In this episode of AI Ignited, host Elif Baser welcomes Mehmet Efe Gurkan to unpack the technical foundations of algorithmic management systems—AI-driven decision pipelines increasingly used in HR, scheduling, and performance management.The conversation explores how machine-learning models are integrated into organizational infrastructure, from data ingestion and feedback loops to real-time decision execution. Drawing on ongoing research from MIT, the episode examines key challenges such as model drift, explainability, human-in-the-loop oversight, and governance frameworks required to manage risk and accountability in automated decision systems.
Rather than treating AI as a standalone tool, this episode frames algorithmic management as a full decision architecture—one that reshapes how organizations allocate work, evaluate performance, and maintain control over increasingly autonomous systems.A must-listen for anyone interested in the technical reality of AI in management, not just the hype.