Scientists studied thoroughly the phenomenon of information and communication technologies’ impact on productivity. In 1987 Sollow summarized the puzzle with the well-known conclusion—“You can see the computer age everywhere but in the productivity statistics”. It took two decades for businesses to develop a so-called intangible capital concept composed of human, organizational capital, and new process knowledge needed to achieve effectiveness with ICT implementation. Recent advancements of digital technologies created a similar pattern issue with large investments into Artificial Intelligence, big data, and other technologies but very limited economic returns. The innovativeness of this paper is based on the analysis of 3 large-scale digitalization programs with AI as a leading tool that was expected to provide the largest return on investment. Key failure factors are analyzed that impeded the organizations to reach planned results and return on investments. Three factors were identified as primary obstacles for the success of comprehensive AI-based solution implementations—complexity, managerial capability, and compatibility.

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The Sharp-Knife Theory of Artificial Intelligence Evidence from the AI Productivity Paradox

  • Yury Pukha

摘要

Scientists studied thoroughly the phenomenon of information and communication technologies’ impact on productivity. In 1987 Sollow summarized the puzzle with the well-known conclusion—“You can see the computer age everywhere but in the productivity statistics”. It took two decades for businesses to develop a so-called intangible capital concept composed of human, organizational capital, and new process knowledge needed to achieve effectiveness with ICT implementation. Recent advancements of digital technologies created a similar pattern issue with large investments into Artificial Intelligence, big data, and other technologies but very limited economic returns. The innovativeness of this paper is based on the analysis of 3 large-scale digitalization programs with AI as a leading tool that was expected to provide the largest return on investment. Key failure factors are analyzed that impeded the organizations to reach planned results and return on investments. Three factors were identified as primary obstacles for the success of comprehensive AI-based solution implementations—complexity, managerial capability, and compatibility.