Abstract
The purpose of this research paper is to examine the impact of artificial intelligence on the changes in management that that take place in the workplace. To understand the change management that take place in the workplace the deductive research approach was used in the research while the artificial intelligence technology was used. Data was gathered from 25 business professionals working in various organizations across the UK that have incorporated. To collect the data a Google Forms questionnaire was used, which was analyzed using frequency data analysis to determine the mean, mode, and median as frequency distributions. The study concluded that AI technologies have a famous influence on change management within the workplace, resulting in changes in job responsibilities, organizational culture, and business procedures AI technologies. The study is also identifying some limitations of the methodology of research that includes through the questionnaire method's lack of responses of emotional captured. Generally, the research is providing insights of valuable into the impact of AI on the management of change in the workplace, and in the knowledge on this topic, it contributes to the growing body.
Contents
Chapter 1: introduction. 5
Chapter 2: Literature Review.. 6
2.2 Theoretical Model Used in the Topical Area. 6
2.3 Impact of Artificial Intelligence on the Future of Workplace in the UK.. 8
2.4 Bank development indicator 9
Chapter 3: Research Methodology. 12
3.6 Data Collection Method. 13
3.7 Method of Data Analysis. 13
3.8 Reliability/Validity/Generalisability. 14
3.10 Limitations of Methodology. 14
Chapter 4: Results and findings. 16
Chapter 5: conclusion and recommendations. 18
5.5 Suggestions for further study. 19
Chapter 1: introduction
In the way we live and work Artificial intelligence (AI) has been a change of life. Many industries are reshaped and transmitted for future in a progressive way. More of the industries are adopting various artificial intelligence to improve their efficiency and productivity .The United Kingdom is also adopting this trend.In the workplace theincorporation AI has important implications in terms of up skilling and business displacement. AL has the capability to enable workers to focus on their work more creative and high-value tasks, monotonous and routine tasks.
In the UK on the future workplace the effect of AI is a focus of increasing concern and interest. It is very important to recognize the drawbacks and benefits of potential in the workplace of AI, as well as the ethical and social consequences that its adoption may entail.
In this context, In UK the present state of adoption of AI is very essential to examine the probable influence on the job market and the measures that can be taken to confirm that the profits of AI are shared fairly across the employees. This topic mandates an interdisciplinary and all-inclusive approach that encompasses policymakers, industry leaders, and the workers themselves.
Chapter 2: Literature Review
2.1 Introduction
The literature review is based on the critical review of the impact of artificial intelligence on the future of the workplace in the United Kingdom. Artificial intelligence is a vast technology that is helping workers and employees to be more productive and helps in increasing the overall efficiency of the workplace. AI-based solutions are effectively helping in the innovation of new services and products. Many workplaces and organisations in the UK have implemented AI-based solutions which help them in advancing in technology and support cross-sectional partnerships. The aim of AI in the UK is to benefit both the private and the public sector organisations along with transforming the industries and stimulating economic growth(De Stefano, 2019).
According to Bughin et al., (2018), there are also some negative impacts of artificial intelligence which is affecting the workplaces in the UK. AI-based solutions have automated many operations and thus replaced humans from their jobs. This is leading to a higher level of inequality and discrimination against employees and workers. Based on this, the secondary data used in this research is collected from the primary resources which help in critically reviewing the impact of artificial intelligence on the future of the workplace in the UK.
2.2 Theoretical Model Used in the Topical Area
Artificial intelligence is effectively helping industries and organisations to increase the efficiency of the workplace. The predictions made by the AI-based solutions help in developing innovative products and services which are helping organisations to gain a competitive advantage over their rivals(Ransbotham et al., 2018). However, artificial intelligence is impacting the experience of employees due to which employees are facing a severe change in adopting AI technology in the workplace. Human resource management is focusing on the internal training of employees so that they get knowledge of artificial intelligence and develop skills for implementing AI. However, extreme automation within the organisation can replace the human workforce as AI and machine learning algorithms are very fast compared to humans(Haefner, Wincent, Parida and Gassmann, 2021).
