Competing in the Age of AI

Marco   Iansiti; Karim R. Lakhani

Book | Forthcoming

Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World

Abstract

In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very concept of the firm. AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value.
Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have constrained business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, drive massive scope increase, enabling companies to straddle industry boundaries, and enable powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions.
When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. The authors present a framework for rethinking business and operating models; explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition and altering the structure of our economy; show how these collisions force traditional companies to change their operating models to drive scale, scope, and learning; explain the risks involved in operating model transformation and how to overcome them; and describe the new challenges and responsibilities for the leaders of these firms.
Packed with examples—including the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is the essential guide for rethinking how your firm competes and operates in the era of AI.

Keywords: artificial intelligence; Technological Innovation; Change; Competition; Strategy; Leadership; Business Processes; Organizational Change and Adaptation;

Format: Print

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Citation:

Iansiti, Marco, and Karim R. Lakhani. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Boston: Harvard Business Review Press, in press.

Working Paper | HBS Working Paper Series | 2019

Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders

Tarun Khanna, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam and Meena Hewett

This paper examines the role that the two lead authors’ personal connections played in the research methodology and data collection for the Partition Stories Project—a mixed-methods approach to revisiting the much-studied historical trauma of the Partition of British India in 1947. The Project collected survivors’ oral histories, a data type that is a mainstay of qualitative research, and subjected their narrative data to statistical analysis to detect aggregated trends. In this paper, the authors discuss the process of straddling the dichotomies of insider/outsider and qualitative/quantitative, address the “myth of informed objectivity,” and consider the need for hybrid research structures with the intent to innovate in humanities projects such as this. In presenting key learnings from the project, this paper highlights the tensions that the authors faced between positivist and interpretivist methods of inquiry, looks at the difference between “insider” and “outsider” categories of positionality, and discusses in the quantification of qualitative oral history data. The paper concludes with an illustrative example from one of the lead authors’ past research experiences to suggest that the tensions of this project are general in occurrence and global in applicability, beyond the specifics of the Partition case study explored here.

Citation:

Khanna, Tarun, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam, and Meena Hewett. "Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders." Harvard Business School Working Paper, No. 20-038, September 2019. View Details

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This case focuses on Nimbus Therapeutics, a biotechnology startup based in Cambridge, Massachusetts, as its leadership team tries to determine the company’s long-term strategy. The startup’s founders structured Nimbus as a limited liability company, which has given it more flexibility when it comes to funding and development partnerships. Does the operating structure still makes sense as Nimbus looks ahead to the future?

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Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World

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