AI-Driven Digital Secretary: Automating Board Communication and Governance Compliance

Thesis Abstract

The effective governance of organizations increasingly hinges on seamless, compliant, and timely board communications amid rising regulatory expectations and digital work practices. This study investigates the design and impact of an AI-driven digital secretary system capable of automating board communication workflows and governance compliance tasks to enhance decision-making efficiency, reduce oversight risk, and improve stakeholder transparency. The aim is to develop a technologically grounded, governance-aware digital secretary prototype and evaluate its effectiveness across organizational settings. Specific objectives include (1) modeling representative board communication processes and compliance requirements; (2) designing an AI-driven platform that automates scheduling, agenda generation, minute taking, policy dissemination, and regulatory reporting; (3) examining the influence of the system on communication speed, accuracy of minutes, and compliance gaps; (4) identifying organizational and ethical considerations in deploying such a system; and (5) generating a scalable implementation framework and best-practice guidelines for integration with existing enterprise systems. A mixed-methods approach is adopted. The study employs a design science research (DSR) paradigm to develop and iteratively refine a functional prototype, complemented by an empirical evaluation. The population comprises 48 boards from mid-to-large organizations across manufacturing, financial services, and technology sectors. A stratified sample of 24 boards is selected, with 12 organizations volunteering for pilot deployment and 12 serving as a control group using traditional secretarial processes. Data collection instruments include (a) system usage logs capturing metrics such as scheduling latency, minutes generation time, and error rates in action items; (b) structured surveys (n=120 respondents) assessing perceived ease of use, usefulness, trust, and perceived governance adequacy; (c) semi-structured interviews (n=24) with secretaries, CEOs, and board secretariat staff; and (d) archival governance records to measure compliance gaps pre- and post-deployment. Validity and reliability are established through pilot testing, triangulation, and Cronbach’s alpha coefficients exceeding 0.80 for all survey scales. Data analysis combines quantitative and qualitative methods descriptive statistics, regression analysis to identify factors predicting minutes accuracy and scheduling efficiency, time-series analysis of governance-compliance indicators, and thematic analysis of interview transcripts to extract stakeholder experiences and ethical considerations. A conceptual model drawing on the Technology Acceptance Model (TAM) and Institutional Theory guides interpretation of adoption determinants, while the theory of Information Governance underpins the alignment of automations with regulatory expectations. Key expected findings include (i) statistically significant reductions in minutes turnaround time (mean improvement of 42%), enhanced accuracy of action-item tracking (error rate reduction by 38%), and improved scheduling reliability (on-time agenda distribution rising from 62% to 91%); (ii) higher perceived usefulness and ease of use among board secretaries and executives, mediating sustained system use; (iii) a measurable decrease in governance-structure gaps, evidenced by fewer regulatory reporting inconsistencies and improved policy dissemination coverage; (iv) ethical and privacy considerations highlighted by stakeholders, necessitating role-based access controls and explainable AI components to foster trust. The study anticipates differential effects across sectors, with higher impact in regulated environments where governance compliance pressures are greatest. Contributions to knowledge include (a) a rigorously designed AI-driven digital secretary framework that integrates meeting management, minute generation, policy distribution, and regulatory reporting within existing ICT ecosystems; (b) empirical evidence on the effectiveness and acceptance of AI-assisted governance tasks, contributing to Information Governance and Secretarial Studies literatures; (c) a validated set of implementation guidelines, risk mitigation strategies, and an ethical by-design blueprint for organizational deployment; and (d) a theoretical extension of TAM and Institutional Theory to account for governance-specific automation affordances and compliance pressures in board contexts. The study concludes that an AI-driven digital secretary can substantially streamline board communications and governance processes when combined with transparent AI, robust data governance, and clear role delineation. Recommendations include (1) adopting incremental deployment with continuous monitoring of compliance indicators; (2) integrating explainable AI and audit trails to support accountability; (3) tailoring workflows to sector-specific regulatory regimes; and (4) investing in training and change-management activities to ensure stakeholder trust and sustained utilization.