The Ethical Implications of AI in Management: Navigating Challenges in Decision-Making

This research uses a tutorial approach to explore the intricate link between artificial intelligence (AI) and management decision-making processes, focussing on the alignment problem, which is a crucial obstacle to ensuring AI systems are in line with moral principles and human values. When defining artificial intelligence, it looks at a variety of methods, including algorithmic methods for machine learning (ML), sentiment analysis, anomaly detection, recommendation systems, expert systems, neural networks, deep learning, data visualisation, and natural language processing. The investigation explores how methodologies for machine learning and predictive analytics may use massive datasets to assist organisations in identifying market dynamics, competitive landscapes and novel patterns. By boosting data-driven decision-making, machine learning (ML) helps businesses proactively adjust to shifting circumstances and take advantage of new opportunities. Additionally, by analysing likely outcomes and their associated probabilities, this study investigates how ML-driven prediction models may lower risks. The investigation also looks at the ethical conundrums that arise when managers utilise ML to make strategic decisions, highlighting the significance of fairness, responsibility, and transparency in decision-making using algorithms.