Technologically intensive SMEs and AI: determinants of the growing demand for specialized training profiles

This paper analyzes the determinants of the demand by technologically intensive SMEs for profiles trained in artificial intelligence (AI). The study is based on the Theory of Skill-Biased Technological Change (SBTC), which posits that AI increases the demand for highly skilled workers while making routine skills obsolete. The sample includes 238 SMEs, selected for their integration of AI and diversity in terms of size and sectors. These companies, although local, are innovation-oriented and internationally open, allowing for the assessment of AI’s effects beyond major economic hubs. The adopted methodology is based on an econometric model using Ridge Regression. The results show that companies where AI complements human skills actively seek specialized profiles. The automation of routine tasks and the transformation of business models also contribute to this increased demand. Conversely, government support does not have a significant impact. Moreover, larger companies and those focused on exports exhibit a stronger need for qualified profiles.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-04
DOI
https://doi.org/10.5281/zenodo.14034446
Primary Topic
Firm Innovation and Growth
Type
article
Field-Weighted Citation Impact
0.00
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article

Technologically intensive SMEs and AI: determinants of the growing demand for specialized training profiles

Zenodo (CERN European Organization for Nuclear Research)
Firm Innovation and Growth
article

Technologically intensive SMEs and AI: determinants of the growing demand for specialized training profiles

article en

Abstract

This paper analyzes the determinants of the demand by technologically intensive SMEs for profiles trained in artificial intelligence (AI). The study is based on the Theory of Skill-Biased Technological Change (SBTC), which posits that AI increases the demand for highly skilled workers while making routine skills obsolete. The sample includes 238 SMEs, selected for their integration of AI and diversity in terms of size and sectors. These companies, although local, are innovation-oriented and internationally open, allowing for the assessment of AI’s effects beyond major economic hubs. The adopted methodology is based on an econometric model using Ridge Regression. The results show that companies where AI complements human skills actively seek specialized profiles. The automation of routine tasks and the transformation of business models also contribute to this increased demand. Conversely, government support does not have a significant impact. Moreover, larger companies and those focused on exports exhibit a stronger need for qualified profiles.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 32%
Firm Innovation and Growth
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