AI in anti-corruption governance: bilingual policy framework evaluation

Purpose This study aims to examine the potential of artificial intelligence (AI) systems to generate innovative anti-corruption measures for martial law governance and post-conflict reconstruction, addressing gaps in traditional policy frameworks designed for peacetime implementation. Design/methodology/approach A mixed-methods design used six top AI systems – ChatGPT-4, ChatGPT-4o, ChatGPT-3.5, GitHub Copilot, Google GEMINI and Anthropic Claude – with bilingual English and Ukrainian queries. This study used systematic cross-validation procedures, temporal consistency verification and comprehensive content analysis over a 50-day research period from April to July 2024. A total of 216 responses were evaluated with standardized scoring matrices that assessed coherence, relevance and feasibility using five-point scales. The methodology integrated quantitative analysis of AI-generated responses with qualitative assessment of contextual appropriateness, ensuring robust evaluation of AI capabilities in crisis governance contexts. Findings AI systems demonstrated significant capability in identifying strategic gaps and proposing adaptive frameworks absent from Ukraine’s Anti-Corruption Strategy for 2021–2025. Notable variations emerged across linguistic contexts, with English-language responses showing greater analytical depth. Claude and ChatGPT-4 exhibited superior contextual understanding, while all systems identified five common anti-corruption measures: transparency initiatives, judicial reform, institutional strengthening, public engagement and education programs. However, critical limitations included contextual disconnection from existing Ukrainian institutions and reliance on pre-war training data. Originality/value This study introduces a pioneering bilingual methodology, evaluating AI-generated anti-corruption policies in both English and Ukrainian, addressing the unique challenges of martial law governance. It provides the first systematic evaluation of AI-generated policies in conflict contexts, offering practical frameworks for integrating AI with crisis governance.