Research Proposal Assessment Answer

1. Introduction and Business Context

In the current scenario, the proper application of advanced technologies including artificial intelligence (AI) and machine learning (ML) are the primary technologies which have been used by a large number of organisations for identifying several decisions. As depicted by Paliwal et al. (2021), many leaders are using these advanced technologies to provide different types of decisions as per their leadership and another context. These two technologies majorly use the statistical model along with the algorithm for identifying different types of patterns to make clear predictions depending on different types of data available in the market. In a particular management and leadership application, AI admission learning can be effectively used for improving their overall ability to analyse a good amount of data and to provide proper insights which can help the business organisation.

The ABC organisation is a hypothetical retail organisation which provides different types of products to their customers for getting a good amount of revenue along with profitability. This organisation faced different types of issues in identifying the appropriate decisions at the time of managing the overall business organisation. This organisation is very much well known for providing various types of clothes, furniture and home appliances to the customers. As illustrated by Devereux et al. (2020), Australia is one of the most advanced countries in the world. A large number of business organisations, especially retail organisations are already having their branches in different locations in Australia. For getting a good amount of consumer base, specially in Australia, the management body needs to be so much focused on developing various types of functionality which provide a good amount of results to their customers. The abc organisation needs to evaluate every friend of purchasing the clothes based products or furniture through the application of advanced equipment available in the market. The company also planned to initiate their online operations in different locations of Australia through their online service and by making a business deal with the third party delivery partners.

However, for getting business growth in the area of Sydney, understanding the customers inside and using the proper technology for development decisions are very much essential for the management body of ABC organisation. Therefore, the management body of the organisation has planned to include ML and AI for helping them to develop a particular decision for getting a good amount of support.

In the global market, the application of AI has reached around 309.6 million US dollars within the year 2020 (CB Insights, 2020). A huge amount of enhancement has been identified which helps the organisation to increase overall growth of the organisation. due to the overall market analysis and identifying the overall consumer area, the application of machine learning can provide the management and better idea of the life demand of the consumer base in a particular location.

In this research report, the background of the business organisation has been already analysed to provide a brief idea about the importance of using these technologies in the organisation. The application of literature is the second part where various pieces of literature are being collected on this topic of applying AI and ML for decision-making to identify the gap. The research questions along with the research methods are going to be analysed in this study to provide a clear idea about the overall data collection process. In the data and analysis part, different types of literature collected from secondary databases are going to be analysed for the research methods to provide proper recommendations for the ABC organisation in the chapter of the research project.

2. Literature Review

Introduction

The application of literature review is one of the major parts of the research which helps to analyse a large number of pieces of literature to get a better idea about the overall research paper. For gathering a good amount of literature, different types of data about the application of AI-related data are being collected to provide a clear idea about the overall impact on the business organisation. Similarly, different types of challenges and benefits of using AI and Ml are going to be evaluated in this research. Various types of technologies managed by AI and ML are also going to be evaluated in this research.

Critical evaluation of various applications of ML and AI in managing the business operations of the organisation

In the current situation, the application of ML and AI are the two types of technologies which provide better results in managing the technologies in getting better results. As depicted by Chen and Biswas (2021), in today's leading organisations, ML and AI are known as the proper technologies that help to automate the decisions for starting the experiment with more advanced applications of AI. Corporate investment in overall artificial intelligence is one of the advanced technologies which provide better results in managing the overall functionality.

Machine learning is known as the enabling technology which helps to expand their growth by optimising the overall process at the time of improving employee engagement and increasing customer satisfaction. The major benefits of using AI and machine learning are described below which offer better support in managing overall operations.

Personalising the customer service

Personalisation of customer service is one of the primary benefits of using AI and ML which helps the organisation to improve their overall customer service by using the overall cost which makes it one of the most effective areas for the business. As illustrated by Soni et al. (2020), combining the overall historical customer service data, different types of algorithms, and language processing from various kinds of interaction among the customers. Customers can also ask different types of questions which have been resolved by the basic organisation through the application of different types of ML and AI which provides purpose support to the management to get a good result. Customer service representatives can take different types of steps for handling various exceptions with the various algorithms to look at the overall next future.

