Should you make an AI or just buy one? A new study might have the answer

Many companies across various industries are embracing artificial intelligence (AI) technology, leading to significant changes in their operations. Chris Forman, a professor at the Dyson School of Applied Economics and Management in the Cornell SC Johnson College of Business, co-authored a study investigating firms' decisions regarding AI adoption and their sourcing strategies.

The study, titled "Make or Buy Your Artificial Intelligence? Complementarities in Technology Sourcing," examined over 3,000 European firms, particularly in sectors such as science, retail trade, finance, real estate, and manufacturing. It found that many of these firms are opting for off-the-shelf AI technology that can be customised to their specific needs. Despite concerns about AI threatening human jobs, the research suggests that workers with AI-related skills will remain in demand.

Forman emphasised the importance of both ready-made software and in-house development, noting that for most firms, one does not replace the other. This indicates that ready-made software does not eliminate the need for AI-related skills in the short term.

The study, authored by Forman, along with Charles Hoffreumon and Nicolas van Zeebroeck, analysed data from a survey conducted by the European Commission (EC) across the 27 countries of the European Union in 2020. It revealed that firms across various sectors are utilising AI for purposes such as fraud detection, process optimization, and automation.

While some industries, like finance and science, prefer developing their own software, others, such as agriculture and construction, lean towards ready-made solutions. The data highlighted the diverse approaches to AI adoption among different sectors.

Historically, as new technologies emerge, firms have relied on ready-made software, but the study suggests a shift towards customised AI solutions. It also underscores the importance of sourcing strategies in understanding the diffusion of AI technology across industries.

Forman noted that, similar to previous digital technologies, AI adoption involves a process of complementary innovation, where firms experiment to find the most effective ways to utilise the technology. This iterative process contributes to the refinement of ready-made software solutions over time.

Overall, the study sheds light on the evolving landscape of AI adoption in various industries and emphasizes the role of both off-the-shelf and in-house AI solutions in driving innovation and efficiency.

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