According to Lewin’s force field theory, there are two types of forces including driving force and restraining force. The driving forces focus on leading the change within the organisation while the restraining forces restrict the change to happen. In other words, restraining forces diminishes the effects of driving forces(Ro?ca, 2020).
Figure 1: Lewin’s Model of Change
Source- Practical Psychology (2023)
The analysis of artificial intelligence can be understood from Lewin's three-step change model which includes:
Unfreezing- In this stage, the managers and leaders of the organisation motivate employees to support the implementation of artificial intelligence. Many organisations in the UK have applied communication policies that helped employees to get support in the new situation(Burnes, 2020). According to Benbya, Pachidi and Jarvenpaa, (2021),much of organisations spent a huge amount of their budget on the implementation of artificial intelligence but they did not focus on providing training to employees so that they can use the systems efficiently.
Moving- In this stage, many organisations within the UK have empowered their employees to support the change and embrace the new system of working. Employees were asked to introduce artificial intelligence in various tasks to improve their productivity and the overall efficiency of the organisation(Burnes, 2020).
Refreezing- In the refreeze stage, the human resource management of many organisations has applied the tactics of rewards and recognition to influence employees to get integrate with the use of artificial intelligence and enhance their performance and productivity. Some organisations in the UK utilised the method of incentives for employees who have been highly supported during the implementation of artificial intelligence, systems, and solutions. This significantly helped in getting the support of employees who are opposing the change(Hughes, Robert, Frady and Arroyos, 2019).
From this change management model, it is clear that many organisations in the UK have experienced challenges during the implementation of artificial intelligence but later with the help of effective strategies, they have gained the support of the employees due to which they have successfully implemented AI-based solutions within the workplace. However, due to extreme automation, artificial intelligence has replaced many human workers and jobs which is affecting the employees of the organisations (Haefner, Wincent, Parida and Gassmann, 2021).
2.3 Impact of Artificial Intelligence on the Future of Workplace in the UK
Artificial intelligence systems and solutions have many technical capabilities such as autonomous vehicles, drones, and robots which are substantially helping in the progress of UK organisations. AI and its applications are completely transforming industries by implementing tech-based innovations which are significantly helping in boosting the economy. According to the UK government, these technologies can help the country in increasing the economy by up to 10%(GOV.UK, 2021).
From this, it is clear that artificial intelligence is significantly helping the development of the country. The progression of different organisations and sectors in the UK helps the country to generate a huge economy with the help of which many development processes can be initiated. This will help the country to become one of the most developed and successful countries in the world(GOV.UK, 2021).
According to GOV.UK, (2021), these technologies develop concerns for the huge number of human workers and employees who are serving UK organisations for a long time. The technologies of artificial intelligence can affect the UK labour market and can increase the unemployment rate within the country. This will highly affect the country and the organisations the capabilities of artificial intelligence are still limited and some jobs cannot replace humans.
Thus, it is not possible to completely replace humans as their cognitive abilities influence their actions and decisions which cannot be expected by AI solutions. Also, humans possess a set of skills including interpersonal skills, critical thinking skills, the ability to solve complex problems by generating creative solutions, and emotional intelligence. These soft skills are vital for the growth and development of organisations. Thus, artificial intelligence cannot replace humans completely (Anderson, Rainie and Luchsinger, 2018).
2.4 Bank development indicator
Bank development indicators are the most important tools that are used to assess the overall growth and health of the banking sector of a country. With the help of these indicators the overall performance of the banks can be indicated and the level of financial inclusion of the banks can be determined. In the context of literature, the impact of financial development on the growth of economy can be easily understood by the bank development indicators (Yuval, 2016).
The key development indicator is the financial level inclusion. It determines the extent up to which businesses and individuals have the access to financial services like insurance, loans and saving accounts (Gilmour et al, 2011).
Another bank development indicator is the ratio of bank assets to Gross Domestic Profit. By the help of this ratio size of the banking sector relative to the whole economy can be determined. If this ratio is higher than it indicates that there is a higher development in the banking sector and that it is playing a crucial role in the economy of the country,
Another important indicator is the quality of bank assets. If there is a high ratio of non-performing loans in the banking sector, it indicates that there is a certain problem in the banking sector because these loans are regarded as the loans that are in default or cannot be repaid (Yuval, 2016).
