The use of AI to drive productivity and innovation in the UK Midlands A multi-case comparative study of varied work organisations Assignment Sample

Introduction:To investigate the use of AI to drive productivity and innovation in the UK Midlands. A multi-case comparative study of varied work organisations within retail industry

Background

Innovation refers to the process of initiating new ideas, method or product that aids in enhancing customer’s experience and increase value of services. This is the crucial element in each organization as it support in increasing efficiency of the business entity and help in creating competitive edge within the industry. Artificial intelligence (AI) implies the art of making machines and technology think like the humans. AI refers to the computer systems that are capable in undertaking diverse and complex task that were initially undertaken by the human beings such as problem solving, decision making and reasoning.

The AI technology was introduced in year 1950 and more than 78% of retail stores in UK have integrated the AI technology in their operations. The retail sector of UK is contributing significantly towards the overall economic growth of the UK. It has identified that more than 2.7 million job opportunities has been created in retail sector of UK and there are more than 314040 retail business within the country (Retail sector of UK, 2023). Tesco, Morrison and Aldi are the leading retail company of UK and involve towards providing wide ranges of consumer goods and services. This includes books, clothing grocery, electronic, internet services, financial services, software and many more. This proposal will depict on the role of AI in enhancing overall productivity and innovation within UK’s retail sector. Various methodologies will also be discussed for better understandings the research issue.

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Rationale

The present study will discuss on the role of the AI technology in driving innovation and productivity within the retail industry of UK. This is the research issue as AI has introduced in the retail sector and it is crucial to identifying its impact on overall organisation’s performance. In the current time, innovation is the crucial requirement of each organization as customer’s taste and preferences are changing continuously. For maintaining stability in such environment, each firm needs to initiate innovation as to enhance customer’s loyalty and maintaining profitability (Sohn et al, 2020). Moreover, the use of AI has increased in the business entity with the aim of providing seamless experiences to the customers. This requires firm to identify the role and influence of the AI in promoting innovation within the retail sectors. This study will also help in determining the negative impact that could caused due to AI and help in taking proactive actions on time. Thematic analysis will be used to shed light on the importance of the AI in fostering innovation and productivity within the retail sector of UK.

Aims and objective

Aims:

The aim behind initiating current study is to ascertain the role of AI in fostering productivity and innovation within varied organisation.

Objective:

• To study the concept of Artificial intelligences and its types.
• To evaluate the significance of innovation within UK’s retail industry.
• To ascertain the role of AI in enhancing innovation and productivity.
• To suggest competent strategies for promoting innovation within UK’s retail sector.

Research questions

Q1. What is the meaning of AI and its types?

Q2. What us the importance and requirement of innovation within Retail sector of UK?

Q3. What is the impact of AI in driving innovation and productivity within UK’s retail industry?

Significance

The research holds the importance in depicting the relationship between AI integration and innovation within UK’s retail industry. This study will help in creating awareness regarding all the positive and negative impact of such technology on the fostering innovative culture within organization (La Torre et al, 2023). Current research will also assist organization in effectively initiating AI so that negative consequences could be eliminated. Many other organizations in the retail sector of UK could use this research to determining the need of AI model for creating competitive edge.

LITERATURE REVIEW

The Concept of AI and its types

According to Oosthuizen et al, (2021) AI refers to the stimulation of human intelligences that are process within computer system and machines. AI helps in enhancing the retail operations and support in effectively carrying out all the process with utmost efficiency. This technology helps in mitigating the risk and support in enhancing decision making process by providing effective data. Based on the view point of Heins (2023) there are large numbers of AI models that have initiated and implemented within the retail industry of the UK. Inventory management is one of the tools of AI in which technology evaluated the optimum demand of the particular product and suggests the level of inventory that shoddy be available within the entity. This help in firm in reducing the risk of under or over stocking and support in effectively managing firm’s cost. For example: Tesco has initiated AI technology that help in evaluating the past data abased on which appropriate suggestion are provided regarding the inventory level.

