Competing in the Age of AI

Artificial Intelligence, Innovation and Economic Growth and Competition Policy and Antitrust

Article Snapshot

Author(s)

Marco Iansiti and Karim R. Lakhani

Source

Harvard Business Review, January-February 2020

Summary

Artificial Intelligence (AI) enables the rapid growth of a new type of firm. Many traditional firms now compete directly with AI-based firms. Business strategies and competitive processes are changing.

Policy Relevance

Traditional businesses should transition to new AI-based models. Organizations based on specialized “silos” will be less effective.

Main Points

  • AI enables the growth of a new kind of firm, which delivers value without traditional workers, supervisors, or customer service representatives; instead, valuable products and services are provided by algorithms, digital automation, or by connecting many providers outside the firm.
     
  • Examples include large firms such as Ant Financial, Google, Facebook, and many smaller firms; AI sets prices on Amazon, recommends songs on Spotify, and qualifies borrowers for Ant Financial loans.
     
  • The core of these new firms is an "AI factory" that converts data into predictions and insights, guiding the firm’s workflow.
     
  • With traditional business models, large firms tend to enjoy lower costs than small firms, known as gains from scale; AI-driven firms can expand in scale further and faster than traditional firms.
     
  • Traditional firms are organized into "silos," specialized structures that keep data and analysis fragmented; AI-driven businesses like Google Ads avoid silos and favor integrated data and software development.
     
    • Traditional firms like Nordstrom and Visa are making a transition to an integrated AI-driven approach.
       
    • Microsoft chose leaders with product development experience to reorganize itself into an AI-driven firm.
       
  • Increasingly, firms will gain competitive advantage less from specialization and more from a universal set of capabilities in data collection, data analysis, and algorithm development.
     
  • Digital operating systems can aggregate harm as well as value.
     
    • One mistake can expose an entire digital network to cyberattack, or perpetuate bias or misinformation.
       
    • The unconstrained growth of AI-based systems can increase risk and threaten equality.
       

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