Artificial Intelligence in UK Healthcare: A Strategic HRM Analysis

This essay analyzes the implications of Artificial Intelligence (AI) on strategic human resource management within the UK healthcare sector. It explores how AI can improve healthcare services, potentially replacing human resources in areas like talent acquisition, training, performance analysis, and staff retention. The study emphasizes the need for healthcare managers to adopt effective business strategies and integrate AI tools to enhance productivity and reduce costs. It also discusses the changes that AI might bring to HR policies, such as improvements in training, talent management, and error prevention. The essay further examines how these changes can positively impact business strategy by addressing budget shortfalls and improving care delivery. Finally, it applies Kurt Lewin’s Force Field Analysis to design change implementation strategies, highlighting the importance of addressing emotional challenges among healthcare staff during the adoption of AI.

Running head: HRM STRATEGIES FOR ORGANIZATION
HRM STRATEGIES FOR ORGANIZATION
Name of the Student
Name of the University
Author’s Note

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Executive Summary
The present assignment focuses on how adoption of AI will improve the healthcare service in the
UK healthcare service in future. Few areas where AI might replace human resource in future
involves-talent acquisition, onboarding, training and development of healthcare employees,
analyzing the performance of healthcare staff, retention of staff and enabling HR managers to
improve outcome and monitor workers efficiently. Furthermore, the managers of the healthcare
sector should adopt effective business strategy in order to bring about change in business in
future. They should adopt machines so that it can support AI tools that are integrated in the
organization.

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Table of Contents
Introduction......................................................................................................................................3
Task 1...............................................................................................................................................4
Analyze the implication on strategic human resource management of Artificial Intelligence (AI)
within the UK health care sector.....................................................................................................4
AI that might change the way work is done within the health sector..........................................4
Change that might occur in present HR policies due to introduction of AI in this sector...........6
Analyzing how change will effect the business strategy.............................................................6
Task 2...............................................................................................................................................7
Kurt Lewin’s Force Field Analysis for designing change implementation.................................7
Conclusion and Recommendations..................................................................................................8
References......................................................................................................................................10
Bibliography..................................................................................................................................11

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Introduction
The purpose of this assignment is to analyze the effect and implication on strategic
human resource management of Artificial Intelligence within the UK health care sector. The
study reflects on the HR functions and HR policy formulation within the business context. The
analysis has been evaluated in this study with reference to Kurt Lewin’s Field Analysis. The
UK’s healthcare market has a constant requirement for the product and is open for innovative
technologies. The healthcare system in UK is divided between public healthcare system (NHS-
National Health Service) and small private sector. The NHS mainly dominates the healthcare
system in UK as the private health care sector is small and private insurance- based for users.
NHS employs near about 1.5 million people, thereby ranking it in the top five biggest workforces
in the globe. The NHS workforce play 350 different roles within this sector. The workforce in
private healthcare sector of UK provide services on behalf of NHS. Recent evidences reflect that
the NHS workforce has increased at high rate over the last few decades. Among the clinical staff,
the total number of nursing staffs is three times that of the doctors. The non- clinical support to
the clinical staffs generally makes up 25%of the total people working in NHS. Artificial
Intelligence (AI) is simulation of human intelligence procedure by machines mainly computer
systems. These procedures involve learning, reasoning and correction. AI can be categorized into
different types such as reactive machines, limited memory, self-awareness and theory of mind.
The study also provides recommendations to the managers of health care sector regarding change
in management strategy (Nilsson 2012).

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Task 1
Analyze the implication on strategic human resource management of Artificial Intelligence
(AI) within the UK health care sector
AI that might change the way work is done within the health sector
Healthcare system in UK requires reform in order to maintain high- quality health service
free at point of care. Over the years, the funding growth has gradually decreased and has been
unlikely to meet rising demand, driven by ageing population with chronic health conditions. The
utilization of AI in the healthcare sector will aid deliver NHS fit for the future. Growing AI
sector in UK reflects the huge potential of AI in the healthcare sector. The integration of AI in
this sector might improve outcomes in NHS and eventually reduce the total cost. Adoption of AI
will facilitate to enhance productivity and lead to economic as well as social benefit. Different
forms of AI ranging from decision support tools to intelligent virtual assistant will aid clinicians
to make diagnostic decisions and make efficient scheduling. The implementation of different
types of AI in healthcare sector might involve danger of repeating past mistakes when various
approach to the technological integration is needed.
The researchers have found out that adoption of AI in the healthcare sector will change
the way work is done within this sector. AI will help to predict the individuals who are at risk
relating to illness and permit NHS to effectively target treatment towards them. As wearables
monitor information in relation to health of individuals, AI can aid to interpret information for
providing people higher access to the knowledge regarding their physical condition. Recent facts
reflect that one out of seven UK citizens own fitness trackers highlighting the UK’s appetite for
the well- being. However, AI can utilize the data gathered on these devices for keeping people
change their behavior (Compas.ox.ac.uk 2018). In addition to this, AI might enable the clinicians

