Introduction

In the recent years, artificial intelligence (AI) technology has begun to play an increasingly important role in the healthcare sector - from proposals to the improvement of documentation, through staff management, to supporting clinical decision-making. Despite these impressive possibilities, serious questions are also emerging about risks, the impact on workers, and what “assistance” or “better care” means. Artificial intelligence has the potential to significantly relieve the burden on the Polish healthcare system and improve the quality of care. However, without thoughtful and ethical implementation that takes into account the real working conditions - particularly of nurses - it may deepen existing problems and the widely discussed inequalities. This article outlines how AI could meaningfully transform Polish hospitals, taking into account factors such as reducing the workload of overburdened nurses, the risks associated with automation, and the critical decisions that must be made today to ensure that technological advancement serves human needs, rather than undermining them. In the context of a workforce shortage, an aging professional staff, and increasing patient demand, the Polish healthcare system is progressively adopting AI-driven solutions. While such technologies may improve documentation, support diagnostic processes, and reduce the burden on nursing staff, they also pose a risk to the integrity of the patient-nurse relationship. Poland is now confronted with a crucial choice: will AI serve as a means of improving the quality of care, or will it become yet another destabilizing factor within an already strained system?

samoili et al. defined artificial intelligence (Ai) in 2020 as: “software (and possibly also hardware) systems designed by humans that, given a complex goal, act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the collected structured or unstructured data, reasoning on the knowledge, or processing the information, derived from this data and deciding the best action(s) to take to achieve the given goal. Ai systems can either use symbolic rules or learn a numeric model, and they can also adapt their behaviour by analysing how the environment is affected by their previous actions”

AI as a Means of Reducing Workload in India

On the other hand, in the context of developing countries such as India, the use of AI is often presented as a response to the heavy burden on healthcare systems. In a Reuters article on the Apollo Hospitals network in India, plans were outlined to invest in AI tools aimed at reducing the workload of doctors and nurses. Apollo Hospitals, with more than 10,000 beds, has in recent years allocated around 3.5% of its digital spending to AI and plans to increase this investment. The goal is to “free up two to three hours per day” for doctors and nurses through AI interventions such as medical record analysis, automated discharge summaries, and documentation support. AI tools are also expected to assist in tasks such as selecting appropriate antibiotics or predicting the risk of complications. However, several challenges remain, including the cost of technology, fragmented data sources, limited access to electronic health records, as well as concerns about implementation and cost-effectiveness. In this context, AI is not seen as replacing healthcare workers, but rather as improving their working conditions by reducing routine tasks and allowing staff to focus on what matters most – direct patient care [2]. When comparing the examples from the United States and India, several key research gaps become apparent. One of them is the tension between flexibility and job stability. In the U.S., the gig model suggests flexibility, but in practice, it may lead to unstable employment, lower pay, and poorer working conditions. In India, AI is presented as a tool to increase efficiency, but its success depends heavily on infrastructure and how well it is implemented. Another important issue is algorithms and accountability. Who is responsible when an algorithm provides incorrect guidance and a nurse, unfamiliar with a specific work environment, relies on it? As highlighted in the Roosevelt Institute report, “human vulnerability – the essence of nursing – is based on relationships and cannot be managed algorithmically” [1]. Investments in AI should go hand in hand with clear rules regarding responsibility, oversight, and patient safety. Infrastructure also plays a key role, especially in the context of interprofessional teamwork. In countries with well-developed systems, the main challenges relate to working models and employment conditions in healthcare. In developing countries, however, the barriers are more technological - data systems, standards and procedures, costs, and infrastructure. AI can support improvement, but only if these basic conditions are met. The quality of care and the relationship between patient, staff, and family - especially in person-centred care - remain central. In both cases, the key question is whether technology actually improves patient care or mainly increases efficiency. In the U.S., concerns focus on whether quick “matching” of staff compromises quality. In India, although the goal is ambitious – reducing workload – the implementation is still at an early stage (e.g., “some AI tools are still in the experimental phase”) [2].

AI-based technologies, including robots, decision-support algorithms, and staff scheduling applications, are increasingly being introduced into hospitals and healthcare facilities. This trend is visible both in the U.S. and in the countries with fewer resources. At the same time, concerns are growing about their impact on healthcare workers, patient safety, and quality of care. An Associate Press article describes the robot “Robin”, which has been introduced in nursing homes and healthcare facilities in the United States [3]. Robin is designed to assist with simpler tasks such as entering patient data, monitoring patient condition, and transporting materials [3]. Its purpose is to reduce the workload of nursing staff and ease their physical burden [3]. However, concerns remain: could a robot assistant weaken the relationship between staff and patients? Might such technologies be used to justify staff reductions or increase pressure on workers? This example shows that AI is not only automating processes but it also entering areas traditionally associated with nursing, such as care, communication, and presence. This represents both an opportunity and a challenge.

