AI is providing solutions of different problems using optimization and many methods. There are so many algorithms, which can reduce the time of different processes in business. It is most common approach to analysis the business processes using different methods. There are many approaches in business management. However, all those approaches are providing best results to manage business processes of an organization. AI is creating new things that are useful for society and business in future (Benjamins, 2006).
Furthermore, AI can provide better business system analysis. Every business is having different operations. Therefore, it is necessary to analyses those processes and create new system to manage those operations in better way to increase growth, productivity and revenue of an organization. AI powered business strategy is increasing performance and profitability of business ( Byrnes, 2018).
In business, procedures and methods can be improves through examining a business situation and it will helpful for system analysis and design. It is necessary process to shaping organizations as well as improving performance. It will provide objectives for growth and productivity of organization. In an organization, many subsystems are providing help to meeting a common goal. AI is helping in every field of business to grow organization (Castelluccio, 2017).
An organization has a proper structure and order to maintain different operations for their business. It is having a proper arrangement of different components, which are helpful to achieve objectives. Hierarchical relationship is used to design of a business system mostly in organization. Big data and AI is a great combination and it will change the scenario of current business approaches (Chen, Chiang, & Storey, 2012).
AI-driven application is affecting most of the industries. In above diagram, it is divided in three ranks. Mainly it is affecting the information technology area of business then customer services and operations or manufacturing processes of an organization. AI is reshaping the present business strategies ( Ransbotham, Kiron, Gerbert, & Reeves, 2017).
Organizations are having Management Information System (MIS) to manage different operations that are used to manage business processes. MIS is having a capability to manage the operations of organization. It was designed to handle all the services and products of the organization. It is necessary to identify the system performance and feasibility of an organization to change existing system processes. System performance can be increased using identification of specific system objectives. Artificial neural network is providing backtracking and other techniques that are helpful for risk analysis (Tká? & Verner, 2016).
Feasibility study can provide a basic idea of system design and it will provide an idea to change the business processes. Feasibility study of system includes these things, which are feasibility consideration, economic feasibility, technical feasibility, and behavioral feasibility. AI is most popular technology that is accepted in business analysis processes ( Garfinkel, 2018).
AI provides help to create new features in the MIS of organization and it will useful for cost and benefits of organization. Using MIS and new methods, organization can manage their tangible and intangible costs and benefits from different business processes. There are many processes in organization, which provides direct or indirect costs and benefits (Ghosh, 2017).
Therefore, it is necessary to examine the system for increasing saving and reducing cost of different processes of business. In addition, evaluation methods are helpful to identify the cost effective processes in the system. Business intelligence is highly required to enhance the business strategies (Ho?evar & Jakli?, 2010).
AI-Driven development is highly occupied in business system analysis through organizations in present era. From last two decades, AI-driven development is providing better result in business system analysis. Now, MIS systems are designed with AI algorithms and models as well as other features that are used to integrating AI capabilities. AI is helping in business intelligence. It can provide better tools and services to understand business strategies (Isik, , Jones, & Sidorova, 2013).
In present time, highly advanced MIS, systems are designed, which are having AI-Powered environments that are managing all the functional and nonfunctional processes of business in a better way. AI provides different tools that can be handling easily and it will drive a different level of flexibility to a business analyst. Artificial intelligence is enabling an option in business system that is business intelligence. Most of the organizations are having their own databases and data warehouses. In addition, they are also having daily reports as well as annual report. Those are helpful for identification of issues and challenges in business. AI is providing better algorithms, which are helpful for the business system analysis, such as neural network algorithms, backtracking, and many others. AI is providing decision making power based on the data analysis (Turban, Sharda, & Delen, 2010).
Data mining is having many algorithms that are based on the AI, such as Apriori Algorithm, clustering, decision-making, and many others. AI is enabling system to calculate all the issues in the existing system based on the collected data, such as financial report of an organization. AI provides better collaboration between AI-driven tools and business strategies (Klumpp, 2018).
AI can make computers smart to take decisions based on the data and controls. MIS systems can intelligent using AI. AI makes many changes in the process of business, which can enhance the profitability of an organization. In every field, AI is helping to reduces complex processes, such as industry, education, health sector, communication, business, banking, transportation, tourism, and many others. AI provides an environment and it maximizes the performance of an organisation to achieve its missions. AI can implement many systems that reduce human efforts and provide security and privacy to different business processes, as an example a computer system can accept loan application and takes a decision based on its data and information (Laney, 2012).