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to recognize those people with health conditions who are probable to develop specific
complications. AI can also provide health professionals access to treatment and diagnostics
tailored to the individual requirement. AI algorithms with higher diagnostic accuracy to the
clinicians might decrease variation in decision making quality whilst providing personalized care
generally. Moreover, deployment of AI in the healthcare sector can help clinicians to attain and
keep information in advance. Some of the Ai tools such as Watson can process literature
alongside the patient data for aiding diagnosis and recommending various treatment options to
the clinicians. Apart from this, this has huge potential in standardizing high-quality care since
healthcare professionals have enhanced access to guidance as well as research Compas.ox.ac.uk
2018). The researches have pointed out that adoption of AI in the healthcare sector might also
improve diagnostics with the target of decreasing morbidity and complications. Several
experimental studies reflect that autonomous robots might perform better treatment than the
surgeons. Integration of AI can help the surgeons to interpret anatomical data. Besides this, AI
can also change the treatment of mental health conditions of the UK citizens such as depressions,
panic disorders and so on. Moreover, AI can also help to reduce administrative work in various
healthcare sectors and address present inefficiencies. Several research done on AI helps to
predict that this can empower people with chronic disease for improving their outcomes. Recent
evidences highlights that NHS has made several mistakes in the past of not implementing
technology within the service transformation plans. However, the NHS must further investigate
which applications of AI can be adopted in several areas according to the requirements of
patients as well as staffs. They should also take into account how to integrate AI in delivering
efficient system that is focused on attaining better results for the patients in future.

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Change that might occur in present HR policies due to introduction of AI in this sector
The growth of AI represents huge opportunity for the HR managers to play strategic role
in the UK health care organizations. Russell and Norvig (2016) states that introduction of AI in
the UK healthcare sector will help the HR mangers to improve the HR policies and practices.
Training and development is one of the biggest segments where UK healthcare HR managers can
utilize AI. It will help the HR managers in UK healthcare sector to assure that their workers
assessment, training and development, communication as well as monitoring tools are effective.
In addition to this, adoption of AI will also permit the HR team to change every areas in effective
ways. This augmentation will facilitate the staffs in UK healthcare sector to improve their
efficiency level and complete their work quickly.
The researchers have found out that hiring procedure are suitable for improvement in the
HR management through AI. The talent management system is the data type AI can utilize for
identifying best talent for the respective position. AI can help the HR managers to improve this
by giving better matching individuals to the jobs, thereby permitting the hospitals to recruit right
candidates effectively. Apart from this, AI can aid the UK healthcare HR managers to identify
errors and generate new ideas for preventing and reducing future errors. AI can also help UK
healthcare HR leaders to monitor staff behavior as well as look for market trends. Thuds, this
kind of work can thereby aid to reduce compliance risk as well as turnover risk.
Analyzing how change will effect the business strategy
Recent evidences reflect that NHS in UK has been facing multi-billion budget shortfall
during the last few years. Some of the key challenges also remain in making improvements in the
quality as well as adoption of proper care delivery (May and Pitt 2012). The change in HR
policies in UK healthcare sector due to integration of AI will have positive impact on the

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business strategy. This will facilitate the healthcare staffs to adopt strategy that will work on all
issues and navigate the various competition bases as well as build capabilities necessary for
delivering lasting value. The change in policies and procedures will help the managers of UK
healthcare to implement few strategies such as building healthy environment, developing
resilient communities and creating diverse business framework for healthcare providers. It will
also facilitate the UK healthcare providers to improve strategies relating to quality challenges,
disparities in accessibility to care, quality challenges, cost –effective patient centered solution.
Even the UK healthcare system can take opportunities to work with the individuals for
preventing and managing problems relating to healthcare (the Guardian. 2018). Moreover, this
will also aid to improve the individuals understanding as well as control over life chances and
health illness. Overall, integration of effective business strategy will aid to embed sustainability
in UK healthcare system involving decreasing its environmental affect while staying within
financial limits.
Task 2
Kurt Lewin’s Force Field Analysis for designing change implementation
Kurt Lewis developed Force field Analysis in order to inform decision-making,
specifically in planning as well as adopting change management programs within the
organizations (Swanson, and Creed 2014). It is one of the powerful methods of attaining
overview of various forces acting on potential enterprise change problem and for evaluating their
main source as well as strength (Kruglanski et al. 2012). The Kurt Lewin’s Force Field analysis
assess the effect of forces which influences change in the organization. These forces are
categorized into two parts- driving and restraining forces. Driving forces refers to the force that
promote as well as push change. The change drivers then promote as well as motivate change