Moreover, Dwivedi et al, (2021) explicated that AI Chabot are most useful and significant tool used within the retail industry of UK. Customer’s satisfaction is highly impacted by the after sales services provided by the business entity. Chabot has resulted in managing all the queries and issues of the customer and involve towards quickly responding to them. This help in resoling customer’s issues and support in enhancing overall customer’s satisfaction. For example: Aldi has initiated, chat with Aldi Chabot that contribute towards decreasing customer’s queries and support in increasing their motivation level. Guha et al, (2021) stated that AI has been initiated within the retail sector with the objective of price optimisation that aids in managing profitability position of the business entity. AI data analytics and algorithms involve towards suggesting the most optimum price of the particular product and services so that overall budget of the organization did not get impacted. This also helps in evaluating the existing pricing strategy and recommended changes that should be initiated with the aim of enhancing company’s financial position.

Importance of innovation

According to the view point of Cao (2021) innovation plays a crucial role in overall growth and development of the retail industry of the UK. Innovation helps in increasing overall profitability of the business entity and support in maintaining stability within the industry. Innovation provides tangible values to the customer that helps in attracting them towards the company and result in increasing firm’s profitability position. For example; Tesco has initiated a self service checkout or tills services which mitigate the need of staff at the checkout process that leads to enhancing customer’s experiences. On the critical point of view, Jin and Shin (2020) claimed that innovation is creating negative impact on the firm’s overall productivity and performance. Innovation has resulted in increasing firm’s cost by 24% as this requires high investment at the initial level that impact on firm’s budget.

Har et al, (2022) asserted that innovation support in maintaining stability within the retail industry that indicate long term growth prospect of the firm. Innovation in the firm’s operation helps in gaining attention of customers by providing new services to the customer that has resulted in creating competitive edge within the industry. For example: Aldi has automated the stores operation that has resulted in providing seamless experiences to customer and aids in attracting large number of customers. Moreover, Mariani, Machado and Nambisan (2023) stated that innovation help in creating positive image in the mindset of the customer that has resulted in the enhancing overall firm’s profitability. Company that are having vision and mission of continuous innovation are able to create a positive image in customer’s mindset that result in enhancing overall sales.

Based on the view point of Grewal et al, (2021) it has professed that innovation has resulted in enhancing adaptability within firm. A firm that are continually brining innovative technology and ideas are able to enhance adaptability skill of the employee’s result in better services. For example: Morrison is focused over initiating innovative technology on regular basis that motivate employees to enhance their adaptability skill for managing stability within company.

The role of AI in driving innovation

Based on the view point of Ameen et al, (2021) it has depicted that AI integration has created both positive and negative impacted on the innovation and productivity within the retail sector of UK. AI integration has resulted in generation of new idea by evaluating the current market trend and needs. This technology is involved in evaluating the market trend based on which suggestions are provided regarding new innovation. For example: Tesco is using trend analysing AI tool that is involve towards analysing the market and provide most suitable recommendations regarding the innovation (Innovative approach of Tesco, 2024).

However, Bahoo, Cucculelli and Qamar (2023) asserted that AI tools provide biased suggestion that creates negative impact on the overall innovation within the company. As mentioned, Tesco is using trend analysis tool but this technology proved biased decision due to the algorithm biases and inappropriate training data that has been provided to the devices. Babu et al, (2024) stated that AI technology help in assessing the risk that are associated with the particular innovative ideas and support in taking most effective decision. The financial analyst tool of AI and the Risk watch are the two crucial risk assessment tools that have been used for identifying the compliance and financial risk associated with the innovation. For example: Aldi has initiated the tools that help in effectively identifying any potential compliance and financial risk associate with the new ideas and support in making informed decision.

On the critical point of view, Sharma et al, (2022) stated that AI technologies are not effective in identifying the Human risk associated with the ideas that hampers the overall effectiveness of new innovative idea. Based on the view point of Maixé-Altés (2020) it has determined that AI provide information regarding the infrastructure development that will be need in the business entity which help firm in determining overall budget of the new ideas. This tool help firm in identifying and predicating the necessary resources required for the ideas and suggest the sources through which such resources could be acquired. Such suggestion helps firm in identifying suitability of each innovative idea and support in effective implementation of the idea. On the critical point, Varsha et al, (2021) explicated that AI did not suggest recommendations based on firms’ financial position that ultimate impact on overall profitability of the business entity.

