| Title: | Unveiling Organizational AI Adoption Patterns in Italian Companies through the Lens of the Diffusion of Innovations Theory |
|---|
| Authors: | ID Garlatti Costa, Grazia (Author)
ID Venier, Francesco (Author)
ID Pugliese, Roberto (Author) |
|---|
| Files: |  https://ojs.upr.si/index.php/fm/article/download/172/82
 MGT_Garlatti_Costa_Grazia_2025.pdf (574,55 KB)
MD5: D3CB9FD99B623CE29351572D7C42A924
|
|---|
| Language: | English |
|---|
| Work type: | Article |
|---|
| Typology: | 1.01 - Original Scientific Article |
|---|
| Organization: | ZUP - University of Primorska Press
|
|---|
| Abstract: | This paper investigates the adoption and integration of artificial intelligence (AI) technologies within a sample of 237 Italian enterprises using the Diffusion of Innovations (DOI) theory as the theoretical framework. It examines the characteristics of companies leading in AI adoption, evaluating their alignment with the innovator and early adopter profiles defined by Everett Rogers in 2003 within the DOI framework. The research emphasizes AI’s significant role in enhancing operational efficiency, fostering innovation, securing competitive advantage, and driving long-term growth. It also identifies challenges such as lack of skills, data management issues, and ethical concerns. Our findings contribute empirical evidence to the academic literature on the DOI theory, addressing the underexplored context of AI in Italy. The study provides a nuanced perspective on AI’s impact on employment and sets a foundation for future research, offering managerial insights for strategically deploying AI.
|
|---|
| Keywords: | artificial intelligence, diffusion of innovations theory, early adopters, implementation challenges, Italian companies |
|---|
| Publication status: | Published |
|---|
| Publication version: | Version of Record |
|---|
| Publication date: | 29.03.2025 |
|---|
| Year of publishing: | 2025 |
|---|
| Numbering: | Vol. 23, no. 1 |
|---|
| PID: | 20.500.12556/RUP-22247  |
|---|
| eISSN: | 1854-6935 |
|---|
| DOI: | https://doi.org/10.26493/1854-6935.23.79-111 |
|---|
| Publication date in RUP: | 18.12.2025 |
|---|
| Views: | 167 |
|---|
| Downloads: | 0 |
|---|
| Metadata: |    |
|---|
|
:
|
Copy citation |
|---|
| | | | Average score: | (0 votes) |
|---|
| Your score: | Voting is allowed only for logged in users. |
|---|
| Share: |  |
|---|
Hover the mouse pointer over a document title to show the abstract or click
on the title to get all document metadata. |
