In an age of rapid technological evolution, corruption is also evolving. Criminal networks are increasingly using advanced technologies to bribe, launder, collude, and conceal, often faster and more effectively than the systems meant to stop them. In this context, the use of tools like artificial intelligence (AI) and big data by public authorities, companies, and civil society is not a luxury but a necessity.
This imperative was discussed during the OECD Global Anti-Corruption and Integrity Forum on 26-27 March 2025, which explored how these technologies are being used to reshape efforts to promote integrity and accountability across sectors.
The promise of these tools is significant. AI is now deployed to detect corruption risks, strengthen compliance, monitor financial transactions, and expose sophisticated bribery schemes. Meanwhile, big data analytics enable oversight institutions and enforcement bodies to spot red flags, map hidden patterns and networks of influence, and build cross-border investigations with a level of speed and precision previously unimaginable.
For instance, enforcement agencies are combining public procurement datasets, corporate registries, and beneficial ownership information to detect collusive bidding and other bribery red flags. Companies are automating due diligence, risk assessments and compliance workflows to reduce blind spots and better anticipate exposure to corrupt practices. Investigative journalists, too, are using machine learning to sift and parse vast leaks and whistleblower reports, extracting meaningful stories from terabytes of unstructured and often opaque documents. These innovations are not only improving and speeding up detection and enforcement, but also fostering new forms of collaboration between governments, businesses, and investigative actors committed to closing the implementation gap in anti-corruption efforts.
But alongside these opportunities come serious challenges. Data quality and reliability remain major concerns. Inaccurate, incomplete or biased data can distort risk assessments and trigger flawed enforcement actions. The use of AI in investigations raises further issues, from “hallucinations” in generative models to opaque decision-making processes, which can threaten due process and accountability. Privacy, security, and the ethical use of data are also under scrutiny, particularly when algorithms are applied to high-stakes areas such as investigations, sanctions or whistleblower protections – making a human-centred use of and approach to digital technologies essential.
Moreover, many anti-corruption systems still suffer from fragmented and siloed data landscapes. Critical datasets, such as beneficial ownership registers or political-party finance and procurement records, are often incomplete, inconsistently formatted, or difficult to access across different institutions and jurisdictions. This lack of interoperability hampers stakeholders’ anti-corruption efforts, including tracing illicit financial flows, uncovering bribery networks, and coordinating cross-jurisdictional enforcement. Without robust data infrastructure and a level of standardisation, even the most advanced technologies will struggle to deliver on their anti-corruption potential.
To fully harness the potential of cutting-edge technologies in the fight against corruption and bribery, three priorities must be addressed:
- Build trustworthy data ecosystems: Ensuring accuracy, completeness, accessibility and interoperability across public and private sources is foundational. Fragmented, unreliable or opaque data erodes impact and impedes action.
- Invest in people, skills and collaboration across borders and sectors: Whether in law enforcement or corporate compliance, data scientists, legal experts, and technologists must work together. This requires adequate and targeted resourcing of enforcement authorities and compliance departments of companies, sustained international cooperation, and a deliberate effort to break down institutional and professional silos.
- Advance ethical and legal frameworks: With regulations evolving quickly, public and private sector governance must keep pace to ensure transparency, and protect fundamental rights, such as privacy, due process, and the responsible handling of personal data. Striking the right balance requires respecting data privacy rules while avoiding excessive restrictions that could hinder the effective detection and investigation of corruption. “Data diplomacy,” explaining how data will be used and demonstrating its public value, can help build trust and improve access where it’s needed most.
In short, technology alone will not win the fight against corruption and bribery, but when smartly and responsibly applied, it can tip the scales. The key lies in bridging data gaps, strengthening cooperation, and treating innovation not as an end in itself but as a powerful enabler of transparency and accountability.
For more, watch in replay the following sessions:
Harnessing cutting-edge technologies and collaboration for a holistic fight against corruption, moderated by Nicolas Pinaud
Bridging the data gap: Leveraging technology to strengthen the fight against corruption, moderated by Julia Fromholz
