Role of automated learning ability of AI systems
The foremost determination of the paper is to investigate the role of the automatic learning ability of the AI based systems. Most of the business organizations all over the world uses the automated learning ability of the AI based systems and this paper will be very much effective for the organizations who are planning to implement this technology in their working environment. Along with this accounting organization other similar organizations such as the Accounting and Finance Association of Australia and New Zealand also uses the automated learning ability of the AI based systems.
The selected organization have numerous complexities associated in their business environment which can be solved purposefully with the help of the automated learning ability of artificial intelligence. The tax experience and the commercial skills are the two most essential components of this corporation which needs an automated system so that the inaccuracies can be resolved (Azuregroup.com.au. 2018). Planning for tomorrow is the mission and vision of this chartered accounting organization which can be improved with incorporation of the automatic learning ability of AI based systems.
Considering the incorporation of the new automated learning ability, there are numerous disadvantages associated with the system such as the lack of variability since it is an algorithm centric system, complexity in the installation and maintenance procedure of the technology and compatibility issues with the other technologies which are already present in the organization.
Primary data will be collected from an experienced professional who have the experience of working with the automated learning ability and secondary data will be presented in the literature review unit of the paper (Lewin 2018). The effectiveness of the paper will be maintained as it will consider both qualitative and quantitative data analysis technique in the research methodology unit. The paper will be also discussing the ethical concerns associated with this project. The following unit of the paper will be discussing the objectives and the aim of this paper.
This unit of the paper will be discussing the aims and objectives of the paper. The incorporation of the automated learning ability of artificial intelligence in the accounting sector has few limitations as well, the paper will be beneficial to minimize those issues. The prime objective of this paper is to highlight and address those issues in a detailed manner. The paper will be hugely useful for all the business organization where there are complexities due to the forced human errors. The productivity and the growth of the organization is hugely dependent on those challenges which will be discussed in the following units of the paper. The problem associated with the use of the automated learning ability of the artificial intelligence in the accounting sector will be discussed in the following unit of the paper.
Disadvantages of AI in accounting industry
This unit of the paper will be discussing the problem associated with the use of artificial intelligence in the accounting industry. There are numerous challenges associated with the incorporation of the automated learning ability of artificial intelligence in Azure Group Private Limited such as such initial investment for the management team, compatibility issue with the existing systems, complexity in installation and maintenance and algorithm centric system which lacks variability. These issues are needed to be mitigated in the first place so that the desired results are obtained from this new system. The questions which will be used to understand the topic in a better war will be presented in the next segment of this research paper.
The research questions which will be useful to understand the topic in a better way are as followings:
- Is the automatic learning ability really useful to understand the current trends in the accounting sector?
- What are challenges associated with the incorporation of the new AI based system.
- Can the automated learning ability of the AI based systems can be customised so that it can tackle with the issue of lack of variability?
This unit of the paper is considered as that secondary data collection for this paper, as it describes the opinion of the scholar about the incorporation of this new technology in the accounting industry.
As discussed by Lewin (2018), machine learning ability can be very much used in the business organizations as it can understand the needs and requirements of the consumers in a better way as compared with the human agents. The researcher focused on the fact that the automatic handling of the data sets can be managed in a more effective way with the help of the artificial intelligence systems. The researcher stated there are more advantages associated with the use of artificial intelligence than its limitations. The researcher stated that there are inaccuracies associated with human agents working in the accounting sector which have a direct negative impact on the growth and productivity of the organization (Poosapati, Katneni and Manda 2018). The researcher also stated that every artificial intelligent system is algorithm centric so it works under a fixed set of instructions, and as the needs and requirement of the consumers are always changing the fixed set of instructions are sometimes very much bad for this organization considering the business aspects. The prime advantage of this paper is that it focuses on both the advantage and disadvantage of the use of AI in the accounting industry.