Literature gap

Prior research has been conducted on the importance of AI in the retail industry of UK. However, concentration has not paid on determining AI’s influence in fostering innovation and productivity within the business entity (Sharma et al, 2021). This proposal will depict on the role of AI in enhancing innovation which support in overall growth of business entity.

RESEARCH METHODOLOGY

Research type

Research type refers to the various methods and procedure that are used for collecting, analysing and interpreting the data. The two crucial method of research type includes quantitative type and qualitative type (Ahmad et al,2019). Qualitative research includes gathering non numerical data where as quantitative research includes gathering numerical information regarding the topic. In context of determining impact of AI, Qualitative research will be initiated as to determine the belief and attitude of respondent. This method has been selected as it aids in capturing diverse information and support in gathering targeting information resulting in optimum research. Further, this type provides flexibility in data collection that helps in gaining more reliable and accurate information.

Research approach

Research approach refers to the general techniques and plans that research followed while analysing and interpreting the data. Inductive approach and deductive approach are the two most common and effective type of research approaches (Alharahsheh and Pius, 2020). Inductive approach includes developing a new theory and concept whereas deductive approach focuses on testing and evaluating the existing theory. For identifying impact of AI on innovation, inductive research approach will be used by the research. This research method will be used as it promotes flexibility that support in studying and evaluating new concept and phenomena. Inductive approach aids in enhancing understanding of research issues by determining probability in data and support in identifying cause behind the particular phenomena. This approach is based on holistic view that helps in determining new theory that aids in gaining accurate information regarding the issue.

Research philosophy

Research philosophy implies certain beliefs and assumption based on which data has been gathered, analysed and interpreted (Bauer et al, 2021). The two most crucial type of research philosophy includes positivism and Interpretivism philosophy. Positive philosophy holds that all the accurate knowledge could be gained either by observation or the measurements. Interpretivism philosophy is sociology method includes analysing and interpreting action based on the values belief and norm within the society. In the present study, Interpretivism philosophy will be used by the research for better understanding the role of AI. This philosophy will be used as to identify social situation, mindset and motivation of the respondent. This method has been selected as it support in gaining reliable information by analysing human perception. Additionally, quantitative research could be effectively carried out by using Interpretivism philosophy.

Data collection

Data collection refers to process of collecting and measuring data that help in answering question, testing hypotheses and analysing the outcome. Primary data collection and secondary data collection are two distinct method of gathering information (Bloomfield and Fisher, 2019). Primary data collection refers to process of gaining information from the first hand source. Secondary data collection includes gathering information from the already published sources such as database and public record. For determining the role of AI in innovation, both primary and secondary data collection method will be used by the researcher. Under primary method, 10 manager of Tesco, Morrison and Aldi will be surveyed with the help of questionnaires. Secondary data collection will be used as it aids in gaining perception of diverse authors which help in conducting effective research. For gaining secondary information, various books and journal will be analysed and interpreted by researcher. Goggle scholar will be used to get easy access to large number of articles and journals.

Sampling

Sampling implies the procedure of selecting respondent form the total population as to conduct primary research (Chandra et al, 2019). Probability and non probability sampling methods are two crucial methods through which samples could be selected. Probability method includes random selection of respondent whereas non probability research method includes choosing respondent on particular judgment. For identifying impact of AI integration, probability method will be initiated by the research. Under this method, 10 manager of Tesco, Aldi and Morrison will be selected on which survey will be initiaed via questionnaires.

