Understanding the fundamental economics of AI

Abstract

Purpose

Despite the hype about transformative technology, the authors of “Power and Prediction: The Disruptive Economics of Artificial Intelligence” see the recent AI advances as all basically ‘better statistical techniques’ that allow us to take really big data sets and come up with more refined predictions.

Design/Methodology/Approach

University of Toronto experts, Ajay Agrawal, Joshua Gans and Avi Goldfarb explain why transformation of business model by AI will be some time in the future when we move beyond simply substituting the new technology into existing systems and start to leverage its potential to enable the reimagining of old system solutions and innovate radically new value propositions.

Findings

What economic history tells us is that technology-driven transformation does not come easy and real adoption only occurs when new systems are created.

Practical Implications

As there are likely many decisions in your organization that have been codified into rules, AI offers the potential to turn them to dynamic decisions.

Originality/Value

To realize the full potential of AI, companies need to adopt a “system mind-set,” in contrast to the “task-level thinking” that still predominates in most companies.

Citation

Leavy, B. (2023), "Understanding the fundamental economics of AI", Strategy & Leadership, Vol. 51 No. 2, pp. 17-23. https://doi.org/10.1108/SL-11-2022-0111