As stated by Kokina and Davenport (2017), there are different categories of limitations associated with the use of the automated learning ability of artificial intelligence in the accounting sector such as the high installation cost, higher maintenance cost, cost involved with the training schedules which are needed to be provide to the employees so that they can be aware of the technology (Fernández-Macías et al. 2018). Creativity is something which is lacking in this technology as it is always algorithm based. Problems such unemployment are the other issues associated with the application of the automated learning ability of the intelligent systems in the accounting industry. The challenges associated with the use of the automated learning ability is properly described in this paper which is the most striking feature of this paper (Kokina and Davenport 2017). The drawback of this paper is that it does not consider the challenges faced by the employees of a business organization who have been suffering from the use of automated learning ability.
Data collection and analysis
According to Barnett and Treleaven (2017), the current trends in the field of accounts and finance can be successfully implemented in business organizations with the help of the automated learning ability of artificial intelligence. The business reports can be successfully managed with the help of artificial intelligent systems. There are lots of compatibility issues with the application of the automated learning ability of artificial intelligence. The new laws and regulations should be incorporated into the AI system so that the current trends in the competitive market can be implemented in the business organizations (Smith and Anderson 2014). The security of the artificial intelligent systems is the other limitation associated with this technology. The paper helps in concluding the automated learning ability of the AI bots are used to compare the services of the other similar industry so that business strategies can be implemented.
As discussed by Poosapati, Katneni and Manda (2018), automated learning ability of the intelligent systems are very much important for the accounting industries as automated learning ability and the machine learning ability can be hugely beneficial to optimise the business processes of this industry. The current accounting market can be analysed in a more efficient manner with the use of the machine learning and automated learning ability. Identification of the relationships between the stakeholders of the accounting organization can be conducted in a better way with the help of the intelligent systems (Galarza 2017). The prime advantage of the paper is that it provides reliable information about the inaccuracies of the human system used in the accounting sector. The researchers of the paper also stated about the importance of the automated learning ability in managing the accountants of the clients of the accounting organizations (Mørch 2013). However, there is a drawback associated with the paper, it do not describes the disadvantages of the automatic learning and machine learning feature of the AI systems.
According to Fernández-Macías et al. (2018), the application of the automated learning ability of artificial intelligence in accounting industry has resulted in the growth and progress of the business organizations. The researchers of the paper provided reliable information about the success of the automated learning ability across most of the global accounting organizations. The researchers specified the application of AI based systems in breaking down a large number of datasets into smaller subsets which are easier to be managed (McWilliams 2017). The researcher also focussed on the predictive analysis of the AI based system, as they are increasingly been used in the global accounting organizations. The most significant advantage associated with the paper is that it states about the positive impact of the technology in the selected industry in a detailed manner. However, the limitation associated with the paper is that is do not discusses the challenges faced by the employees while working with the AI systems.
Aims and objectives
As stated by Kumar, Lahiri and Dogan (2018), both academic scholar as well as practitioners have their opinions about the importance of the needs and requirements of the consumers and sharing economy firms. The researchers of this paper have highlighted the importance of the efficient utilization of the available resources. According to them, the customer relationship is very much important for business organizations so that the mission and vision of the organization can be achieved (Whitman and Sobczak 2018). Business models have been proposed in the paper which will be very much useful to understand the role of the service providers associated with the business organizations. The researchers of the paper also focussed on the importance of the service providers which are the prime external stakeholders associated with the business organizations (Barnett and Treleaven 2017). The prime advantage of the paper is that it focuses mainly on the impact of customer relationship on the business organizations however the limitations associated with this paper is that use of the automated learning ability of the artificial intelligence have not been described in this paper.
As discussed by Lin, Wu and Hsueh (2014), computer learning techniques can be hugely beneficial in our society. The researchers of this paper focused on the importance of electronic learning techniques with the help of the effective tutoring system. The usability and business strategies can be easily created and implemented with the help of the electronic platforms. Both qualitative and quantitative analysis have been used in the paper which provides reliability to the statements provided by the researchers (Smith and Anderson 2014). The researcher also stated the importance of the electronic learning techniques which can be used in the accounting organizations as there are lots of complexities associated with this industry. The prime drawback of the paper is that it do not discuss the impact of the automated learning ability on the accounting sector, it is written entirely in a generalized format.
