Table 2.
Perceived barriers to implementation and use of artificial intelligence (N=40).
| Ranking | Barrier | Total participants in agreement and sample percentages, n (%)a |
| 1 | Lacking resources (staff, knowledge, and financial) | 36 (90) |
| 2 | Lacking compatibility or interoperability with existing IT infrastructure | 33 (83) |
| 3 | Quality of data | 30 (75) |
| 4 | Availability of data | 26 (65) |
| 5 | Ethical aspects (eg, liability issues) | 24 (60) |
| 6 | Product range on the market | 23 (58) |
| 7 | Data protection | 22 (55) |
| 7 | Quantity of data | 22 (55) |
| 8 | Legal regulations | 19 (48) |
| 9 | Consent of the work council | 15 (38) |
| 10 | Corporate culture | 13 (33) |
| 11 | User (eg, physicians, nurses, and administration) acceptance | 9 (23) |
| 12 | Leadership acceptance | 4 (10) |
| 12 | Patient acceptance | 4 (10) |
aResponses of “agree” or “rather agree” were grouped together.