AI Nurses and Professional Opposition

A second Associated Press article illustrates how artificial intelligence tools are beginning to function as support - and in some cases, as a substitute - for nursing practice in hospitals in the United States [4]. These tools are capable of analysing patient data, suggesting clinical actions, and even conducting initial communication with patients [4]. Nurses and professional organizations are increasingly voicing their opposition. Concerns relate not only to potential job loss, but also to a perceived loss of control over patient care and the erosion of human-to-human relationships [4]. It is also emphasized that AI is neither neutral nor free from error. Data inaccuracies, algorithmic bias, and insufficient oversight may lead to medical errors. This highlights that the implementation of AI in healthcare is not only a technological issue, but also one that involves workplace culture, ethics, professional relationships, and the protection of patient rights.

What does this mean for Poland and Europe?

A Reuters article describes how Apollo Hospitals in India is investing in AI to reduce staff workload and improve nurses’ efficiency, among other benefits [2]. The Roosevelt Institute report, which served as the basis for The Guardian’s article, indicated that in the US, application platforms are attempting to manage nurses’ schedules and work hours, raising concerns about future employment conditions [1]. When combined with robots and algorithms, this technology is becoming part of the management systems for both work and healthcare. This raises questions about who will work, how they will work, and for whom. Combining all these elements, several important issues worth considering can be identified, forming the basis for identifying research gaps. Range of Support vs. Replacement. Technology can support work, but when it begins to replace it, what does this mean for the nurse? Does a robot assistant become an excuse to reduce the number of full-time positions or increase the workload on those who remain? Qualifications and the relationship with the patient. Healthcare is not just about technical activities but most importantly about relationships, trust, and presence. Can a robot or algorithm strengthen or weaken this relationship? Databases, algorithms, transparency. Questions arise everywhere with AI implementations: Where do we get the data? Is the algorithm trained on the right keywords? Who is responsible for a potential medical error or other adverse event? Combined with the realities of work, where pressure, staff shortages, and fatigue are a reality, this risk increases. In the US, nursing employment conditions, gig-economy models, and the balance between flexibility and stability are becoming issues. In countries like India, infrastructure, data, budget, and training pose challenges. In Poland and Europe, both of these dimensions will be important. Is the ethical context in this area relevant? What are the regulations and economic balance? Finally, who sets the parameters for AI? Under what principles is the technology implemented? Is the primary goal better care or lower costs? Do employees have an impact on how technology is integrated into their daily lives? While the examples provided focus on the US and India, the conclusions are also relevant for Poland and Europe: Decisions to implement AI in healthcare should consider not only the technology but also staff working conditions, qualifications, data infrastructure, and patient safety. Flexible work models via digital platforms may be tempting, but without appropriate safeguards, they can reduce job satisfaction and the quality of care. Investments in AI must be coupled with the development of digital infrastructure, system interoperability, healthcare staff education, and legal and ethical regulations. The key question is whether technology should primarily serve to reduce costs or improve conditions for employees and patients.

Artificial Intelligence in Polish Healthcare: A Time of Hope and Challenges?

