Jun 2026· Journal of Information and Technology· 0 citations· 44 references
TL;DR
This analysis underscores the need to continuously recalibrate governance as decentralized technologies proliferate, requiring increasingly adaptive EAM strategies to balance innovation, flexibility, and architectural coherence.
Abstract
Enterprise systems governance is undergoing a shift toward decentralization and federation, as platforms and tools increasingly empower business users to create and deploy applications outside professional IT. Low-Code Development Platforms (LCDPs) represent a prominent instance of this trend, enabling rapid application development while simultaneously introducing challenges for Enterprise Architecture Management (EAM). Through a multiple-case analysis of organizations from financial services, healthcare, and manufacturing, we identify three governance challenges organized around what is governed (architectural drift), who is governed (role ambiguity and shifting accountability), and how governance is enacted (tension between formal and informal control), and show that that organizations address these challenges through deliberately composed governance portfolios pairing formal instruments with informal enabling practices. Reasoning abductively across cases, we identify five mechanisms through which these portfolios produce durable EA outcomes: information symmetry, perceived legitimacy, developer capability, enacted decision-right alignment, and secure-by default conditions. Theoretically, we contribute by distinguishing the locus of control (centralized vs decentralized) from the mode of control (formal vs informal), and by offering a mechanism-based explanation of how governance portfolios produce EA outcomes under decentralized development conditions, moving beyond generic prescriptions for “balance” toward a concrete account of why specific governance compositions work. Practically, our analysis underscores the need to continuously recalibrate governance as decentralized technologies proliferate, requiring increasingly adaptive EAM strategies to balance innovation, flexibility, and architectural coherence.
Multinational organizations operating across diverse regulatory regimes face significant challenges in managing compliance obligations that span multiple jurisdictions, industries, and legal frameworks. The fragmented nature of compliance management, characterized by siloed risk assessments, disconnected control mechanisms, and duplicative reporting structures, creates operational inefficiencies, heightened compliance risks, and increased costs. This paper examines the conceptual foundations and practical implementation of cross-industry unified compliance frameworks designed to address these challenges. Building upon Chinenye's (2013) foundational work on transitioning from fragmented compliance to integrated governance, this study explores how multinational organizations can harmonize regulatory controls, security protocols, and risk management processes across disparate operational contexts. Through analysis of international standards (ISO 19600, ISO 31000, COSO ERM), technological enablers (blockchain, automation, GRC platforms), and governance architectures, the paper proposes a comprehensive framework for achieving compliance integration. The framework emphasizes centralized policy development coupled with localized implementation, continuous monitoring mechanisms, and stakeholder engagement across organizational boundaries. Findings indicate that successful unified compliance frameworks require alignment of organizational culture, technology infrastructure, and governance structures while maintaining flexibility to accommodate jurisdiction-specific requirements. The paper concludes with recommendations for practitioners and identifies areas for future research in compliance harmonization and regulatory technology.
Olajumoke Mary Ogundipe· Multiverse Journal· 0 citations
A decentralized autonomous organization (DAO) is a governance entity that allows its stakeholders to manage blockchain-based protocols through smart contracts. The DAO explicitly specifies how stakeholders make and enforce decisions concerning a protocol's operation in a smart contract, aptly referred to as its governance contract. The design of this governance contract, therefore, has far-reaching implications for the security (trust) and privacy (transparency) of the smart contracts managed by the DAO and its stakeholders. In this work, we (i) explicate the trust and transparency trade-offs of the design choices in implementing a DAO and (ii) highlight how poor choices introduce critical vulnerabilities, using real-world examples as case studies. To this end, we analyze $48$ public, actively used Ethereum-based DAOs that control a vast capital. We classify the design choices into a handful of key dimensions that succinctly capture how a DAO's stakeholders initiate a protocol change, vote on it, and, based on the voting outcome, execute that change. Our analyses crucially uncover a new class of attacks, which we call governance attacks, that directly exploit the fundamental design of a DAO's governance mechanisms, even if we assume bug-free implementations.
