Q3 2026

Across Supreme Audit Institutions, conversations about artificial intelligence (AI) often focus on technology. Discussions highlight models, data infrastructure, governance frameworks and future potential. Talk about AI is often shrouded in a certain air of mystery; practical applications tend to be conflated with more visionary ideas such as autonomous agents or even quantum computing. For many auditors, this can make AI seem complex − sometimes even intimidating.

In a world of rapid changes and increasing challenges, governments are asked more than ever to have concrete findings, provide high quality public service and manage the available resources efficiently, effectively and responsibly. With these changes, the public audit is not only viewed as just ensuring compliance with laws and protocols but also evaluating the performance and measuring the actual influence of government policies and programs on lives of citizens.

Environmental audits, especially in marine protected areas, face challenges in obtaining reliable evidence as environmental conditions often evolve gradually and are not completely reflected in routine monitoring records. Such challenges may necessitate an approach beyond conventional audit methods.

Over the past several years, the U.S. Government Accountability Office (GAO) estimated fraud facing the U.S. government using rigorous approaches that helped communicate the extent and impact of fraud in federal programs to Congress, the American public and antifraud professionals.

Supreme Audit Institutions (SAIs) play an essential role in strengthening accountability and transparency within democratic governance systems. As public policy challenges become increasingly complex and interconnected, SAIs are expected not only to provide assurance, but also to contribute more directly to governance improvement and sustainable development outcomes. This expectation is reflected in INTOSAI-P 12, which emphasizes that SAIs should create value and deliver tangible benefits to citizens through stronger accountability, transparency, and public sector performance (INTOSAI, 2013). International discussions have also highlighted the growing need for SAIs to address cross-sectoral and long-term governance challenges, including sustainable development and governance resilience (INTOSAI Journal, 2021).

In recent years, intermediate cities have emerged as critical drivers of regional development, yet evaluating their public services poses unique challenges for Supreme Audit Institutions (SAIs). To address this gap, Costa Rica’s SAI developed and implemented an innovative performance audit methodology specifically tailored to these distinct urban centers. This specialized framework advances traditional performance auditing by integrating a pragmatic assessment of public value, equity, and sustainable development within decentralized contexts.

Supreme Audit Institutions (SAIs) have increasingly expanded their role beyond legal compliance and administrative regularity to improve public policies and the quality of services delivered to society. Despite this evolution, many audits still focus on bureaucratic processes, governance structures, and institutional indicators, without fully capturing how public-sector shortcomings affect citizens’ daily lives.

Performance audit aims to secure government accountability by examining the economy, efficiency, and effectiveness of government activities. Although INTOSAI established universal standards for performance audit, the specific manners of how each SAI operates, shows different developmental stages and outcomes of their performance audits are all different depending on their own historical background and political, administrative landscape.

What do women with breast cancer actually pay for their treatment? Providing a rigorous answer based on available data poses a significant methodological challenge.

Data has become a central part for the management of complex public programmes. It helps to highlight trends, better understand impacts and identify the need for policy adjustments. For Supreme Audit Institutions (SAIs), the question is therefore no longer whether data analysis should be used in performance audits and evaluations. Rather, the key issue is how data analysis can be planned, prepared and integrated into audit work in such a way that it is driven by the audit questions and contributes to better insights, more convincing recommendations and, ultimately, greater impact.

At the beginning of 2026, the Netherlands Court of Audit published a report on the use of taxpayers’ money to fund both voluntary and obligatory energy saving measures. To carry out the audit we relied heavily on AI to analyse the data and map the overlap between incentives and obligatory measures. In this article we explain how we approached the audit topic and the use we made of AI.

On 29 October 2024, a DANA — a Spanish acronym for an isolated upper-level atmospheric depression forming over the Mediterranean Sea — triggered catastrophic flash flooding across Valencia province, Spain. Within hours, several municipalities received severe rainfall equivalent to an entire year’s precipitation, with peaks of up to 771 litres per square metre, devastating entire towns, leaving thousands stranded, damaging over 60,000 dwellings, destroying more than 130,000 vehicles, and claiming 230 lives.

At present, countries around the world are facing significant pressure to strengthen public governance, achieve the United Nations Sustainable Development Goals, and fulfill commitments to preventing and combating corruption, wastefulness, and other negative practices. In this context, Sustainable Development Goal 16 highlights the importance of enhancing transparency, good governance, and combating corruption in all its forms. At the same time, the Abu Dhabi Declaration of the International Organization of Supreme Audit Institutions (INTOSAI) also emphasizes and reinforces the role of Supreme Audit Institutions (SAIs) in preventing and combating corruption more effectively.

The expanding complexity of digital governance has fundamentally reshaped the audit landscape. Supreme Audit Institutions (SAIs) today confront voluminous financial records, and rapidly evolving programme architectures that strain conventional audit methods. Sample based scrutiny, and conventional data analysis methodologies are increasingly inadequate to detect systemic risks, hidden relationships, and governance failures embedded within interconnected digital systems.

The integration of artificial intelligence (AI) in the public-sector has reached a point at which Supreme Audit Institutions (SAIs) can no longer treat it as a distant or experimental matter. Emerging applications of agentic AI are beginning to reshape the work of professional knowledge services, including auditing. The pace of this development, driven both by private-sector commercial adoption and by the rapid evolution of open technical standards, makes technology relevant for public auditing today rather than at some point in the future.

The field of auditing faces challenges in keeping pace with unprecedented changes in perspectives and tools brought about by contemporary technologies resulting from technological advancements and the growing reliance on artificial intelligence tools. The information technology environment is no longer merely an assisting vehicle to improve audit quality; rather, it has become the primary driver for redefining the concept of auditing, as affirmed by INTOSAI in its professional pronouncements, which advocate for the development of audit tools and methods to align professional practice with the digital environment. This has prompted the Accountability State Authority (ASA), as the Organization’s chair, to move swiftly in this direction by putting forward pioneering initiatives, such as the Maat Initiative, which was brought up to the 25th INCOSAI agenda in Sharm El-Sheikh in October 2025. This initiative represents a contemporary vision that reflects the importance of utilizing artificial intelligence in the development of audit work, particularly in terms of performance audits that focus on evaluating the performance of government entities to verify the efficiency of public spending, thereby supporting governance and the protection of public funds.

The field of performance audit is transitioning from manual retrospective evaluations to real-time and prospective analysis due to the infiltration of technologies such as Big Data, artificial intelligence (AI) and predictive modelling, that is reshaping the efficiency and effectiveness of the audit function. As public institutions increasingly rely on data-driven systems for decision making, the complexity of governance frameworks also increases emphasizing the need for greater scrutiny of such institutions to strengthen transparency, accountability and public trust (Agostino, Lourenco & Jorje, 2025). Digital transformation has proliferated across both public and private sectors, resulting in the generation of enormous volumes of structured and unstructured data that cannot be effectively analysed using conventional audit approaches alone (Basuki, Atarwaman & Layn, 2025). Hence, the need for innovation in performance audit has become more prominent than ever, calling for the development of new tools and techniques to match the dynamics of modern information ecosystem.

As the INTOSAI Development Initiative (IDI) marks its 40th anniversary, it is timely to reflect on an important milestone: the establishment of the INTOSAI-Donor Cooperation (IDC) in 2009. Over the years, the IDC has become an important platform for helping the INTOSAI community, including IDI, engage more effectively with development partners. With the INTOSAI-Donor Cooperation Strategy 2020–2030 now entering its final phase, and with official development assistance undergoing major shifts, this is also an opportune moment to consider how the Cooperation can be repositioned to maximise its future value.