Enhancing corporate governance with decentralized AI: a structuration theory perspective

Purpose Decentralized artificial intelligence (DAI), built on distributed ledgers and smart agents, is increasingly used to strengthen corporate governance by tackling record-keeping and transparency issues. Drawing on Giddens’ structuration theory, this study aims to examine the interaction between actors and structures within DAI systems. Structuration provides a lens to explain the duality of organizational relationships with shareholders, particularly relevant to Annual General Meetings (AGMs), where remote voting often creates methodological concerns. Design/methodology/approach A meta-synthesis dimension analysis is undertaken to assess DAI-based governance solutions, using a retrodictive approach. Alongside the duality of structure, new meta-dimensions for governance solutions are introduced to capture their operational relevance. Findings The convergence of blockchain, data science and the Internet of Things is creating new opportunities for research and application. The analysis shows significant synergic effects in the financial and economic domains from technological adoption and the potential of blockchain-driven tools to enhance the effectiveness of governance practices. Practical implications The study supports the integration of decentralized technologies to reduce shareholder voting costs, improve the speed of decision-making and encourage greater participation in AGMs, thereby advancing governance quality. Originality/value This research offers a fresh perspective by applying structuration theory to the role of DAI in corporate governance. It develops a comprehensive and theoretically grounded model for implementation, aiming to make governance systems more transparent, secure and participatory while improving shareholder engagement and decision-making efficiency.