AI-driven systems are having learning capability. Therefore, they can take decision based on the data and it is beneficial for the machine and organization. It will be beneficial for the organization that machine can take decision based on the intelligence. An organization can make their business intelligent using AI and it will be Business Intelligence (BI). AI provides a base to the organization and BI is a new way to manage different operations of an organization in an efficient way. AI is having two areas, which are most popular in present time that are machine learning and deep learning. Machine learning is so beneficial for those industries, which are based on the data and machines. A computer system can maintain the entire machine using mechanical concepts and computer knowledge. It can increase performance of a system using machine learning. AI increases business intelligence, which is reduces losses of organization (Zeng, Li, & Duan, 2012).
Above diagram is shows expectations for AI adoption across industries operations. It will defiantly enhance the business of an organization. In next five years, it will change the performance of the complete system and it will increase growth and revenue of organization ( Ransbotham, Kiron, Gerbert, & Reeves, 2017).
Deep learning is useful in those businesses that are based on the data, such as share marketing, research, weather conditions, and many others. Deep learning can mine the data from the data warehouse of organization and provides suitable results for the organization. Machine learning programs learn from the business environment to improve their performance over time. Computer system is having datasets to understand the working and machine-learning techniques can make it a feature of that system. In case of loan issue, credit score is matter a lots for the system to issue loans. Deep learning provides results after searching thousands of records from data warehouse or other place. Every record is important for the system and it predict better ( Ransbotham, Kiron, Gerbert, & Reeves, 2017).
AI enabled system systems are having 83 percent strategic opportunity according to surveys and study. It has only 37 percent strategic risk. However, every business is having risk factors. AI-driven system is having risk but it provides many benefits to the organizations in long-terms ( Ransbotham, Kiron, Gerbert, & Reeves, 2017).
Deep learning is working as neural network. It learns from different records and predicts outcomes. There is many things to learn and that leaning is beneficial for predict outcomes. There are many decision-making techniques in AI, such as tree-like structure, hierarchical structure, and many more (Ruthven, 2012).
Large amount of data is requiring for deep learning, which is increasing its computing power. It is a most powerful tool for an organization to take decision based on the calculated reports and evidences (Sabherwal & Becerra-Fernandez, 2012).
AI is making a high impact on the business analysis and its requirements. It is a way to create better business system analysis using the AI-Driven system and techniques. AI enables a facility in business analysis that they can track all the processes and operations of an organisation. It will provide a decision-making facility to managers and top management to change in the system for increasing the business performance and growth. BI can implement an alternate system that can provide help to take decision for existing system and operations of the organization. Data is a base of AI and BI. Large amount of data is required to take decision for a business processes (Turban, Sharda, & Delen, 2010).
It can be dangerous sometimes if it is not calculated properly based on the data and information. AI technologies are providing speed-up to internal processes of an organization. Business intelligence is also affected from the new techniques, which are provided by the AI. AI-driven applications are helpful in products and services development, customer’s feedback management, sales enablement, and implementation of new technologies (EY, 2018). In below figure, biggest challenge to an organization shows.
Business analyst can take help of AI-driven applications into decision-making. Machine learning techniques can enable a computer system to take their decision based on the data. There are many data, which is collected from internal and external sources of an organization. Data is collected from transactional system of organization in a process. In retails business, data is collected form Point-of-sale system (POS).
It can provide suggestion to their customers for their next purchasing and visit. Organization can provide offers and discounts to each customers based on its previous purchases. Loyalty program can be managed by AI-driven applications that will suggest the name of selected customer and awards for particular customer. Each business is having their different processes, such as banking, tourism, retails, value-chain, transportation, and many others (Ghosh, 2017).
To enabling AI-driven business in organization, there are few steps to take advantage of AI, which are as:
AI promises to create new ways to run business and improve decision-making. In future, robots replace humans to run businesses. AI tools are providing better results in business analysis (Wright & Schultz, 2018).
There are many reasons to adopt the AI in business, such as competitive advantage, new businesses enter our market, incumbent competitors, reduce costs, supplier, and customers. AI-driven systems are beneficial for the origination in term of competitive advantage. Every industry is having competition and few are having strong competition. It is considers as a threat or external force according to porter’s five force model. Therefore, it is necessary to involved AI-driven application in processing of different operations.
I leant from the study that AI-driven business strategies are requires to enhancing the business of an organization. It provides many benefits to the organization, which is based on the data and information. That information can be collected from raw data of business processes. Machine learning and deep learning are highly used techniques that are providing better results in business analysis. According to (Castelluccio, 2017), AI improves performance of the internal processes of the system, which is affecting overall growth of an organization. We can take AI as an additional benefit to our business processes. It enables different capacities of business processes. AI-driven applications are best for real-time decision-making. Many times, it is necessary to take decision in less time. Therefore, AI-driven system can predict better outcomes based on the data.
