Using Artificial Intelligence in Care – an ambivalent attitude

The attitude of nurses towards the use of artificial intelligence in clinical practice remains ambivalent. It ranges from the hope that artificial intelligence will revolutionise the profession to fear for their own jobs.

In view of the ongoing shortage of skilled labour, nurses* are exposed to a high workload 1. Not only is there a shortage of carers, it is also difficult to recruit and retain qualified staff 2. It can be observed that the quality of nursing care and patient satisfaction are beginning to suffer due to the shortage of skilled staff.

Innovative and forward-looking approaches are needed that offer concrete and recognisable relief and support options for nursing staff. One approach could be the use of artificial intelligence (AI) in the nursing care of patients. An AI that “improves human performance in a narrowly defined task area for which it has been specially trained.” 3 Functioning AI applications, albeit often still in laboratory situations or pilot phases, include, for example, predictions regarding infection events, wound treatment, rehospitalisation, falls or even recommendations on staffing requirements or the risk of burnout among nursing staff 4. AI systems can take on administrative tasks in nursing care, e.g. in documentation, e.g. use of terminology, data quality or nursing process control, or the monitoring of patients, i.e. alerts combined with condition analyses and recommendations.

Although AI applications can bring numerous benefits for patient care, such applications are still struggling to find their way into everyday clinical practice 4,5. Apart from technical developments, there is often a lack of high-quality data sets to train AI 3. Another problem is that healthcare professionals are often barely involved in the development, testing and implementation of AI applications 4. However, it is also particularly important that only a favourable acceptance profile of the users, i.e. healthcare professionals, can have a positive influence on technology adoption 6. It was therefore interesting to investigate what evidence can be found on the attitudes of nurses towards AI applications in everyday clinical work.

AI systems and the attitudes of nurses

The literature shows that nurses are ambivalent about the use of AI systems in nursing. Carers hope that AI systems will relieve them of administrative or routine tasks. 7,8 For example, robots could show new employees rooms or explain equipment relevant to medical treatment. From the carers’ perspective, the positive aspect is that repetitive and clearly structured tasks and processes are supported and taken over by AI, allowing them to spend more time caring for their patients and their relatives 8. They are sceptical about other applications, such as a robot bathtub, as they do not perceive these as relieving the burden or see any ergonomic benefits 9.

In addition to being used for routine tasks, carers also see the use of AI systems as useful for tasks that serve patient safety. For example, patients can be monitored around the clock both in institutions and at home by AI systems that trigger an alarm in an emergency 7,8,10. The number of medical errors can also be reduced if AI systems check or support certain actions, such as in paediatrics, where robots are used to dose medication. However, carers point out that the devices must be regularly maintained and staff must be trained to use them in line with technological advances 8.

Carers see a further benefit of AI systems in supporting patients, e.g. in reminding them to take their medication or supporting them during sporting activities 10. However, carers are still rather critical of the emotional support of patients, as they consider the ability of AI systems to empathise with patients to be unrealistic 8,11. Nevertheless, they can imagine that robots could, for example, reassure patients if carers are not immediately available 8,10.

More human – but how?

AI has great potential to humanise the care sector. By automating and simplifying repetitive, administrative, monitoring or early detection tasks using AI systems, carers can once again focus on their core business, the patient. However, this also means that the resources that are freed up, i.e. where AI systems take over, really benefit the person, i.e. the interaction between carer and patient, and are not ‘filled’ by other administrative or similar tasks. The interaction should be allowed to last longer and take place more frequently, e.g. during assessment, in clarifying needs, in dealing with difficult psychological or social situations or in enabling people to cope with an illness in everyday life, as well as in promoting individual health literacy.

The use of AI systems can contribute to a high quality of care, especially if data is systematically analysed and made available so that care professionals and the interdisciplinary team can make ‘better’ decisions. AI systems can also help to counteract the shortage of skilled labour if, as mentioned, nurses once again have adequate time for people, i.e. for interaction with the patient, which was often a reason why nurses entered the profession.


