Strategic Use of Modern AI and Data Empowered Information Systems

In this age of rapidly evolving AI- and data-driven business insights, managers must engage in modern intelligent information systems (IS) decisions because successful management in today’s digital landscape requires a deep understanding of technology and its implications for business strategy. Unlike in the past, when IT solely focused on management decisions, organizations now face the challenge of developing comprehensive digital strategies that integrate various technological channels. The rapid evolution of technology, highlighted by the impact of companies engaged in innovation and disruption, shows that effective IS management is crucial to avoid being overtaken by market changes and dynamic AI-driven competition. Managers need to recognize that personal technological experience does not equate to proficiency in AI-driven enterprise-level IS, which demands a unique skill set that encompasses security, privacy, and regulatory considerations.

This text starts with Chapter 1, where a modern information strategy network is discussed that drives contemporary business utilizing legacy IS systems as well as modern AI- and data-driven insights. Chapter 2 introduces the reader to the strategic use of information resources and intelligence. Emphasis is placed on AI-powered dynamic intelligence coming from generative and agentic (or autonomous) technologies. Chapter 3 explores organizational strategy and IS in the age of AI. The productivity revolution and resulting organizational changes are significant in modern businesses as we move toward 2030 and beyond. Chapter 4 discusses intelligent digital systems, the Internet of Things, and the

Work Design Framework as we transform from traditional IS to intelligent environments influenced by AI and data. Chapter 5 provides a deep dive into AI- and data-empowered IS and digital transformation, which are taking center stage in the IT productivity revolution. The modern intelligent architecture and infrastructure described in Chapter 5 provide a glimpse of the worldwide AI infrastructure expansion driven by enormous data engineering needs. Chapter 6 discusses modern intelligent architecture and infrastructure as we move from legacy IS systems to AI-powered intelligent systems. We then focus on security, privacy, and ethical issues as we embrace AI and data from heterogeneous sources in Chapter 7. In Chapter 8, we discuss the business aspects of information technology in the age of AI and data empowerment. Governance related to IS, organizations, and data is the focus of Chapter 9. Special attention is placed on AI governance, the new paradigm in IS. Global intelligent IS sourcing and integration are explained in Chapter 10, including the influence of AI in outsourcing. Chapter 11 discusses managing modern IT projects in the new IS landscape with data empowerment and AI.

In Chapter 12, dynamic business intelligence, knowledge management, KPIs, and analytics are explained in relation to evolving AI- and data-driven insights that are driving modern businesses. Finally, Chapter 13 concludes with AI- and data-empowered IS strategy for competitive advantage and disruption through AI and related data engineering technologies.

Throughout the text, numerous mini cases are used to explain how real-world businesses use these strategies. At the end of each chapter, two major case studies provide detailed examples of the concepts and strategies.