations, concerns around secure deployment, cyber resilience and workforce readiness are becoming key policy priorities.

The programme also highlights how AI is being used both as a potential source of cyber risk and as a tool for improving threat detection, incident response and cyber defence capabilities.

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Anthropic expands AI cybersecurity programme for critical infrastructure

AI company Anthropic has announced a major expansion of Project Glasswing, an initiative aimed at strengthening the security of critical software through AI-assisted vulnerability detection.

After initially providing access to around 50 organisations, the programme will expand to approximately 150 additional partners across more than 15 countries.

Project Glasswing provides selected organisations with access to Claude Mythos Preview, Anthropic’s cybersecurity-focused AI model. According to Anthropic, participating organisations have identified more than 10,000 high- and critical-severity software vulnerabilities through the programme.

The newly added participants include operators and vendors across critical infrastructure sectors such as power, water, healthcare, communications and hardware manufacturing.

Anthropic argues that increasingly capable AI systems could significantly reshape cybersecurity, creating both new defensive opportunities and new risks. The company says future AI models may enable defenders to identify, analyse and remediate vulnerabilities at greater scale, while also potentially enhancing the capabilities available to malicious actors.

Project Glasswing is intended to help critical organisations adapt before such capabilities become widely accessible.

Alongside the expansion, Anthropic said it plans to provide additional cybersecurity tools, support vulnerability remediation efforts and work with industry, governments and open-source software maintainers to strengthen cyber resilience.

Why does it matter?

The expansion of Project Glasswing highlights the growing role of AI in cybersecurity, particularly in vulnerability discovery and software security testing. As critical infrastructure operators face increasingly sophisticated cyber threats, AI-assisted tools may help identify and address security weaknesses more quickly.

At the same time, the initiative reflects broader concerns that advances in AI could benefit both defenders and attackers, increasing the importance of responsible deployment, coordinated security research and resilience planning across critical sectors.

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