Data analysis

Data analysis refers to structuring raw data that aids in gaining insight of the issue and support in decisions making process. SPSS and thematic data analysis are two significant methods through which gathered information could analysed. SPSS is the statistical tool that is used for analysing the quantitative data whereas thematic analysis includes utilization of themes and pattern for evaluating quantitative data (Duckett, 2021). In the context of depicting role of AI integration, thematic data analysing method will be used by the researcher. This analysing method will be used for developing theoretical framework by linking existing theories to the Literature review. Additionally, qualitative research type will be used that could be accurately and efficiently analysed through thematic approach. Thematic analysis method helps in gaining reliable information and support in effective interpretation by drafting graphs and pie charts.

Ethical consideration

Ethical consideration implies the set of rule, principles and guidelines that are utilised for carrying out activity in fair and ethical manner (Fischer, Boone and Neumann, 2023). In the present study, various ethical actions will be initiated as to ensure confidently and anonymity in the research. A consent form will be filled up by the respondent that indicates that results are obtained without any external forces or coercion. The questionnaires will be filled up by using digital method which helps in maintaining confidentiality of the data. Further, random sampling method will be used that ensure equality as it provides fair opportunity to each individual to be selected as the respondent. While using secondary data, all the information will be effectively citied that will provide appreciation to original researcher and a reference list will be added to ensure accuracy of the collected data.

Research Limitation or are of concern

The depth of the research is impacted by various limitation and shortcomings. The amount of the data collected could limit due to lack of time and cost (Hodge, 2020). For conducting primary research, there is requirement of high amount of time and cost to actual meet the respondent and collect all the necessary information. For overcoming the issue, both primary and secondary data collection method will be used by the researcher. Secondary method helps in easily gaining access to large amount of information that support in overcoming the constraint of time. Further, researcher could use Google scholar to gain articles which reduces the cost for conducting the research. Due to lack of time, SPSS method of data analysis has been avoided and thematic approach will be used by the researcher. Thematic analysis includes the formation of graphs and pie chart that help in quick interpretation of the data and support in gaining faster outcome. Due to financial constraint, research will not be able to use diverse software for the research which will impact on the efficiency of the research. Further for overcoming the constraint of time, Random sampling method has been used over non probability method. Non probability method requires in-depth analysis of characteristic based on which respondent are decided then ultimate selection has been carried out. So random sampling has been used which help in selection of respondent in a time effective manner.

