Engineering Value: The Returns to Technological Talent and Investments in Artificial Intelligence

Abstract

Employees with technological skills are highly complementary to the intangible knowledge assets that firms accumulate. This paper describes how technical talent is a source of rents for corporate employers, particularly for the case of Google’s surprising open source launch of TensorFlow, a deep learning software package. First, I present a simple model of how employers intangible assets expose them to the returns to their employees’ skill acquisition efforts. Then, using over 180 million position records and over 52 million skill records from LinkedIn, I build a panel of firm-level skills to measure the market value of exposure to newly available deep learning talent. AI skills are strongly correlated with market value, though variation in AI skills from 2014-2017 does not explain contemporaneous revenue productivity within firms. AI-intensive companies rapidly gained market value following the launch of TensorFlow, while companies with opportunities to automate relatively larger quantities of labor with machine learning did not. Using a difference-in-differences approach, I show that the TensorFlow launch is associated with an approximate market value increase of $11 million per 1 percent increase in AI skills for AI-using firms. AI superstar firms in the top quintile also appear to benefit more over the sample period than less intensive adopters. These results suggest that the primary mechanism responsible for the market valuation increases of AI adopters at the time of the AI skill shock from TensorFlow is a revaluation of existing firm-specific technology-exposed assets.

Keywords: Artificial Intelligence, Intangible Capital, Labor Investments, TensorFlow

JEL Classification: J24, M15, M21, D24