Improvement of customer retention and loyalty

Companies can gather a good amount of data for customer transactions, actions and social sentiment which helps to identify the overall customers who are planning to leave the company. The application of various profitability of different types of data allows organisations to optimise all their next best action for the end-to-end customer experience. Different types of young adults currently prefer to have all types of discounts and offer from the organisation. Therefore, the organisation can use the proper application of machine learning for generating a good amount of revenue and make various types of customised offers for detecting the overall competitors.

Recruitment of the right people

Different types of corporate job openings can be easily done with the help of ML and AI which manages different types of productivity and business operations by implementing various types of AI and ML technologies. As stated by Aung et al. (2021), the application of automated recruitment processes can provide a huge amount of support to the business organisation for generating a good amount of revenue and managing their overall business process in nature. Shortlisting the right people by analysing the resume is one of the difficult parts which can be easily managed through the application of machine learning and automated systems that provide a good amount of support to the business to have proper employees and young talents.

Helping management to take different decisions

Currently, due to the customers changing behaviour the demand of a particular customer is changing day by day which creates several issues for the management to get better. Therefore, it is highly required for the management body to take different types of preventive measures which can offer support to the organisation at the time of taking proper decisions. AI and machine learning are the two primary technologies which use various types of advanced equipment along with the algorithm process to otherwise the future demand of consumers by evaluating the existing operation and data available to customers (Food and Drug Administration, 2019). Analysing the previous data history of customers, the application of AI and machine learning can easily predict the future trend of customers.

Detecting fraud and measurement of brand exposure

For a new type of business organisation, it is very much essential for the organisation to take proper promotional activities which can help to expose the brand in a highly competitive environment. Different types of automobile programs using these technologies can help to identify people's product logos and others which helps to maintain a good relationship with their customers.

Critical evaluation of different challenges faced by the organisation in implementing this technology

ML and AI are the two major technologies which help to change the overall operations of the business. The writing about driving self-cars clearly shows that most organisations are using various types of artificial intelligence for managing their overall practices. However, at the time of implementing different technologies, the management faced different challenges which affected the organisation to get proper support in a particular environment.

Machine learning and AI depend upon a set of data relevant to the topic which are effective in predicting future operations. Companies are facing so much struggle to use the AI algorithm with a higher rate of risk quality as the data volume is necessary for the business organisation. Improper or insufficient data created a huge amount of imbalance which can lead to discriminatory results which creates major issues. As opined by Vollmer et al. (2020), for the application of artificial intelligence, the proper development of infrastructure is very much essential to process a large amount of information in various fractions. This is the only way for achieving the overall operating devices with the various types of processing and infrastructure capabilities. A large number of businesses use different types of outdated equipment which note taking on various challenges in the AI generation. Most business organisations are using different types of learning and development methods with their emotions to be prepared for a good amount of frustration and applications that are technologically advanced.

For incorporating AI in the overall program, the application of a training program can provide a huge amount of support that is very much effective in managing different types of operations. As analysed by Sun and Scanlon (2019), the lack of knowledge among the employees along with their improper skillset created a huge amount of issues for the business organisation to implement these AI and ML in the overall implementation. For incorporating AI and ML in the business organisation, a huge amount of budget will be required for managing productivity in the environment.

Theoretical Framework

Asphalt analysis of different types of theoretical models, application of resource-based view (RBV), Innovation diffusion theories (IDT) and technology acceptance model (TAM) are the three famous frameworks which help to define the working of AI and ML in the organisation.

The RBV helps the organisation to understand the capabilities and resources for sustaining the competitive advantage. These two technologies are considered as the statistical resources which can help the business organisation to achieve the comparative advantage inside the customer's behaviour and identify various opportunities and operations. On the other hand

, the TAM explains the adoption of new technology for individuals (Kim et al. 2021). AI and ML are also known as new technologies that can be adopted by basic organisations for providing improved decision-making and valuable insights to management. The third theory is the innovation diffusion theory which explains the process of different innovations through the application of social systems. Therefore, as illustrated by Huang et al. (2022), ML and AI are also known as the major innovations which help to provide different types of support in getting an advantage in managing complexity and providing significant benefits over the traditional methods which impact business performance.