Without data, AI is nothing and it cannot help in business analysis. AI-driven systems can analysis a huge system in few seconds. It can provide data as can possible. IBM’s Watson is a great example of the AI-driven development. It is an example of an intelligent machine, which take decision as a human being based on the data and proper management of processes (IBM, 2019).
I learn that AI-driven system is best way to enhancing profitability of an organization. It can take business analysis of an existing systems and it suggests about the changes in the existing system and business processes. I learnt from the whole study that AI adoption is little bit risky but it is a normal thing that business has risk. Therefore, most of the organization should adopt the AI-driven system to manage their business processes, such as business analysis, and many others. Business system analysis is a process, which required proper information to take decisions for current and new business processes. AI tools and techniques are most suitable things to analyses business risks. Information technology is providing support to manage many operations of an organization and AI is enhancing the information technology features. AI can provide better results as compared to existing system to manage the customer services and operations of an organization. AI applications are empowering an existing system using different tools and techniques (EY, 2018).
References
Adams , C. (2017). Describe Artificial Intelligence and how it might impact the Business Analysis profession? . Retrieved from modernanalyst.com: https://www.modernanalyst.com/Careers/InterviewQuestions/tabid/128/ID/3834/Describe-Artificial-Intelligence-and-how-it-might-impact-the-Business-Analysis-profession.aspx
Byrnes, S. (2018, December 4). The Importance Of Having An AI-Powered Business Strategy. Retrieved from Forbes: https://www.forbes.com/sites/forbestechcouncil/2018/12/04/the-importance-of-having-an-ai-powered-business-strategy/#71e911f64392
Garfinkel, J. (2018, October 15). Gartner Identifies the Top 10 Strategic Technology Trends for 2019. Retrieved from Gartner: https://www.gartner.com/en/newsroom/press-releases/2018-10-15-gartner-identifies-the-top-10-strategic-technology-trends-for-2019
Ransbotham, S., Kiron, D., Gerbert, P., & Reeves, M. (2017, September 6). Reshaping Business With Artificial Intelligence. Retrieved from sloanreview.mit.edu: https://sloanreview.mit.edu/projects/reshaping-business-with-artificial-intelligence/
Benjamins, V. (2006). AI’s Future: Innovating in Business and Society. IEEE Intelligent Systems, 21(3), 72-73.
Castelluccio, M. (2017). Artificial intelligence in business. Strategic Finance, 98(10), 55.
Chen, H., Chiang, R., & Storey, V. (2012). Business intelligence and analytics: from big data to big impact. London: MIS quarterly.
(2018, April 30). The Growing Impact of AI on Business. Retrieved from technologyreview.com: https://www.technologyreview.com/s/611013/the-growing-impact-of-ai-on-business/
Fethi, M. D., & Pasiouras, F. (2010). Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey. European journal of operational research(204), 189-198.
Ghosh, P. (2017, December 21). The Business Analyst in the World of Artificial Intelligence and Machine Learning. Retrieved from dataversity.net: https://www.dataversity.net/business-analyst-world-artificial-intelligence-machine-learning/
Ho?evar, B., & Jakli?, J. (2010). Assessing benefits of business intelligence systems–a case study. Management: journal of contemporary management issues, 15(1), 87-119.
IBM. (2019, March 30). Enterprise-ready AI. Retrieved from IBM: https://www.ibm.com/watson/about
Isik, , O., Jones, M. C., & Sidorova, A. (2013). Business intelligence success: The roles of BI capabilities and decision environments. Information & Management, 50(1), 13-23.
Klumpp, M. (2018). Automation and artificial intelligence in business logistics systems: human reactions and collaboration requirements. International Journal of Logistics Research and Applications, 21(3), 224-242.
Laney, D. (2012, February 1). Ten Reasons to Reach Beyond Basic Business Intelligence. Retrieved from www.gartner.com: https://www.gartner.com/doc/1911314/reasons-reach-basic-business-intelligence
Ruthven, P. K. (2012). A snapshot of Australia’s digital future to 2050. Australia : IBISWorld.
Sabherwal, R., & Becerra-Fernandez, I. (2012). Business Intelligence: Practices, Technologies and Management. John Wiley & Sons, Inc.
Tká?, M., & Verner, R. (2016). Artificial neural networks in business: Two decades of research. Applied Soft Computing, 788-804.
Turban, E., Sharda, R., & Delen, D. (2010). Decision Support and Business Intelligence Systems . Google Scholar.
Wright, S. A., & Schultz, A. E. (2018). The rising tide of artificial intelligence and business automation: Developing an ethical framework. Business Horizons, 61(6), 823-832.
Zeng, L., Li, L., & Duan, L. (2012). Business intelligence in enterprise computing environment. Information Technology and Management, 13(4), 297-310.
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