According to Fernandez and Aman (2018), Robotic Process Automation (RPA) have a great impact on the accounting industry. The researchers stated that most of the global accounting organizations which have been successful over the years due to its wide range of services provided to the clients uses this automated technology (Peters 2017). The paper states that the incorporation of the RPA have both advantages and disadvantages associated with them. Each of the advantages and disadvantages are described in the paper in a professional manner which helps the other organizations who are looking forward to implementing these kinds of automated systems in their working environment (Tredinnick 2017). This paper has minimum limitations as it covers all the essential aspects of automated technologies which are used in the business organizations.
Challenges in using AI in accounting industry
As discussed by Parkes and Wellman (2015), artificial intelligence plays a huge role in the business organizations optimising each of the business units of the production rooms. The researchers focussed on the application of the AI based advanced systems in business organizations which provides them with a competitive advantage over the other similar rival organizations. The implementation of the artificial homo-economics and the neoclassical economics in the business environments are stated in the paper it a detailed manner (Brynjolfsson, Rock and Syverson 2018). The application of the artificial agents compared with the human agents are stated in the paper. Every business industry needs to provide customised products and services to their clients which is possible with the application of artificial intelligence (Wakelam et al. 2015). The prime advantage associated with this paper is that it provides in-depth knowledge about the effectiveness of the artificial agents as compared with the human agents.
This unit of the paper will be introducing the research designs of this paper. The effectiveness of the paper will be maintained with the help of the three different types of research designs such as the explanatory design, descriptive designs and exploratory design. This paper can be used in the future research process due to its reliability which is provided with the help of both primary and secondary data collected from experienced professionals and peer reviewed journals so it falls in the category of the exploratory design (Dicey 2017). The explanatory research design will be also incorporated into this paper as the paper will be very much beneficial for the other accounting organizations who are planning to implement the application of the automated learning ability of artificial intelligence in their working environment. There are lots of participants associated with the project such as the experienced professional who have already faced the challenges of this advanced technology in their office premises (Fernandez and Aman 2018). The opinions and the view of the consumers are very much essential for improving the reliability of this paper.
This unit of the paper will be considering the research methodologies used in this paper. The type of data collection method and the type of data analysis method will be presented here. The different categories of data sampling method will be also stated in this unit of the paper (Wirtz, Weyerer and Geyer 2018). The ethical issues associated with the projects will be discussed in this paper with primary importance, the unit will be also considering the risks associated with the project along with the assumed outcomes of the project.
Research Questions
This unit of the paper will be considering the research philosophies which will be considered in the paper. The two different categories of the research philosophy which will be considered in this research paper is positivism and interpretivism. Interpretivism philosophy will be useful in this project as we can implement the application of the use of artificial intelligence in the accounting industry. The roles and opinion of the scholars regarding the application of the automated learning ability of artificial intelligence are also considered in this category of the research philosophy (Furman and Seamans 2019). Positivism research philosophy will be also be considered in the paper as it will be based on scientific evidence of the application of this technology in the selected organization. Statistical tools will be considered in the data analysis phase of this project for the evaluation of the primary data which will be gather from the experienced professional who knows each minute details associated with this technology. The following unit of the paper will be focussing on the research methods used in the paper.
This unit of the part will be presenting the different categories of data collection method used in the paper. This research paper will be considering both qualitative and quantitative data collected method. The practise of both the different categories of the research methods will be very much essential for maintaining the effectiveness of the paper. The data collected from the experienced professionals of the business organizations using the automated learning ability of the artificial intelligence will be considered as the qualitative data and the data which will be collected from the peer reviewed articles will be considered as the quantitative data. The articles will be presented in the literature review unit of the paper (Mutiu 2016). Both the qualitative and the quantitative data will be very much useful to understand whether the automated learning ability of artificial intelligence can be effective in the accounting sector or not. The following unit of the paper will be discussing the different categories of data collection method used in this paper.
