Discover data analytics strategies and the role of Government Affairs Analysts in public-privatepartnership development. There is an increasing trend of published research applying data-driven and AI methods to assess risks in PPPs over recent years, which aligns with the growing adoption of PPPs globally for delivering public infrastructure projects. This study aims to explore the application of data-driven methods, including artificial intelligence (AI) techniques, for risk assessment in PPPprojects. This study systematically reviews 30 peer-reviewed journal articles sourced from academic databases, including Scopus and Web of Science. Find links to online databases for infrastructure, public-privatepartnerships (PPPs), private sector investment and other complementary resources to support analysis for PPPs below or visit the PPP Tools for an wider array of useful tools, guides and references. Projects can be broadly categorized into three main sectors: private, public or public-privatepartnership (PPP). The type of sector significantly influences the type of stakeholders involved and the required approach for stakeholder engagement and management. Effective risk assessment is crucial for mitigating these risks. This study aims to explore the application of data-driven methods, including artificial intelligence (AI) techniques, for risk assessment in PPPprojects. The Policy Brief Series will address both the pros and the cons in implementing AI in PPPs and infrastructure projects, including how AI is already utilised in projects and its potential to predict infrastructure needs, generate reports and analyses data.