Books and Journals

• Ahmad, S., Wasim, S., Irfan, S., Gogoi, S., Srivastava, A. and Farheen, Z., 2019. Qualitative v/s. quantitative research-a summarized review.em>population,em>1(2), pp.2828-2832.
• Alharahsheh, H.H. and Pius, A., 2020. A review of key paradigms: Positivism VS interpretivism.em>Global Academic Journal of Humanities and Social Sciences,em>2(3), pp.39-43.
• Ameen, N., Tarhini, A., Reppel, A. and Anand, A., 2021. Customer experiences in the age of artificial intelligence.em>Computers in human behavior,em>114, p.106548.
• Babu, M.M., Rahman, M., Alam, A. and Dey, B.L., 2024. Exploring big data-driven innovation in the manufacturing sector: evidence from UK firms.em>Annals of Operations Research,em>333(2), pp.689-716.
• Bahoo, S., Cucculelli, M. and Qamar, D., 2023. Artificial intelligence and corporate innovation: A review and research agenda.em>Technological Forecasting and Social Change,em>188, p.122264.
• Bauer, G.R., Churchill, S.M., Mahendran, M., Walwyn, C., Lizotte, D. and Villa-Rueda, A.A., 2021. Intersectionality in quantitative research: A systematic review of its emergence and applications of theory and methods.em>SSM-population health,em>14, p.100798.
• Bloomfield, J. and Fisher, M.J., 2019. Quantitative research design.em>Journal of the Australasian Rehabilitation Nurses Association,em>22(2), pp.27-30.
• Cao, L., 2021. Artificial intelligence in retail: applications and value creation logics.em>International Journal of Retail & Distribution Management,em>49(7), pp.958-976.
• Chandra, Y., Shang, L., Chandra, Y. and Shang, L., 2019. Inductive coding.em>Qualitative research using R: A systematic approach, pp.91-106.
• Duckett, L.J., 2021. Quantitative research excellence: Study design and reliable and valid measurement of variables.em>Journal of Human Lactation,em>37(3), pp.456-463.
• Dwivedi, Y.K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A. and Galanos, V., 2021. Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy.em>International journal of information management,em>57, p.101994.
• Fischer, H.E., Boone, W.J. and Neumann, K., 2023. Quantitative research designs and approaches. Inem>Handbook of research on science education (pp. 28-59). Routledge.
• Grewal, D., Guha, A., Satornino, C.B. and Schweiger, E.B., 2021. Artificial intelligence: The light and the darkness.em>Journal of Business Research,em>136, pp.229-236.
• Guha, A., Grewal, D., Kopalle, P.K., Haenlein, M., Schneider, M.J., Jung, H., Moustafa, R., Hegde, D.R. and Hawkins, G., 2021. How artificial intelligence will affect the future of retailing.em>Journal of Retailing,em>97(1), pp.28-41.
• Har, L.L., Rashid, U.K., Te Chuan, L., Sen, S.C. and Xia, L.Y., 2022. Revolution of retail industry: from perspective of retail 1.0 to 4.0.em>Procedia Computer Science,em>200, pp.1615-1625.
• Heins, C., 2023. Artificial intelligence in retail–a systematic literature review.em>foresight,em>25(2), pp.264-286.
• Hodge, S.R., 2020. Quantitative research. Inem>Routledge Handbook of Adapted Physical Education (pp. 147-162). Routledge.
• Jin, B.E. and Shin, D.C., 2020. Changing the game to compete: Innovations in the fashion retail industry from the disruptive business model.em>Business Horizons,em>63(3), pp.301-311.
• La Torre, D., Appio, F.P., Masri, H., Lazzeri, F. and Schiavone, F., 2023.em>Impact of artificial intelligence in business and society: Opportunities and Challenges. Routledge.
• Maixé-Altés, J.C., 2020. Retail trade and payment innovations in the digital era: a cross-industry and multi-country approach.em>Business History.
• Mariani, M.M., Machado, I. and Nambisan, S., 2023. Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda.em>Journal of Business Research,em>155, p.113364.
• Oosthuizen, K., Botha, E., Robertson, J. and Montecchi, M., 2021. Artificial intelligence in retail: The AI-enabled value chain.em>Australasian Marketing Journal,em>29(3), pp.264-273.
• Sharma, S., Gahlawat, V.K., Rahul, K., Mor, R.S. and Malik, M., 2021. Sustainable innovations in the food industry through artificial intelligence and big data analytics.em>Logistics,em>5(4), p.66.
• Sharma, S., Islam, N., Singh, G. and Dhir, A., 2022. Why do retail customers adopt artificial intelligence (AI) based autonomous decision-making systems?.em>IEEE Transactions on Engineering Management,em>71, pp.1846-1861.
• Sohn, K., Sung, C.E., Koo, G. and Kwon, O., 2020. Artificial intelligence in the fashion industry: consumer responses to generative adversarial network (GAN) technology.em>International Journal of Retail & Distribution Management,em>49(1), pp.61-80.
• Varsha, P.S., Akter, S., Kumar, A., Gochhait, S. and Patagundi, B., 2021. The impact of artificial intelligence on branding: a bibliometric analysis (1982-2019).em>Journal of Global Information Management (JGIM),em>29(4), pp.221-246.

Online

• Retail sector of UK. 2023. Online. Available through: < https://researchbriefings.files.parliament.uk/documents/SN06186/SN06186.pdf>
• Innovative approach of Tesco. 2024. Online. Available through: < https://aithor.com/essay-examples/innovation-and-enterprise-at-tesco-essay#:~:text=At%20Tesco%2C%20innovation%20is%20approached,of%20new%20products%20and%20services.>

Author Bio

Casey Bennett   7 years | PhD

My name is Casey Bennett and I have obtained my graduation, post-graduation and PhD from London Business School. I have been giving education to students for the last 7 years in the United Kingdom. I can help you deal with complex dissertation topics, assignments, and essays and finish them fast.