This unit of the paper will be presenting two different categories of data collection method. The effectiveness of this research paper will be dependent on the data collection method. Both secondary type of data collection and primary type of data collection method will be hugely beneficial for finding the impact of the automated learning ability of artificial intelligence. Primary data will be collected from the experienced professional who knows both the advantages and limitations associated with the application of automated learning ability of artificial intelligence (Mathur 2019). The data collected from secondary sources such as the peer reviewed scholarly articles which have the opinion of the researchers about the selected topic will be also significant to understand the impact and the challenges of the accounting industry on using the AI based advanced systems. The sampling of the collected will be considered in the following unit of the paper.
Opinions of Scholars on AI in accounting industry
A wide range of data sampling method will be selected in this research paper. The sampling of the data which are collected from the primary sources can be done with the help of the data sampling technique. The data sampling technique of the primary data will be done with the help of the statistical examination. Different categories of inspection techniques will be applied in this paper so that there are minimum inaccuracies involved with the paper. The different categories of inspection techniques are the likelihood testing strategy and the non-likelihood testing procedures. The choice of the populace of the literature review which is the secondary data of data collection method will be done using the non-likelihood testing strategy and the primary data will be evaluated with the help of the likelihood evaluation plan. The data sampling techniques are needed to be done very professional so that the unforced errors can be minimised to a significant extent. The following unit of the paper will be the most essential part of this paper which is the data analysis.
The prime determination of this unit of the paper is to discuss the different categories of data analysis methods. The data which are collected from the secondary data and the primary data will be analysed critically with the help of the analytical tools. Critical thinking procedures will be also very much beneficial to understand the data collected from reliable secondary sources. The data which are collected from the experienced professionals which are considered as the primary data will be analysed with the help of the qualitative data analysis technique. The data which are considered from the peer reviewed articles will be evaluated with the help of the quantitative data (Singh 2016). The analysis of the quantitative data is done with the help of the analytical tools of Microsoft Excel. The data analysis will be very much useful as the reliability of the raw data is sometimes questionable. The following unit of the paper will be discussing the ethical issues associated with this project.
Like every other research project this project also have numerous issues associated with it, the security associated with the collected data from both primary and secondary sources are the prime concern of this paper. The originality of the paper is needed to be maintained inspite of getting data from secondary resources and credentials are needed to be given to all the scholars and researchers whose data are being used in this paper (Manic et al. 2016). The data which are collected from the primary sources should also be maintained with high security. The participants should be allowed to make any kinds of decision regarding their opinions about the selected technology. The data which are collected from the experienced professionals of the accounting industry should be kept private considering the Data Privacy Act of 1998. Any kinds of interference should not be allowed in the data collection procedure as it might have a direct negative impact on the findings of the paper. The respondents should be given privacy during the data collection procedure. The participants of the research paper do not need to clarify their statements and their opinion or any kinds of justification.
There are numerous risks associated with this project. The primary risk associated with this project is the issue of funding as this project requires huge financial backup which are needed to be sanctioned before the data collection procedure of the project (Geist 2017). The handling of the primary data is the secondary risks associated with this project as any kinds of variations and changes may alter the findings of the project. Security of the respondents are the other risks associated with this project.
References
Azuregroup.com.au. (2018). Accountant Sydney, Business Accounting, Tax Accountant, Small Business Accounting. [online] Available at: https://www.azuregroup.com.au/about-us [Accessed 7 Dec. 2018].
Barnett, J. and Treleaven, P., 2017. Algorithmic Dispute Resolution—The Automation of Professional Dispute Resolution Using AI and Blockchain Technologies. The Computer Journal, 61(3), pp.399-408.
Brynjolfsson, E., Rock, D. and Syverson, C., 2018. Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics. In The Economics of Artificial Intelligence: An Agenda. University of Chicago Press.
Dicey, L., 2017. Accounting trends to watch in 2017. Professional Accountant, 2017(30), pp.14-16.
Fernandez, D. and Aman, A., 2018. Impacts of Robotic Process Automation on Global Accounting Services. Asian Journal of Accounting and Governance, 9.
