In Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 2018, Part III, edited by Zofia Wilimowska, Leszek Borzemski, and Jerzy Świątek • Springer International Publishing, 2018
ABSTRACT: The discipline of enterprise architecture (EA) provides valuable tools for aligning an organization’s business strategy and processes, IT strategy and systems, personnel structures, and organizational culture, with the goal of enhancing organizational agility, adaptability, and efficiency. However, the centralized and exhaustively detailed approach of conventional EA is susceptible to failure when employed in organizations demonstrating exceedingly great size, speed of operation and change, and IT complexity – a combination of traits that characterizes, for example, some emerging types of “technologized” oligopolistic megacorps reflecting the Industry 4.0 paradigm. This text develops the conceptual basis for a variant form of enterprise architecture that can be used to enact improved target architectures for organizations whose characteristics would otherwise render them “unmanageable” from the perspective of conventional EA. The proposed approach of “enterprise meta-architecture” (or EMA) disengages human enterprise architects from the fine-grained details of architectural analysis, design, and implementation, which are handled by artificially intelligent systems functioning as active agents rather than passive tools. The role of the human enterprise architect becomes one of determining the types of performance improvements a target architecture should ideally generate, establishing the operating parameters for an EMA system, and monitoring and optimizing its functioning. Advances in Big Data and parametric design provide models for enterprise meta-architecture, which is distinct from other new approaches like agile and adaptive EA. Deployment of EMA systems should become feasible as ongoing advances in AI result in an increasing share of organizational agency and decision-making responsibility being shifted to artificial agents.