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Slower World Growth or Global Recession with the Trade War? Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Artificial Intelligence, Its Corporate Use and How It Will Affect the Future of Work

Author : Jacques Bughin

Published in: Capitalism, Global Change and Sustainable Development

Publisher: Springer International Publishing

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Abstract

In the current debate over the Future of Work, there is little discussion about how firms anticipate the evolution of their demand for labor and the related mix of skills as they adopt Artificial Intelligence (AI) tools. This article contributes to this debate by leveraging a global survey of 3000 firms in 10 countries, covering the main sectors of the economy. Descriptive statistics from the survey are complemented by econometric analyses of corporate labor demand decisions. The findings are four-fold. First, those are still early days in the absorption of AI technologies, with less than 10% of companies investing in a majority of AI technologies and for multiple purposes. Second, if an aggregate portion of firms anticipates reducing employment as a result of adopting AI technologies, as many other companies anticipate labor growth or reorganizing employment. Third, this reallocation picture holds true when we examine further demand by labor functions and skills, with talent shifting toward more analytic, creative, and interaction skills, and away from administrative and routine-based functions, in line with past trends of skill- and routine-biased technological change. Fourth, a novel to the literature on Future of Work, econometric results on employment change highlight that employment dynamics are driven by related spillover effects to product markets. Higher competition, larger expectations of market (share) deployment may counterbalance negative automation effect on employment dynamics.

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Footnotes
1
Discussion with Mark Purdy from Accenture research at the G-20Y in Evian, Sept.
 
2
See A future that works: Automation, employment, and productivity, McKinsey Global Institute, January 2017.
 
3
As a case in point, let us consider the Associated Press news agency, which used to deliver reports on large corporations using 65 journalists in its newsroom. With AI technologies, the company quickly managed to automate the production of simple stories of quarterly earnings for 10 times as many small companies in the long-tail. This output gain was not done at the expenses of reporters; the in-house reporters did not lose their jobs, but were instead redirected to write longer research article on business trends as a major latent demand spotted by the company. See for detailed reference, the article by Ramaswamy, S (2017) at https://​hbr.​org/​2017/​04/​how-companies-are-already-using-ai.
 
4
Substitution may arise when, furthermore, the economics are attractive to replace human capital for example.
 
7
We are rather keen to understand the expectations of firms as the current level of AI diffusion across all technologies is still relatively low.
 
8
Here we show results in aggregate, but the same picture is also visible by industry.
 
9
The same skill-biased tendency is also noticeable in the econometric analysis conducted by Arntz et al. (2016) linking occupations and tasks to the OECD PIACC skill database.
 
10
Note that the sample used will concern only firms which are aware of, but not necessarily adopting, AI technologies. We sub-select those firms, and survey responses on the impact on AI are likely not to be largely noisy for those respondents with limited understanding of AI technologies
 
11
With no loss of generality, we drop the suffix r hereafter.
 
12
See also Ugur et al. (2016).
 
13
The preponderance of empirical estimates on the substitution between labor and capital point to σ < 1, see Chirinko (2008).
 
14
We do not have any mean to split this variable in terms of investment objectives, however.
 
15
We do not include AILE as otherwise, we have perfect multicollinearity.
 
16
There is a case for a selection bias in the sense that we only concentrate on firms aware of AI. However, firms not aware of AI have not given data, and if yes, noisy ones, so we can not control for them. We tried a Heckman correction where we try to predict awareness or not of AI in a first step. But it is rather difficult to have specific regressor for this first step.
 
17
See however the asymmetry- in this present case, employment decline has still a positive probability; while employment increase in the previous case was nil. Everything being equal, it still suggests that employment pressure may be happening along automation.
 
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Metadata
Title
Artificial Intelligence, Its Corporate Use and How It Will Affect the Future of Work
Author
Jacques Bughin
Copyright Year
2020
Book
Capitalism, Global Change and Sustainable Development

Print ISBN: 978-3-030-46142-3

Electronic ISBN: 978-3-030-46143-0

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-46143-0_14