Literature Gap

To identify the overall factors, different types of literature have been gathered for getting a good amount of results. However, very little amount of data has been gathered about the management of AI and ML for identifying better decisions in the overall management process. Similarly, the application of proper techniques for managing the issues related to data is also very much less which motivated the researchers to continue their work on this topic to get better results.

3. Research Questions and Methods

Questions

How do ML and AI help the business leaders of ABC retailers to manage their businesses?

What are the primary benefits and issues of ML and AI in the decision-making process?

How does the ABC organisation improve their overall implementation process of AI and ML in managing the operations?

Methodology

The proper application of research methodology can provide a huge amount of support to the researcher to get proper findings. As depicted by Newman and Gough (2020), proper management of research methodology can help identify the overall findings from different types of databases. This study is based on identifying the importance of ML and AI in developing different types of decisions for the organisation ABC. Therefore, choosing the right methodology for all the research questions discussed above. As depicted by Marsonnet (2019), the researcher has used the positivism philosophy to get proper findings and to link the data with different variables of the research questions. This philosophy is also helpful for including realistic data in the overall research process to get some major findings. For gathering several ideas about the application of AI and ML in the organisation, implementation of this philosophy is very much appropriate to identify some major impacts of these technologies.

Evaluating the various approaches, the application of the deductive approach is very much effective which helps to develop hypotheses for analysing the case studies identified in different data. This approach is very much effective in managing the overall research in gathering a good amount of qualitative data. Analysing the strategies used by the researcher for managing this research work, the application of the case study strategy has been used by the researcher to analyse the case of applying AI and ML to develop different business decisions. Different types of data from various databases have been identified through the application of these strategies to get the major findings of the overall process. As analysed by Mohd Satar et al. (2019), the case study is used for generating an in-depth and multiplicative understanding of the various types of complex issues in a particular realistic context. This type of research design has been used by the researcher extensively based on different varieties of disciplines including the social sciences. However, in this research for identifying the impact of ML and AI, the application of this approach is very much beneficial for the researcher.

In identifying the case study design, the application of secondary data collection methods been used by the researcher. The application of inclusion and exclusion criteria including year, authenticity, topic-related and others have been used by the researcher to get the proper data about the research topic. 5 journal articles are being selected based on these criteria. Different types of databases such as ProQuest, Google Scholar and others have been chosen to collect the necessary information about the overall data.

For analysing the collected data, the application of thematic analysis has been used for getting major findings. A total of 2 themes are being developed to gather several information in managing the work for identifying the results. As per the overall research gap identified in the research, it is very much essential for the researcher. The application of purposive sampling has been used by the researcher to get the proper data in managing the overall research paper (Campbell et al. 2020). This type of sampling has been used in managing the research work for getting a good amount of data from the database.

Proper management of various ethics in the research is very much essential for the researcher to manage their findings and to get approval from the research committee. In this research, the researcher is very much focused on managing the copyright and plagiarism issues that helped the research to be authenticated. Secondly, the researcher also maintained all the laws and regulations of the country for starting the research work. As per the secondary collection method, no participants have been affected. It follows the confidentiality of different data from the database to find out this research.

Data and Analysis

The application of data analysis is one of the crucial parts which help the researcher to get the finding by analysing different types of data. As per the research methodology, thematic analysis is going to be done in this research to find out the overall findings of the research paper.

Theme 1: a critical analysis of the importance of using AI and ML in the decision making

In the overall activities, identification of various technologies ML and AI are the prime technologies that are effective to get better results in the overall competitive environment. The major benefits of using AI and machine learning are described below which offer better support in managing overall operations. As opined by Vollmer et al. (2020), the organisation can use the proper application of machine learning for generating a good amount of revenue and make various types of customised offers for detecting the overall competitors. Shortlisting the right people by analysing the resume is one of the difficult parts which can be easily managed through the application of machine learning and automated systems that provide a good amount of support to the business to have proper employees and young talents.

