Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Harvard Business Review Press. Boston, MA.
The age of AI is coming. It may have just begun. The new digital economy involves economies of scale, scope, and learning. Through big data, algorithms, software, and computing power, digital companies attempt to transform themselves into firms possessing AI factories based on AI-driven and data-centric operating models. Companies industrializing data collection, analysis, and decision-making include e-commerce giant Amazon, Alibaba’s financial company Ant Financial, British food delivery company Ocado, American fitness company Peloton, and Google. "While Ant Financial exclusively provides information-based services, Ocado delivers products with a highly efficient supply chain, and Peloton offers a well-integrated product-service combination” (p.49).
However, these companies operate beyond specific industries. Instead, they expand across industry boundaries. On the other hand, traditional companies have industrialized production, but analysis and decision-making still remain traditional and isolated processes. This includes phone companies like Nokia, Motorola, BlackBerry, and Blockbuster in video distribution and production, Viacom in the video sector, large retailers in malls and retail, and GE, which is half successful in the digital realm. In reality, "Amazon and Tencent have competitiveness in heterogeneous industries such as messaging and financial services, video games and consumer electronics, healthcare, and credit rating" (p.207). These can be seen as hub companies in the AI era. Consequently, "the emphasis on differentiation in terms of cost, quality, and brand assets is shifting from specialized vertical expertise to positioning in networks, accumulation of differentiated data, and deployment of next-generation analytics" (p.207).
Now, new challenges like individual consumer privacy, cyber threats and misinformation, and economic inequality have emerged for hub companies and society as a whole. Especially, issues like privacy and antitrust are very challenging for hub companies. To prevent monopolistic dominance by hub companies, open-source software will continue to emerge in diverse forms, from databases like MySQL to user interface libraries like Facebook's REACT, and the almost ubiquitous machine learning framework TensorFlow. Another positive trend for the future is that cloud services can facilitate the transformation into data-driven AI companies at lower costs.
On the other hand, open participation by the general public and the innovation community will be another way to address these issues. For example, "bias on Wikipedia tends to diminish over time as multiple contributors correct it" (p.225). In this context, leadership through collective wisdom is necessary. Particularly, the healthy networks of hub companies like Alphabet, Microsoft, Facebook, Alibaba, Amazon, and Tencent are crucial because they can bring collective health to the entire ecosystem.
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About the author Dr. Phil Yang: Chairman of CKT Group; CEO of MAILab; China Qingdao Municipal Government Economic Ambassador; Advisor, Tsinghua University Foundation, China; Adjunct Professor, Tsinghua University, China; International President of Jilin Vocational University, China; New York State University, Korea Branch, Chair Professor; Director, Konkuk University's Chinese Enterprise Research Institute
MAILab www.mailab.co.kr: MAILab commercializes AI solutions for quarantine, security and safety with QSS integrated solution based on its own engine i2Brain, Vision AI Framework, MEGA Image AI Platform, and MEGA Industrial AI Platform through engineering and marketing organizations in the United States, Canada, China and India. MAILab offers Industrial AI such as QSS Integrated Solution, Medical AI such as congenital heart disease algorithm, Logistic AI such as Robotic AI Fulfillment Service, Beauty AI for sales and production of skin care and makeup products.
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