Managing Algorithmic Initiative in Autonomous Systems: A Governance Framework for Corporate Accountability
TL;DR
This conceptual study analyzes the accountability gap that opens when strategic goals are delegated to algorithmic agents and develops the Dynamic Authority Delegation Model (DADM), which distributes responsibility among human strategic intent, algorithmic operational execution, and institutional oversight.
Abstract
Autonomous and agentic AI systems are turning information technology from a passive automation tool into an active decision-making proxy. Traditional human-centered liability models fall short once AI makes adaptive, high-impact decisions. This conceptual study analyzes the accountability gap that opens when strategic goals are delegated to algorithmic agents. Drawing on three cases (the Uber autonomous vehicle accident, the 2010 Flash Crash, and the COMPAS judicial risk assessment system), it develops the Dynamic Authority Delegation Model (DADM), which distributes responsibility among human strategic intent, algorithmic operational execution, and institutional oversight. By moving from individual blame to organizational governance, the study contributes to the IT management literature and offers a practical framework for corporate accountability, human oversight, algorithmic auditing, and responsible AI governance.