Potentials, risks and implications of AI-driven Strategic Foresight in disruptive environments - A framework for companies to exploit new opportunities and remain resilient

This thesis aims to identify potentials, risks, and implications arising from the implementation of AI-driven Strategic Foresight in a disruptive corporate environment. The central hypothesis of this thesis is that the integration of AI-supported foresight components can enhance a company's resilience and competitiveness in volatile, uncertain, complex, and ambiguous (VUCA) environments. The highly dynamic and uncertain global environment demands a paradigm shift in strategic planning and decision-making. Consequently, Strategic Foresight has evolved from a discretionary luxury to a critical survival skill for contemporary companies. However, contemporary approaches to Strategic Foresight are characterised by a manual, slow and reactive nature, leaving organizations inadequately equipped to anticipate disruptions or capitalize on emerging opportunities. Strategic Foresight is set to undergo a substantial transformation and disruption in the wake of generative Artificial Intelligence. While AI offers transformative potential by enhancing the ability to analyse trends, model scenarios, and support decision-making, its adoption remains fraught with challenges. The central objective of this thesis is to provide guidance for the enhancement of organisational Strategic Foresight through the utilisation of AI. The scope of the thesis encompasses the delineation of the framework of AI-driven Strategic Foresight, with a focus on the main components and the manner in which these components function collectively to facilitate proactive, AI-supported decision-making. This thesis will provide a comprehensive analysis of the potential benefits, challenges, and risks associated with AI-driven Strategic Foresight. Moreover, the thesis aims to make a contribution to the identification of requirements and implications of AI-driven Strategic Foresight for organizations. This master's thesis is predicated on a thorough review of the extant literature, supplemented by a set of expert interviews dedicated to a specific topic. The prevailing consensus in the academic literature is that AI is a crucial competitive necessity for effective data collection, processing and predictive analytics in the context of massive internal and external datasets as well as the management of disruptive conditions. Beneficial uses cases comprise advanced analytics for market evaluations, competition mapping, the identification of emerging opportunities, simulated test of strategic alternatives and continuous monitoring mechanisms assessing plan relevance against external shifts. Practitioners specializing in foresight, market intelligence, and business intelligence have observed the dissolution of boundaries among these disciplines. This phenomenon can be attributed to the emergence of synergies that transcend traditional disciplinary boundaries. A considerable number of experts advocate for a synergistic integration of these domains within the context of AI. Despite the technical ability of AI systems in making informed decisions through mathematical optimization processes, particularly through the integration of symbolic AI andTU Wien MBA | Strategic Management & Technologymodern AI to form hybrid AI algorithms, there is a consensus among research, industry, and society that the ultimate decision-making authority should always reside with humans. In light of these challenges, scholars have proposed a synergistic, hybrid approach for future foresight. The integration of human expertise, which encompasses the capacity to navigate ethical dilemmas, generate creative solutions, and comprehend intricate social dynamics, with AI’s data processing and analytical capabilities, is central to this approach. Furthermore, the democratization of Strategic Foresight, facilitated by AI and automation, is regarded as a significant transformative development in the domain. This development will enable the generation of insights at scale, making them more accessible to a broader audience while still allowing for individualization and high-quality results. It is further anticipated that a major development in the foresight industry in the forthcoming decade will be the emergence of in-house foresight expertise, manifesting in companies increasingly focused on building their own foresight capabilities. In this context, the advent of AI tools is revolutionizing the way information is processed and analysed, offering organizations the ability to gather insights at a faster pace while reducing costs. Thereby it equips companies with the fundamental instruments requisite for sustaining competitiveness and fortifying their resilience.