Strategically managing the artificially intelligent firm

Abstract

Purpose Artificial Intelligence is a general-purpose technology that is bound to affect every industry. To develop successful corporate and business strategies with AI, leaders have to capture the technological opportunity, understand the economics of AI and lead organizational change. Design/methodology/approach What to do with AI? How to set up for AI? Where is the value? Initial answers to these three fundamental questions are derived based on an interdisciplinary and integrated literature review. Findings AI leaders pursue competitive advantage by taking up the technological offer to predict-prescribe-automate, they enact machine learning by entering into a portfolio of experiments within a modular strategic framework, they organize the business to form of man-machine teams following the concept of human-agent collectives and they avoid falling victim to exponential growth bias. Practical implications In a business environment where the cognification of everything will lead to exponential growth of both, volume of data and intelligence of machines, it will be paramount for strategic leaders to have a robust AI strategy in place and to develop the competencies required for managing the Artificially Intelligent Firm. Originality/value This overview enables strategic leaders to prepare themselves and their organizations for AI. It spearheads making required connections between technology, economics and management of AI.

Üretken Yapay Zekâ Ve Pazarlama Strateji̇leri̇: Swot Anali̇zi̇ Perspekti̇fi̇

“…İlaveten YZ teknolojisinin hızla ilerlemesi, pazarlama stratejilerinin ve araçlarının eskimesine yol açabilir ve gelişen YZ yeteneklerine ayak uydurmak için sürekli adaptasyon ve güncelleme gerektirebilir (Wagner, 2020).…”

Profiting from innovation in the aftermath of an economic crisis

“…With regard to product and service innovations, for example, a firm's solutions may increasingly build on customer-specific data to optimally satisfy customer needs (Shukla et al, 2017). In addition, a firm may rely on process and management innovations, such as involving data analytics as a key part of managerial decision-making, for example in assessing the risks of investment decisions (Wagner, 2020). With respect to business model and organization innovations, companies may start to offer predictive analytics and maintenance solutions based on the additional data and new organization structures (Berman, 2012;Lichtenthaler, 2020).…”

Effective integration of artificial intelligence: key axes for business strategy

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