Level of innovation is also an important indictor in the development of the bank of any country like UK. There is a continuous advancement in the technology more even in the countries like UK and it has also transformed the banking industry. The banks that are more adoptable and innovative they are more likely to be successful in the long run (Gilmour et al, 2011).
2.5 Qualitative review
The qualitative review of the literature suggests that the AI technologies brought a huge change in the nature of work, the skills that are required by the workers and also on the job roles. It also indicates that most of the u=industries and sectors of UK are using technology of AI and this trend will be more accelerated in the following years. The review also highlights that the AI can also have an impact on the businesses and policymakers and they may have to invest in the programs like up skilling and re skilling so that the workers at the work place could be fully equipped with the skills that are required in the digital technology.
2.6 Time series
The data used in the literature is collected over different periods of time. It can be analysed by using the technique of time series analysis. It will determine any patterns and trends that exist in the above data. The evolution of various factors over the time and there change in future can be better understood by this series (Sutton, 2000).
2.7 Cross section data
The cross sectional data will be used to examine any differences in the development of banks within different countries at a specific time. The key factors that contribute to the development of banks in different countries like political, social or cultural factors can be analysed by the researchers (Dey et al, 2014).
2.8 Panel data
In this process the data from different banks will be collected from specific periods of time to know the relationship between the performance of banks and the specific characteristics. The panel data will give a more accurate estimate of the impacts if various factors on different banks if it is analyzed by combining time series and cross sectional data (Chamberlain, 1984).
2.9 Conclusion
From the above literature review, it is clear that many tasks are performed better with the help of artificial intelligence but these systems are unable to replace humans as AI systems don't possess some specific set of skills that are important for the growth and development of employees. Artificial intelligence possesses limited capabilities in the present day which are not sufficient for the progress and productivity of organisations. However, it is expected that the technological demands increase in the coming years due to which robots and other artificial intelligence-based systems get human essential skills that help in the progress of organisations. If this happens then there are possibilities that artificial intelligence can completely replace humans in their jobs. Also, it is expected that by 2040, around 1.3 billion businesses will invest in artificial intelligence and the overall rate of adoption will reach up to 34.6%.
In that scenario too, there will be some skills gap that cannot be fulfilled by AI systems and complete replacement of the human workforce may not be possible. Thus, it is concluded that artificial intelligence and other technologies should be used for the growth and development of organisations, industries, and countries but should not affect the lives of humans as they are an important part of the economy.
Chapter 3: Research Methodology
3.1 Introduction
The research methodology used in this research includes a range of processes that helps in conducting the research and gathering relevant and accurate data. The research methodology includes interpretivist research philosophy, explanatory research design, quantitative research method, the deductive approach of research, and a survey through a questionnaire for the collection of data.
3.2 Research Philosophy
The research philosophy used in this research is interpretivist philosophy. The reason for choosing this research philosophy is that it provides an opportunity for further study of the research and also guides about the values that reflect research plans. With this research philosophy, the chosen topic will be researched further which helps in getting accurate and updated results. One of the main advantages of interpretivist research philosophy is that the chosen topic of the research can be studied in depth due to which precise and faultless results can be achieved(Žukauskas, Vveinhardt and Andriukaitien?, 2018).
3.3 Research Design
The research design chosen for carrying out the impact of artificial intelligence on the future of the workplace is explanatory. The reason for choosing this research design is that it can be conducted at a lower cost and also helps in conducting further research. This research design helps the researcher to understand the worthiness of the chosen topic. It helps in understanding the impacts of AI on the workplace of the UK, the economy of the country, and the labour workforce. With the help of explanatory research design, the researcher gets able to predict future happenings(Asenahabi, 2019).
3.4 Research Method
The research method used in this research is the quantitative research method. The quantitative research method helps the researcher to achieve focused, fast, and relatable results. Quantitative research is highly efficient and quick which helps in saving a lot of time in conducting research. By utilising this research method, the researcher got able to collect numerical data and important facts based on it. Quantitative research helped in predicting the advantages of artificial intelligence in the increase of the economy of the UK by 10%. Thus, the research method helps in providing valuable and reliable data(Sürücü and MASLAKÇI, 2020).
