
Hospitals around the globe are facing a mounting nursing shortage, which the World Health Organization estimates to reach 4.5 million by 20301, if the current pattern continues. The reason for the nurses’ shortages, among many things, is burnout, safety issues, and poor pay.
Additionally, frustration amongst the nursing community is rising over an increasing number of tasks preventing them from spending sufficient time on face-to-face patient care. A study found that nurses reported spending only 54%2 of their time on direct patient care and wished to devote more time to this.
Administrative tasks in particular take up a significant proportion of nurses’ time, however, these tasks have the potential to be removed from nurses’ loads through the use of AI-powered assistants. This incorporation of technology into nursing could free up approximately 20% of nurses’ time, enabling them to spend more time with patients.
7 Ways How AI-Powered Assistants Can Help Nurses
1. Enhancing Clinical Decision Making
AI is increasingly being used to aid healthcare professionals with diagnostics. AI can combine data from different sources, including genetic and lifestyle data, to enhance diagnostic accuracy. AI can therefore provide nurses with increased insight and provide care recommendations to enable fully informed decisions regarding patient care delivery. In these circumstances, AI helps identify patterns that could be missed by humans due to their not having the ability to analyze large volumes of data, and can help nurses avoid “information fatigue”3.
2. Predictive Analytics
The use of AI in predictive analytics further assists nurses in providing optimal patient care. AI can analyze large amounts of patient data and compare this to previous patients, allowing patterns to be identified and treatments or care to be adjusted accordingly. AI algorithms can be used to analyze real-time, subtle changes in a patient’s condition, which could be indicative of deterioration or an adverse outcome.
3. Streamlining Administrative Tasks
Administrative tasks account for a large proportion of the non-patient-facing work carried out by nurses, reducing the time available to devote to patient care. One study found that as little as 21% of nurses’ time is spent on direct patient care4. Documentation can consume much of nurses’ time, with estimates as high as 60%5 of the shift absorbed in documenting patient care. The automation of documentation and the updating of patient records could save nurses a significant amount of time.

4. Streamlining Clinical Documentation
Natural language processing can be used to speed up nursing documentation by converting speech or handwritten notes into electronic health records and by assisting in the writing of nurse narratives.
5. Scheduling and staffing
AI algorithms can be used to optimize staffing scheduling, with the ability to produce and optimize a schedule while taking into account constraints, workload, and service demand.
6. Task prioritization
AI tools can be used to prioritize and assign tasks, factoring in time sensitivity, workload, staffing levels, patient complexity, and the resources available.
7. Enhancing Communication
Virtual healthcare assistants are increasingly being used to reduce the load placed on nurses and give them more time for direct patient care. These can take the form of chatbots, using natural language processing to understand patient queries and formulate accurate answers.
Challenges and Risks Surrounding the Implementation of AI in Nursing
Nurse Adoption and Trust in AI Tools
One of the most important considerations with the use of AI tools is how to ensure nurse engagement with the tool. AI tools should be developed in collaboration with nurses, as nurses will be able to inform developers what their needs are and whether the tool could be incorporated into their workflows. Nurses must be given sufficient training on the AI tools. In a survey carried out by The Health Foundation, 54% of registered nurses said that they ‘look forward’ to using AI in their job6.
Technological Challenges
Effective integration of AI assistants into hospitals requires compatibility with pre-existing IT systems to ensure sufficient data access. Interoperability between different IT systems is a common problem, with 61% of clinicians in one survey citing this as a key barrier to the implementation of digital tools, such as AI7.
Ethical and Regulatory Concerns
To carry out its roles in healthcare, AI requires access to large amounts of patient data. Data privacy and confidentiality regulations, such as HIPAA, must therefore be factored into any AI being implemented in hospitals. Further concerns may arise about the use of AI due to the risk of it perpetuating biases into its systems.
The Case for AI Assistants in Nursing
The integration of AI assistants into patient care has the potential to alleviate the global nursing crisis. A contributing factor to nurses leaving their jobs is limited job satisfaction, for which limited face-to-face patient contact due to other tasks is partially responsible. By streamlining administrative tasks, assisting clinical decision-making, optimizing care through predictive analysis, and reducing cognitive load, AI can provide nurses with more time to focus on direct patient care. To learn more about the implementation of AI in nursing, download IT Medical’s latest whitepaper that discusses it in greater detail.
1. Nursing and midwifery. Accessed December 13, 2024. https://www.who.int/news-room/fact-sheets/detail/nursing-and-midwifery
2. Solutions to close the nursing shortage gap | McKinsey. Accessed December 16, 2024. https://www.mckinsey.com/industries/healthcare/our-insights/reimagining-the-nursing-workload-finding-time-to-close-the-workforce-gap
3. Walsh University. 7 Ways Technology Is Impacting Nursing in 2022 | Walsh University Online. November 22, 2022. Accessed December 16, 2024. https://online.walsh.edu/news/technology-in-nursing
4. Solving The Nursing Shortage with Technology. Accessed December 16, 2024. https://www.accenture.com/us-en/insights/health/solving-the-nursing-shortage
5.Gesner E, Gazarian P, Dykes P. The Burden and Burnout in Documenting Patient Care: An Integrative Literature Review. Stud Health Technol Inform. 2019;264:1194-1198. doi:10.3233/SHTI19041
6. Survey: nurses cautiously optimistic about AI | Nursing Times. Accessed December 17, 2024. https://www.nursingtimes.net/digital-and-technology/survey-nurses-cautiously-optimistic-about-ai-01-08-2024/
7. Solving The Nursing Shortage with Technology. Accessed December 16, 2024. https://www.accenture.com/us-en/insights/health/solving-the-nursing-shortage