Respondents demographic data
| Description | No | % |
|---|---|---|
| Age | ||
| 51–60 | 2 | 1.6 |
| 41–50 | 57 | 46.7 |
| 30–40 | 63 | 51.6 |
| Total | 122 | |
| Gender | ||
| Men | 61 | 50.0 |
| Women | 61 | 50.0 |
| Total | 122 | |
| Years of experience | ||
| +29 | 1 | 0.8 |
| 21–29 | 26 | 21.3 |
| 16–20 | 52 | 42.6 |
| 10–15 | 43 | 35.2 |
| Total | 122 | |
| Job position | ||
| Executive | 37 | 30.3 |
| Top manager | 85 | 69.7 |
| Total | 122 | |
| Industry | ||
| Financial services | 4 | 3.3 |
| Industrial sector | 4 | 3.3 |
| Logistics | 3 | 2.5 |
| Manufacturing | 3 | 2.5 |
| Nonprofit organization | 5 | 4.1 |
| Other | 43 | 35,2 |
| Public sector | 11 | 9.0 |
| Retail | 5 | 4.1 |
| Services/consulting | 21 | 17.2 |
| Technology | 23 | 18.9 |
| Total | 122 | |
| AI experience | ||
| Advanced | 107 | 87.7 |
| Intermediate | 15 | 12.3 |
| Total | 122 | |
| Description | No | % |
|---|---|---|
| 51–60 | 2 | 1.6 |
| 41–50 | 57 | 46.7 |
| 30–40 | 63 | 51.6 |
| Men | 61 | 50.0 |
| Women | 61 | 50.0 |
| +29 | 1 | 0.8 |
| 21–29 | 26 | 21.3 |
| 16–20 | 52 | 42.6 |
| 10–15 | 43 | 35.2 |
| Executive | 37 | 30.3 |
| Top manager | 85 | 69.7 |
| Financial services | 4 | 3.3 |
| Industrial sector | 4 | 3.3 |
| Logistics | 3 | 2.5 |
| Manufacturing | 3 | 2.5 |
| Nonprofit organization | 5 | 4.1 |
| Other | 43 | 35,2 |
| Public sector | 11 | 9.0 |
| Retail | 5 | 4.1 |
| Services/consulting | 21 | 17.2 |
| Technology | 23 | 18.9 |
| Advanced | 107 | 87.7 |
| Intermediate | 15 | 12.3 |
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