An ambivalent and cautious attitude towards AI systems still seems to prevail in the nursing profession. It can be assumed that there is often a lack of knowledge and that concrete experience and testing opportunities are rare. Institutions, their nursing staff and managers are called upon to get involved in the discourse and co-development. An ambivalent attitude is not a problem as long as it hinders or even prevents the co-development of AI systems relevant to care. Then others will do it.


  1. Peter, K. A., Hahn, S., Schols, J. M. G. A. & Halfens, R. J. G. Work-related stress among health professionals in Swiss acute care and rehabilitation hospitals – A cross-sectional study. J. Clin. Nurs. 29, 3064-3081 (2020).
  2. Hahn, S. & Golz, C. Together against the shortage of skilled labour. NOVAcura 50, 18-21 (2019).
  3. Riedl, R. What artificial intelligence is already doing in healthcare today. SocietyByte (2023).
  4. O’Connor, S. et al. Artificial intelligence in nursing and midwifery: A systematic review. J. Clin. Nurs. 32, 2951-2968 (2023).
  5. Topol, E. J. Deep medicine: how artificial intelligence can make healthcare human again. (Basic Books, 2019).
  6. Thilo, F. J., Hahn, S., Halfens, R. J., Heckemann, B. & Schols, J. M. Facilitating the use of personal safety alerting device with older adults: The views, experiences and roles of relatives and health care professionals. Geriatr. only (Lond.) 42, 935-942 (2021).
  7. Taryudi, T., Lindayani, L., Purnama, H. & Mutiar, A. Nurses’ View towards the Use of Robotic during Pandemic COVID-19 in Indonesia: A Qualitative Study. Open Access Maced. J. Med. Sci. 10, 14-18 (2022).
  8. Liang, H.-F., Wu, K.-M., Weng, C.-H. & Hsieh, H.-W. Nurses’ Views on the Potential Use of Robots in the Pediatric Unit. J. Pediatr. Nurs. 47, e58-e64 (2019).
  9. Beedholm, K., Frederiksen, K., Frederiksen, A. S. & Lomborg, K. Attitudes to a robot bathtub in Danish elder care: A hermeneutic interview study. Nurs. Health Sci. 17, 280-286 (2015).
  10. Papadopoulos, I., Koulouglioti, C. & Ali, S. Views of nurses and other health and social care workers on the use of assistive humanoid and animal-like robots in health and social care: a scoping review. Contemporary Nurse 54, 425-442 (2018).
  11. Abdullah, R. & Fakieh, B. Health Care Employees’ Perceptions of the Use of Artificial Intelligence Applications: Survey Study. J. Med. Internet Res. 22, e17620 (2020).

* Nursing staff, healthcare professionals, nursing assistants

Creative Commons Licence

AUTHOR: Larina Schenk

Larina Schenk wrote her bachelor's thesis on "Artificial intelligence in nursing - the attitude of nursing staff" as part of her degree programme in nursing at BFH. With this topic, she wanted to combine her technical interest, which she brought with her from her previous training as a structural draughtswoman, with a nursing topic. She is currently training to become a paramedic.

AUTHOR: Sabrina Gröble

Sabrina Gröble is a research associate in the "Psychosocial Health" innovation field, aF&E Nursing, BFH Health. She studied health sciences and technology and worked in the field of robotics in paediatric neurorehabilitation. Her research focuses on migration, homelessness, equal opportunities and ageing.

AUTHOR: Friederike J. S. Thilo

Prof. Dr Friederike Thilo is Head of Innovation Field "Digital Health", aF&E Nursing, BFH Health. Her research focuses are: Design collaboration human and machine; technology acceptance; need-driven development, testing and evaluation technologies in the context of health/disease; data-based care (artificial intelligence).

Create PDF

Related Posts

None found

0 replies

Leave a Reply

Want to join the discussion?
Feel free to contribute!

Leave a Reply

Your email address will not be published. Required fields are marked *