Fernandez, D. and Aman, A., 2018. Impacts of Robotic Process Automation on Global Accounting Services. Asian Journal of Accounting and Governance, 9, pp.123-132.
Fernández-Macías, E., Gómez, E., Hernández-Orallo, J., Loe, B.S., Martens, B., Martínez-Plumed, F. and Tolan, S., 2018. A multidisciplinary task-based perspective for evaluating the impact of AI autonomy and generality on the future of work. arXiv preprint arXiv:1807.02416.
Furman, J. and Seamans, R., 2019. AI and the Economy. Innovation Policy and the Economy, 19(1), pp.161-191.
Galarza, M., 2017. The changing nature of accounting. Strategic Finance, 98(8), p.50.
Geist, E.M., 2017. (Automated) planning for tomorrow: Will artificial intelligence get smarter?. Bulletin of the Atomic Scientists, 73(2), pp.80-85.
Kokina, J. and Davenport, T.H., 2017. The emergence of artificial intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting, 14(1), pp.115-122.
Kumar, V., Lahiri, A. and Dogan, O.B., 2018. A strategic framework for a profitable business model in the sharing economy. Industrial Marketing Management, 69, pp.147-160.
Lewin, J.M., 2018. EMBRACING THE NEW WORLD OF WORK: Five trends are transforming the work of accountants and are presenting new challenges and opportunities for those who can adapt. Strategic Finance, 99(12), pp.32-38.
Lin, H.C.K., Wu, C.H. and Hsueh, Y.P., 2014. The influence of using effective tutoring system in accounting remedial instruction on learning performance and usability. Computers in Human Behavior, 41, pp.514-522.
Manic, M., Amarasinghe, K., Rodriguez-Andina, J.J. and Rieger, C., 2016. Intelligent buildings of the future: Cyberaware, deep learning powered, and human interacting. IEEE Industrial Electronics Magazine, 10(4), pp.32-49.
Mathur, P., 2019. Key Technological Advancements in Finance. In Machine Learning Applications Using Python (pp. 271-293). Apress, Berkeley, CA.
McWilliams, K., 2017. Productivity in accounting services. Improving service sector productivity: the economic imperative, p.118.
Mørch, A.I., 2013. Information seeking and collaborative knowledge creation: Exploring collaborative learning in customer service work and software product development. In Computer-supported collaborative learning at the workplace (pp. 293-313). Springer, Boston, MA.
MUTIU, A.I., 2016. An Analysis of the Disequilibrium between the Business Environment’s Expectations and the Modern Curricula. Corporate Governance in Knowledge-Based Society.
Parkes, D.C. and Wellman, M.P., 2015. Economic reasoning and artificial intelligence. Science, 349(6245), pp.267-272.
Peters, M.A., 2017. DEEP LEARNING, THE FINAL STAGE OF AUTOMATION AND THE END OF WORK (AGAIN)?. Psychosociological Issues in Human Resource Management, 5(2).
Poosapati, V.R., Katneni, V. and Manda, V.K., 2018. Cognitive Automation in Industry–Design Principles and Case Study. International Journal of Applied Engineering Research, 13(20), pp.14827-14831.
Singh, H., 2016. Artificial inteligence revolution and India’s AI development: challenges and scope. Internacional Journal of Science and Research. 5v.
Smith, A. and Anderson, J., 2014. AI, Robotics, and the Future of Jobs. Pew Research Center, 6.
Tredinnick, L., 2017. Artificial intelligence and professional roles. Business Information Review, 34(1), pp.37-41.
Wakelam, E., Jefferies, A., Davey, N. and Sun, Y., 2015. The potential for using artificial intelligence techniques to improve e-Learning systems. In ECEL 2015 Conference proceedings.
Whitman, C. and Sobczak, M., 2018. AI: Overrated or the Future of Accounting.
Wirtz, B.W., Weyerer, J.C. and Geyer, C., 2018. Artificial Intelligence and the Public Sector—Applications and Challenges. International Journal of Public Administration, pp.1-20.
Order an Essay Now & Get These Features For Free:
Turnitin Report
Formatting
Title Page
Citation
Outline