3.5 Research Approach
The research approach used in this research is the deductive research approach. The reason for choosing this research approach is that the researcher has relied on the existing theories and hypotheses to gain effective and reliable results. Rather than creating new theories, the deductive research approach helped in using Lewin's model of change to understand change management within the workplace while introducing the technology of artificial intelligence. This research approach significantly helps the researcher to explain the relationships between variables and concepts so that generalised findings can be achieved(Casula, Rangarajan and Shields, 2021).
3.6 Data Collection Method
The data collection method used in this research is a questionnaire which is conducted with the help of a survey strategy. The survey includes 25 business professionals from different organisations within the UK that have implemented technologies based on artificial intelligence. The survey is conducted with the help of Google forms as it was an efficient method of distributing surveys to a large number of people. The questionnaire method of the survey helped in getting diverse and distinct information efficiently and simply(Sileyew, 2019).
3.7 Method of Data Analysis
The method of data analysis used in this research is frequency data analysis. It helped in identifying mean, mode, and median as frequency distributions which enabled the researcher to present raw data in an easy and organised format. With the help of this method of data analysis, scores that occur frequently can be easily identified, and also helps in outlining the cases that are unique and not common. This data analysis method can help in identifying the number of occurrences that are chosen by each respondent in the questionnaire survey. Hence, this data analysis method helps in analysing results and concluding effectively(Górecki, Krzy?ko, Waszak and Wo?y?ski, 2018).
3.8 Reliability/Validity/Generalisability
The research approach, method, design, philosophy, and data analysis method used in conducting this research helped in gaining effective and accurate results to an extent. The survey method of data collection significantly helped in collecting authentic and relevant data about the impact of artificial intelligence in the workplace of the UK. The questionnaire method helped business professionals to share their views and the impact of implementing AI technologies and solutions within their respective workplaces. The results gained from the research are found to be relevant and reliable after observing the current situation, strategies, and approaches of the workplace.
3.9 Ethics
The researcher has followed the fundamental ethical principles based on the activities that have been carried out for the research. The research outputs and resources used in this research have respected the society and others involved in the research. The researcher has followed all the regulations of the research while conducting surveys through questionnaires. The identity of all the respondents has been kept confidential and the collected data have been kept in a safe and virus-free and password-protected device.
3.10 Limitations of Methodology
While conducting quantitative research, there is a lack of probability in sampling which impacts the interpretation of the findings of the research. Also, the questionnaire method used in this research is unable to capture the emotional responses as well as the feelings of respondents due to which a huge variety of useful data went unnoticed(Evans and Mathur, 2018).
3.11 Conclusion
The research methodology, design, philosophy, approach, and data collection method used for this research significantly helped in getting reliable and accurate data. The data gathered from all these research processes helps in identifying the impact of artificial intelligence on the future of workplaces within the UK.
Chapter 4: Results and findings
The aim of this study is to investigate the impact of the artificial intelligence on the change management taking place in the workplace. It used Lewin's model of change management as the theoretical framework. The data for the research was collected by using a questionnaire survey of 25 professionals related to business and the deductive approach was used there. These professionals were from different organizations of the U.K. to identify the mean, median and mode the analysis of frequency data taken place so that the raw data can be presented in and organized and easy format. Moreover the results showed that the change mamagement is greatly impacted by artificial intelligence in the workplace. The findings of the study indiactes that organizations can have significant benefits of using AI to make them more efficient, productive and for reduction of cost. Change management can be improved by AI by providing insights into cutomer behaviour, improving decision making, enhancing collaboration and automating repetitive tasks. The results of the study also shows that along with the benefits of AI there are also some challenges the organizations have to face. These challenges may include privacy concenrs, potential loss of jobs due to automation, the need for significant investment and the ethicsl issues in the Te technology of AI.
Furthermore, the study reveals that along with the general acceptance of AI technology in the workplace there is also some concerns among tge employees. They may include the fears related to the lpss of jobs and potential for bias in the decision making by AI.
The study recommend s that the organizations must have to adress these issues by educating and training the employees about the limitations and benefits of AI technology.
