Study Reveals How Companies Source AI TechnologyAI Adoption Across European Industries: Trends and Strategies

The Advent of Artificial Intelligence

The advent of artificial intelligence has revolutionized almost every sector, spanning from manufacturing and retail to construction and agriculture. As AI continues to become more prevalent, companies are increasingly turning to off-the-shelf technology that can be tweaked to fit their specific needs.

Chris Forman, a professor at the Cornell SC Johnson College of Business, recently collaborated in a study that delved into how companies make decisions about adopting AI technology and where they source it from: by purchasing pre-made software, developing their own, or using a combination of both, which the researchers believe may indicate "complementarity" in sourcing approaches.

Industry Adoption of AI

After analyzing data from over 3,000 European firms, the researchers discovered that many industries, particularly in science, retail, finance, real estate, and manufacturing, are opting for pre-made technology that can be customized for their business. Despite the concern that AI could replace human workers, the findings suggest that individuals with AI-related skills will still be in demand.

"In most industries, companies are utilizing both pre-made and in-house development, and it would be interesting for future research to explore the reasons behind this," said Forman, who co-authored the study Make or Buy Your Artificial Intelligence? Complementarities in Technology Sourcing published in the Journal of Economics and Management Strategy.

Forman emphasized the importance of pre-made software, but noted that for the majority of companies, it is not a substitute for in-house development, indicating that it will not eliminate the need for AI-related skills in the short term. The study's corresponding author is doctoral student Charles Hoffreumon from the Solvay Brussels School of Economics and Management, and the other co-author is Professor Nicolas van Zeebroeck, an expert in digital economics and strategy at the same institution.

Collection of Data

To collect data for their research, the team used a survey conducted in 2020 by the European Commission's Directorate-General of Communications Networks, Content and Technology which assessed the adoption of AI across all 27 countries in the European Union. The study focused on data from 3,143 firms across various industries.

The implementation of business software is notoriously difficult, and companies have historically relied on pre-made solutions as new technologies emerge. "This aspect of understanding the extent to which pre-made software could potentially replace the need for certain skills was intriguing," Forman stated.

Industry Representation

The study's data included companies from 10 different industries, with the largest representation from manufacturing (19%), retail and trade (18%), and construction (12%). The smallest number of respondents came from the agriculture (4%) and utilities (3%) industries. The most common uses for AI among respondents included fraud or risk detection, process optimization, and automation in warehouses or robotics.

Among those who had implemented at least one AI application, over 58% reported using pre-made software, while nearly 38% hired an external consultant, 24% used modified commercial software, 20% developed their own software, and 20% adapted open-source technology to fit their needs. Some companies utilized a combination of these approaches.

The study also found that the financial and scientific sectors, along with IT, tended to develop and customize their own software, while agriculture, construction, and human health favored pre-made solutions.

Labor Demand in Relation to AI

Forman noted that, historically, the adoption of new technology leads to an increased demand for certain types of skills. "Overall, labor demand usually goes up," he explained, "but it remains to be seen if this will be the case with AI."

As with many new technologies, Forman explained, early adopters often incorporate best practices into pre-made software, making these solutions even more effective. This was the case with enterprise resource planning, a type of automation software used to run an entire business.

"When we look at previous digital technologies, there is typically a process of complementary innovation, where we figure out the most effective way to use the technology for our company," Forman stated. "This usually happens over time through experimentation and trial and error."

The authors of the study wrote that their research "has taken the first steps toward highlighting the importance of sourcing strategies in understanding the spread of AI."

David Lamy
David Lamy Author
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