Vabuk Pahari, B. Chandrasekaran, Johnnatan Messias et al.· 0 citations
The rapid integration of artificial intelligence (AI) into enterprise decision-making systems has fundamentally transformed organizational governance across sectors, enabling automated decisions in credit assessment, healthcare resource allocation, workforce management, pricing strategies, and public-sector services. As AI increasingly influences decisions with significant social and economic consequences, the need for robust governance mechanisms has become as important as technological innovation itself. However, governance frameworks, accountability mechanisms, and equity assessment practices have not advanced at the same pace as AI deployment, creating substantial risks related to transparency, fairness, regulatory compliance, and organizational trust. This article examines three interconnected dimensions of responsible AI for enterprise modernization: governance infrastructure for accountable AI deployment, algorithmic equity in high-impact decision environments, and the evolving international regulatory landscape shaping enterprise AI governance. Drawing upon implementation experiences and governance practices across telecommunications, financial services, and healthcare, the study synthesizes evidence from engineering, policy, ethics, and critical social science literature to develop a comprehensive perspective on responsible AI architecture. The analysis demonstrates that effective AI governance requires integrating technical controls with organizational accountability, continuous monitoring, auditability, risk management, and human oversight throughout the AI lifecycle. Furthermore, the study argues that technical governance alone cannot eliminate algorithmic bias or inequitable outcomes unless accompanied by structural policy interventions addressing the underlying institutional and societal conditions embedded within training data and decision processes. The proposed governance perspective positions responsible AI as a foundational engineering discipline that enhances regulatory compliance, organizational resilience, stakeholder trust, and long-term business sustainability while reducing legal, operational, and reputational risks. The findings provide practical guidance for enterprises seeking to modernize AI-enabled decision systems through governance architectures that balance innovation with accountability, ethical responsibility, transparency, and equitable value creation across increasingly complex digital ecosystems
M. Modi· International Journal of Eng...· 0 citations
Software development has evolved into a core organizational capability whose outcomes are shaped as much by managerial and governance structures as by technical expertise. As engineering teams become increasingly distributed across geographies, organizations, and time zones, traditional coordination mechanisms based on proximity and informal communication are no longer sufficient. In these environments, software development demands deliberate governance models that guide decision-making, accountability, and technical consistency at scale. This article conceptualizes software development as a managerial discipline, arguing that effective software delivery in distributed engineering environments depends on governance frameworks rather than isolated technical practices. It examines how distributed settings amplify challenges related to decision rights, architectural coherence, and risk management, transforming technical choices into organizational commitments. The study positions governance not as bureaucratic control, but as an enabling structure that balances technical autonomy with strategic alignment. Drawing on software development practice and engineering management perspectives, the article analyzes governance mechanisms specific to distributed software teams, including decision authority distribution, communication structures, and accountability models. It explores how leadership roles function within these governance systems to maintain quality, reliability, and consistency across decentralized teams. Particular attention is given to the interaction between technical authority and managerial responsibility in environments where direct oversight is limited. By framing software development as a managerial discipline supported by governance models, this article contributes to the literature on software engineering management and distributed systems. It provides a conceptual foundation for understanding how software organizations can scale responsibly while preserving technical integrity. The findings offer practical insights for software development leaders tasked with governing complex, distributed engineering environments in a sustainable and effective manner.
Deniz Ceylan Kurt· International Journal of Res...· 0 citations
This review critically examines the convergence of enterprise automation and data governance as complementary capabilities shaping organisational efficiency, accountability, resilience, and strategic value. Its purpose is to synthesise the technological, managerial, ethical, legal, and operational dimensions of automated enterprise systems while identifying the conditions under which such systems can be deployed responsibly and productively. A structured narrative review method was adopted, drawing on peer-reviewed scholarship, institutional evidence, professional frameworks, and regulatory perspectives published across diverse sectors and geographical contexts.
The findings show that automation delivers sustained benefits only when supported by reliable data architectures, clearly allocated decision rights, robust cybersecurity controls, and meaningful human oversight. Technologies such as robotic process automation, artificial intelligence, cloud platforms, process mining, digital twins, and cyber-physical systems can improve speed, consistency, forecasting, and resource optimisation. However, fragmented data ownership, poor information quality, algorithmic opacity, privacy breaches, weak organisational readiness, and inadequate workforce capabilities can amplify operational and regulatory exposure. The review further establishes that governance effectiveness depends on coordinated executive leadership, data stewardship, ethical safeguards, continuous monitoring, and multidimensional performance measurement.
The study concludes that enterprises should treat automation and data governance as an integrated strategic agenda rather than as separate technical initiatives. It recommends governance-by-design, phased implementation, workforce reskilling, periodic maturity and impact assessments, stronger model and data inventories, and independent assurance for high-risk systems. Future research should prioritise context-sensitive governance models, especially for African enterprises, alongside longitudinal studies of business value, human–machine accountability, explainable systems, federated learning, and responsible autonomous decision-making. These priorities are essential for preserving trust, legitimacy, adaptability, and sustainable competitiveness.
Bisola AkejuQ, Ayokunle Olamide Ijagbemi, Shalom Alugwe· International Journal of Mul...· 0 citations
The findings are that companies that implement organized governance systems record dramatic advancement in the quality of data, compliance rates, and the accuracy in analytics, and the need to incorporate governance frameworks in enterprise analytics strategies to promote sustainable data-driven change is highlighted.
Jessica Rachel Brown· International Journal of App...· 0 citations