A new era for human resources is beginning, driven by the use of artificial intelligence (AI) and people analytics to inform human resources (HR) decisions. This report presents an integrated, multi-disciplinary review of the current state-of-the-art of using AI and people analytics in HR, based upon established theoretical models from information systems, organizational behavior, ethics, etc. The report describes how traditional descriptive HR metrics have evolved to predictive and prescriptive HR analytics through the application of machine learning, natural language processing and algorithmic decision systems. In addition to providing examples of AI/people analytics applications throughout recruitment, performance management, retention, workforce planning and employee wellbeing, the report also assesses both the positive impacts of AI/people analytics to enable HR decisions to be made more quickly, efficiently and strategically; as well as the significant negative implications of adopting these technologies - i.e. Algorithmic bias, erosion of employee privacy, distrust of employees toward HR systems, deskilling of HR professionals. Additionally, this report reviews ethical and legal frameworks related to fairness, accountability, transparency and the General Data Protection Regulation. Based on a synthesis of recent empirical and conceptual scholarship (2015 – 2025), the report argues that although AI and people analytics represent unparalleled opportunities for enhancing the quality and effectiveness of HR decisions; un-critically adopting them will lead to institutionalized biases, diminished employee dignity and degradation of the relational core of human resource management. Therefore, the report advocates for a human-centered augmented intelligence approach to HR where ethical principles are embedded within system design and human discretion is preserved. Finally, the report outlines a forward-looking research agenda centered around explainable AI, algorithmic literacy among HR professionals and co-design of analytics systems by employees.