The application of ML and AI is also very much effective in managing different types of decisions by taking all types of data about the customers and their operations and purchase rate. As opined by Campbell et al. (2020), for making different types of decisions, the management needs to understand the previous customer behaviour in the organisation to predict the future. Therefore these advanced technologies can provide benefits to the researcher to manage the overall productivity of the environment.

Theme 2: a critical evaluation of various challenges in implementing the AI and ML

AI and ML are the primary technologies which are currently used by most marketing or management bodies for predicting future changes in customer preferences. As depicted by Huang and Rust (2021), machine learning and artificial intelligence are the two types of technologies which require proper focus from the implementation team and the end users to find out different findings. For developing the technology in the overall infrastructure of an organisation, it is very much essential for the management to identify all the benefits of AI and ML. However, the management body faced different issues at the time of implementing the advance in technology. Due to the improper infrastructure in the organisation, the management faced different types of difficulties in using this system. The less amount of skills among the employees can also create some major amount of difficulties which affect the overall decision-making process. As opined by Strusani and Houngbonon (2019), the higher rate of expensive technologies can also create a huge amount of issues in managing all their operations. Therefore, the business organisation needs to implement different types of statistics for mitigating the issues in the environment.

Discussion

AI and ML two technologies majorly use the statistical model along with the algorithm for identifying different types of patterns to make clear predictions depending upon different types of data available in the market. In a particular management and leadership application, AI admission learning can be effectively used for improving their overall ability to analyse a good amount of data and to provide proper insights which can help the business organisation. As depicted by Strusani, and Houngbonon (2019), Corporate investment in overall artificial intelligence is one of the advanced technologies which provide better results in managing the overall functionality. The abc organisation is one of the small medium sized enterprises in all over Australia who planned to expand a good amount of market into different cities. Therefore, analysis of the overall marketplace is very much effective which defines the major changes and the requirement of customers in a particular location of Australia. Currently, most of the customers are also preferring different types of organic and vegan products. Therefore analysing the overall market is very much important for every business organisation for expanding their marketplace through the application of advanced equipment. Analysing the overall operations, it can be depicted that these two technologies are very much beneficial for managing various activities. Similarly, it also offers the management to identify the major demand and requirements of customers. On the other hand, during the overall activities, the management faced huge issues which affected the overall operations of the organisation. Among the major issues, less knowledge, improper skill sets, outdated infrastructure and others created a huge amount of issues for the organisation to manage the overall operations.

After gathering a good amount of ideas about the major challenges and benefits of using artificial intelligence and machine learning in a particular environment, this organisation can get a good amount of support to analyse the realistic data about the changes of customers and future forecast the overall operations of the customers. Management of various customers can provide a huge amount of support to the organisation to gather the impact of different types of sustainable factors in the environment. The overall rate of customers' awareness towards sustainability and organic products has increased by huge amounts which also creates major issues for the small and medium size organisations especially for the ABC to face different difficulties. Thus, the organisation can use these advanced technologies like ML for predicting the future outcomes of the study and to gather proper insights about the data. Similarly, the AI can effectively track all the data and automate the operations of the logistics, and delivery of ABC group.. It can be also effective to solve the customer's query by giving a good amount of feedback and automated answers. It can be also effective to increase the loyalty and the customers' trust in the organisation. Therefore, recommending these technology can provide a huge support to ABC for managing various activities

Conclusion

This research report is based on the implementation of AI and ML in managing overall productivity. Evaluating the introduction, detailed information using AI and ML is being used for getting major decisions in the overall operations. In the literature review, different pieces of literature are collected to identify all the findings of the data. Along with that, as per the research methodologies, the application of secondary data collection has been used by the researcher to get a clear idea about the overall findings of the research. The thematic analysis has been done by the researcher to get proper findings. As per the analysis, it has been identified that AI and ML are very much appropriate for management to make different decisions. On the other hand, for mitigating the challenges, different recommendations can be useful which are described below.