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procedure. On the other hand, restraining forces refers to the forces that makes change highly
difficult. However, these forces counter driving forces as well as lead to avoidance of change
(Shirey 2013).
Schulz and Nakamoto (2013) states that changes in workplace creates uncertainty and
emotionally challenging for the employees. Changes in healthcare practice fail as doctors as well
as nurses are not empowered for adjusting emotionally to the new method of working. Kurt
Lewin offered three-step approach to adopt structured change in workplace. However,
integrating this model will enable the staffs to psychologically recognize and sustain change.
Lewin proposed that adopting structured change will support the healthcare staff to unfreeze
from the comfort point. However, this will help to design the change implementation as all the
staffs becomes motivated to alter their own values, explore alternatives and implement solutions.
In addition, refreezing usually occurs when the change becomes established (Strategy
and.pwc.com. 2018). In NHS, the change will not reach the refreezing stage as the change trends
to impact the previous ones. Thus, this approach is useful to highlight how changes affect
healthcare staffs emotionally and the needs that should be addressed for helping adopting the
changes (Russell and Norvig 2016).
Conclusion and Recommendations
From the above discussion, it can be concluded that integration of AI will help to
improve the healthcare service in the UK healthcare sector. Application of different forms of AI
might help the clinicians to provide best possible care as well as making good quality care
service available to all the people. This will also aid the individuals to attain information about
their own health condition. It has been predicted by several researches that AI will become
interdependent in the health related fields. However, it is recommended that the UK healthcare

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sector must develop infrastructure for data in order to capture as well as adopt data that is
generated from other devices for supporting AI applications. Besides this, the HR managers of
the UK healthcare sector must improve their policies and practices in order to integrate AI tools
effectively. The HR mangers of UK healthcare sector should also provide training and
development to the staffs, so that they can deliver the service care effectively.

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References
Compas.ox.ac.uk. (2018). [online] Available at: https://www.compas.ox.ac.uk/media/PR-2015-
WORKINT-Background-Report.pdf [Accessed 29 Jul. 2018].
Kruglanski, A.W., Bélanger, J.J., Chen, X., Köpetz, C., Pierro, A. and Mannetti, L., 2012. The
energetics of motivated cognition: a force-field analysis. Psychological review, 119(1), p.1.
May, D. and Pitt, M., 2012. Environmental cleaning in UK healthcare since the NHS Plan: a
policy and evidence based context. Facilities, 30(1/2), pp.6-22.
Nilsson, N.J., 2014. Principles of artificial intelligence. Morgan Kaufmann.
Russell, S.J. and Norvig, P., 2016. Artificial intelligence: a modern approach. Malaysia; Pearson
Education Limited,.
Schulz, P.J. and Nakamoto, K., 2013. Patient behavior and the benefits of artificial intelligence:
the perils of “dangerous” literacy and illusory patient empowerment. Patient education and
counseling, 92(2), pp.223-228.
Shirey, M.R., 2013. Lewin’s theory of planned change as a strategic resource. Journal of Nursing
Administration, 43(2), pp.69-72
Strategyand.pwc.com. (2018). Health | PwC's Strategy& UK. [online] Available at:
https://www.strategyand.pwc.com/uk/health [Accessed 29 Jul. 2018].
the Guardian. (2018). Sustainable healthcare: the NHS launches a new strategy. [online]
Available at: https://www.theguardian.com/sustainable-business/blog/nhs-sustainable-healthcare-
strategy [Accessed 29 Jul. 2018].

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Bibliography
Acampora, G., Cook, D.J., Rashidi, P. and Vasilakos, A.V., 2013. A survey on ambient
intelligence in healthcare. Proceedings of the IEEE, 101(12), pp.2470-2494.
Bamiah, M., Brohi, S. and Chuprat, S., 2012, December. A study on significance of adopting
cloud computing paradigm in healthcare sector. In Cloud Computing Technologies, Applications
and Management (ICCCTAM), 2012 International Conference on (pp. 65-68). IEEE.
Bennett, C.C. and Hauser, K., 2013. Artificial intelligence framework for simulating clinical
decision-making: A Markov decision process approach. Artificial intelligence in medicine,
57(1), pp.9-19.
May, D. and Pitt, M., 2012. Environmental cleaning in UK healthcare since the NHS Plan: a
policy and evidence based context. Facilities, 30(1/2), pp.6-22.
Swanson, D.J. and Creed, A.S., 2014. Sharpening the focus of force field analysis. Journal of
change management, 14(1), pp.28-47.
Zang, Y., Zhang, F., Di, C.A. and Zhu, D., 2015. Advances of flexible pressure sensors toward
artificial intelligence and health care applications. Materials Horizons, 2(2), pp.140-156.