In Poland, where the healthcare system is struggling with staff shortages, rising quality standards, and debt, AI appears to be a potential solution. But at the same time, serious questions arise: will the technology be implemented appropriately? Will it strengthen staff-patient relationships, or weaken them? According to a report by the Polish Chamber of Nurses and Midwives (NIPiP), there were 315,670 registered nurses and 41,719 registered midwives in Poland in January 2023 [5]. The average age of nurses in Poland is just over 54, and that of midwives is around 51, with forecasts indicating further growth [5]. In 2022, the number of nurses per 1,000 inhabitants in Poland was only about 5.7, compared with the EU average of about 8.4 [6]. Poland’s healthcare spending is only about 6.4% of GDP, compared to the EU average of 10.4% [6]. These data clearly demonstrate that the Polish healthcare system operates understaffed, with an ageing workforce and limited resources. In this context, introducing AI may present an opportunity, but if conducted incorrectly, it can increase risks. Reports indicate that although AI technology is emerging in Poland, its implementation is still limited. For example, the Polish publication titled “AI to nie sci-fi” mentioned applications such as RSQ AI (a system for diagnostic imaging) and Radiato.ai (for the analysis of kidney tumours) in Polish facilities [7]. In another Polish article titled “Ai w opiece zdrowotnej – w Polsce będziemy musieli na nią jeszcze trochę poczekać” the authors noted that key obstacles include access to data, system interoperability, and financial resources [8]. In an interview, the President of the Polish Chamber of Nurses and Midwives (NIPiP) pointed out that nurses and midwives can benefit from AI: less time spent on paperwork and greater emphasis on patient contact [9]. Opportunities for AI, as well as research gaps in this area, include reducing routine workload. AI can automate administrative tasks, document management, and preliminary data analyses. In the Polish context, where healthcare workers are heavily burdened, this can mean more time for patients. Furthermore, it can support clinical decisions. Algorithms can analyse medical and imaging data, aiding in diagnosis. Examples are already available in Poland (e.g., the aforementioned imaging diagnostic systems). Consideration should be given to greater accessibility and efficiency in the use of AI. Applying AI in primary care will enable nurses and midwives to deliver services more effectively, potentially reducing waiting times and improving the quality of care [9].

Threats

The loss of staff-patient relationships can significantly undermine the quality of care and patient satisfaction. Healthcare is not just about technology but also about presence, empathy, and trust. If AI reduces direct contact, there is a risk of weakening the therapeutic bond and heightening patients’ feelings of isolation. Working conditions for staff, particularly nurses, will be a key determinant of professional well-being and the efficiency of the healthcare system. In the US and other countries, flexible work platforms and scheduling algorithms have been noted to worsen nurses’ working conditions. If AI is used primarily as a cost-cutting tool or to increase workloads in Poland, it could exacerbate the shortage. Implementing AI requires robust data, standards, regulations, and oversight. In Poland, these areas are still in development. For example, the White Paper on the use of AI in healthcare services has received little attention [10]. It is important to assess regional variations and inequalities. In Poland, there are significant differences between voivodships in nurses’ professional activity, employment numbers, age, and related factors. If AI is implemented only in the largest centres, it could worsen these inequalities [5]. For AI technology in healthcare to deliver real benefits, pilot studies involving healthcare professionals are recommended. Before implementing AI throughout a hospital or clinic, pilot implementations with nurses, midwives, and physicians should be conducted to ensure the project is tailored to their needs and work environment. Continuing education and digital competencies for nurses are the foundation for the safe and effective use of technology in clinical practice. Medical personnel must understand how AI works, its limitations, and when to intervene. Investing in competencies is a key element in developing advanced practice and ensuring high-quality patient care in an integrated healthcare technology environment. Building data infrastructure and systems is crucial because AI will not function well without high-quality data. Poland needs interoperable systems, data exchange standards, privacy protection, and secure platforms. Regulations, ethics, and accountability must clearly define responsibility for AI errors, principles for the use of algorithms, and the rights of patients and staff. Maintaining a balance between technology and humans is a priority. Technology should support the roles of nurses and midwives and the patient-nurse relationship, not replace them. When implementing AI, we must continue to prioritise human care.

Summary

Artificial intelligence technology in healthcare is a tool with great potential. Starting from automating documentation to supporting clinical decisions and reducing the workload of employees, including nurses. The example of India demonstrates that it is possible to postpone and extend staff time off effectively. However, the American model exposes the risk that flexibility can mean less job stability, and efficiency does not necessarily translate into better quality, patient- and family-centred care. If technology is to help truly, it must be implemented with consideration for working conditions, patient communication, ethics, and legal norms. Only then can AI be a force that supports, rather than replaces, the foundations of healthcare built by the pioneers of nursing. Poland is at a turning point: on the one hand, there are serious challenges, such as staff shortages, ageing nurses, the next generation of workers, and indebted hospitals, with hospital budgets balanced at approximately 60% on employee salaries. On the other hand, AI is becoming a possible tool to alleviate these challenges. However, success is not simply about implementing technology; it also requires wise implementation with an appropriate legal basis, which is often overlooked. If technology is introduced with consideration for staff working conditions, improved communication with patients, families, and the interprofessional team, and coordinated with infrastructure and legal regulations, it could indeed be a step forward. But if it is treated as a cost-cutting tool, without consideration for ethics and humankind, it could do more harm than good. For Poland, cooperation between staff, IT specialists, the CEO (Chief Executive Officer), patients, and their families will be crucial. Strategic decisions in this area should be designed to ensure that AI serves care, not replaces it.