Recommendation

Implementation of different types of training programs can be effective in providing proper support to the employees of the ABC organisation. Hiring the technical team tio install these technologies can offer proper opportunities to describe all their factors. Similarly, hiring training managers can provide proper support to upgrade the skills of employees in managing the environment. Upgradation of infrastructure can be effective for the organisation to have a better image in society.

References

Aung, Y.Y., Wong, D.C. and Ting, D.S., 2021. The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare. British medical bulletin, 139(1), pp.4-15.

Campbell, C., Sands, S., Ferraro, C., Tsao, H.Y.J. and Mavrommatis, A., 2020. From data to action: How marketers can leverage AI. Business Horizons, 63(2), pp.227-243.

Campbell, S., Greenwood, M., Prior, S., Shearer, T., Walkem, K., Young, S., Bywaters, D. and Walker, K., 2020. Purposive sampling: complex or simple? Research case examples. Journal of Research in Nursing, 25(8), pp.652-661.

CB Insights, 2021. The state of AI in 2021. CB insights. Available at: https://www.cbinsights.com/research/report/state-of-ai--trends [Accessed on 18th April, 2023]

Chen, Y. and Biswas, M.I., 2021. Turning crisis into opportunities: how a firm can enrich its business operations using artificial intelligence and big data during COVID-19. Sustainability, 13(22), p.12656.

Devereux, E., Grimmer, L. and Grimmer, M., 2020. Consumer engagement on social media: Evidence from small retailers. Journal of Consumer Behaviour, 19(2), pp.151-159.

Food and Drug Administration, 2019. Proposed regulatory framework for modifications to artificial intelligence/machine learning (AI/ML)-based software as a medical device (SaMD).

Huang, A., Chao, Y., de la Mora Velasco, E., Bilgihan, A. and Wei, W., 2022. When artificial intelligence meets the Hospitality and tourism industry: an assessment framework to inform theory and Management. Journal of Hospitality and Tourism Insights, 5(5), pp.1080-1100.

Huang, M.H. and Rust, R.T., 2021. A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, pp.30-50.

Kim, J., Merrill Jr, K. and Collins, C., 2021. AI as a friend or assistant: The mediating role of perceived usefulness in social AI vs. functional AI. Telematics and Informatics, 64, p.101694.

Marsonet, M., 2019. Philosophy and logical positivism. Academicus International Scientific Journal, 10(19), pp.32-36.

Mohd Satar, N.S., Dastane, D.O. and Ma’arif, M.Y., 2019. Customer value proposition for E-Commerce: A case study approach. International Journal of Advanced Computer Science and Applications (IJACSA), 10(2), pp.454-458.

Newman, M. and Gough, D., 2020. Systematic reviews in educational research: Methodology, perspectives and application. Systematic reviews in educational research: Methodology, perspectives and application, pp.3-22.

Paliwal, M., Patel, M., Kandale, N. and Anute, N., 2021. Impact of artificial intelligence and machine learning on business operations. Journal of Management Research and Analysis, 8(2), pp.70-75.

Soni, N., Sharma, E.K., Singh, N. and Kapoor, A., 2020. Artificial intelligence in business: from research and innovation to market deployment. Procedia Computer Science, 167, pp.2200-2210.

Strusani, D. and Houngbonon, G.V., 2019. The role of artificial intelligence in supporting development in emerging markets.

Sun, A.Y. and Scanlon, B.R., 2019. How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions. Environmental Research Letters, 14(7), p.073001.

Vollmer, S., Mateen, B.A., Bohner, G., Király, F.J., Ghani, R., Jonsson, P., Cumbers, S., Jonas, A., McAllister, K.S., Myles, P. and Grainger, D., 2020. Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness. bmj, 368.

Vollmer, S., Mateen, B.A., Bohner, G., Király, F.J., Ghani, R., Jonsson, P., Cumbers, S., Jonas, A., McAllister, K.S., Myles, P. and Grainger, D., 2020. Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness. bmj, 368.

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