By concluding, the study suggests that the AI technology has a huge benefit on the change mamagement in different workplaces. The study also highlights that the AI technology is more beneficial in emhancing the productivity, collaboration and efficiency and also acknowledges the challenges and limitations that must also be addressed. It provides an insight into the impact of AI technology on the workplace and makes recommendations for the organizations for the effective management and implementation of AI in the workplace.
Overall, looking at the results of the study, it is suggested that the productivity, efficiency and customer satisfaction of an organization can be increased through the use of AI technology. However, the concerns about the security of jobs and the need of skills for the employees should be managed to adopt any changes due to AI technology.
As concern to the change management, Lewin's mofel of change is helpful in guiding the implementation of AI technology to the workplace. The companies used three stages of unfreezing, changing and refreezing for successful implementation of AI technology.
Chapter 5: conclusion and recommendations
5.1 Introduction
The conclusion of this study indicates that in the UK there is a significant impact on the workplaces future of artificial intelligence. The majority believes that AI technologies increase job satisfaction, productivity and efficiency. However, regards to the loss of potential job and the need of workforce up skilling some concerns were also raised. Based on these findings, implement AI technologies sustainably and effectively to help organizations some recommendations should be made. While also ensuring the sustainability of their business practices and the well-being of their employee’s organization can harness the AI technology potential by adopting these recommendations
5.2 Conclusion
in conclusion, the study highlights that artificial intelligence has a significant impact on the change management. the organizations need to carefully make a plan and implement the AI technologies in their works so that the successful change management can be ensured. moreover the study also found that AI has a greater potential to improve efficiency and productivity. it also has the impacts on the security of jobs and there is also a need of train the employees to cope with changes by AI in the system. the research methodology that is used in this study also highlights that the questionnaire survey, frequency data analysis and the deductive research approach are very useful methods for studying the impact of AI technologies on the workplace. the literature recommends that the organizations should make enough investment s in training the employees and should develope such programs in which the employees are taught to adress the challenges and opportunities that can be presenr by AI technology.
5.3 Recommendations
Based on these research conclusions and the findings, it is recommended that UK organizations in their workplace are considering implementing the technologies of artificial intelligence to gain a competitive advantage and to improve their organizations of business. Organizations should provide transparent policies and clear communication, prioritize employee training and any concerns that are related to the social and ethical AI implications should be addressed to ensure the implementation successfully. Additionally, to ensure they mitigate potential risks and effectiveness organizations have to invest in the evaluation and continuous monitoring of their systems of AI. Finally, to govern the responsible and ethical use of AI in the workplace guidelines and regulations should be established by policymakers.
5.4 Limitations of study
One limitation of this study is the lack of probability sampling in the data collection method which may impact the interpretation of the findings. Additionally, the questionnaire method used may not capture emotional responses or feelings of the respondents, resulting in potentially useful data going unnoticed. Another limitation is that the sample size is relatively small, consisting of only 25 business professionals within the UK who have implemented AI technologies. Therefore, caution should be exercised when generalizing these findings to other contexts or populations. Finally, the research approach used in this study is deductive, which may not capture the full complexity of change management within the workplace.
5.5 Suggestions for further study
Further studies can expand the scope of research to other industries to investigate how AI can benefit them. Moreover, future studies can focus on qualitative methods to capture the emotional responses and feelings of the participants in addition to quantitative methods. Additionally, future research can explore the potential ethical concerns and implications of AI implementation in the workplace. Lastly, longitudinal studies can be conducted to observe the long-term impact of AI technology on the workplace and identify any changes or adaptations required to ensure the smooth integration of AI.
5.6 Summary
This research explores the impact of Artificial Intelligence (AI) on change management in the workplace of the UK. The deductive research approach was used to investigate this topic. The data collection method used was a questionnaire survey with 25 business professionals from different UK organizations who had implemented AI technologies. Frequency data analysis was used to analyze the data collected. The results indicated that AI technology is having a significant impact on change management within the workplace. However, the limitations of the research include the lack of emotional responses captured by the questionnaire survey. Recommendations for further research include investigating the impact of AI on specific industries and conducting interviews to capture more in-depth and emotional responses.
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