Application of Artificial Intelligence in Business

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Artificial Intelligence (AI) has enormous potential for providing businesses with data and solutions that can help executives make better strategic decisions. While it is anticipated that AI can assist with many aspects of business, it is essential to determine whether it can be applied within the strategic management framework. This paper aims to provide definitions of AI and explain its connection to strategic management, including customer needs, industry requirements, stakeholder expectations, and competitive advantage.

Definition of AI

The notion of AI and its explanation has undergone several transformations over the years. According to Li and Du (2017), AI can be defined as “a variety of intelligent human behaviors … which can be realized artificially by machine, system, or network” (p. 2). This includes the ability to perceive specific facts, memorize them, and make judgments based on this information. Marr (2018) states that AI is a computer system that performs tasks that typically require participation from a person. Within the context of business, this means collecting and analyzing data such as performance measures, market trends, customer preferences, and others, which affect the revenue of a company.

The nature of AI implies that there are different approaches to using it within a particular industry or market. The connection of AI and the business strategy of an organization is displayed through the ability to use its algorithm for achieving competitive advantage and maintaining it (Ransbotham, Kiron, Gerbert, & Reeves, 2017). For instance, the algorithm can be applied to ensure top-line growth for a business.

Application in Business

Core businesses closely monitor customer needs and industry requirements by using AI to analyze data such as operations at factories, customer behavior patterns, changes in the market, and others. This approach helps companies locate solutions faster and base their strategy on the information presented by AI. In addition, both executives and clients expect companies to apply digital solutions in their work. For instance, Ilcus (2018) states that digitalization affects the expectations of customers because they have the power to choose when and how to interact with a specific business. Moreover, companies can use it to examine customer experience and improve it accordingly.

Technology-oriented businesses are meeting major stakeholder’s expectations by applying AI at their facilities and incorporating it into their processes. Ransbotham et al. (2017) state that the majority of businesses anticipate a widespread application of AI; however, in the present day, most of them do not have the necessary technology or talent to use this approach. Airbus uses AI at its factories to locate solutions for mistakes, which minimizes the delays (Ransbotham et al., 2017).

Therefore, businesses should use AI to make their operations more efficient by enabling a faster decision-making process. Ransbotham et al. (2017) provide an example of a Chinese insurance company Ping An, which created an AI algorithm to evaluate its clients and make decisions regarding loans. While this approach is time-saving, its accuracy is beyond that displayed by this organization’s employees.

Thus, businesses have measured their competitive advantage within the technology context and use AI to be able to compete with others in the market. However, according to Ransbotham et al. (2017), “only one in 20 companies has extensively incorporated AI in offerings or processes” (para. 10). Therefore, although the awareness of the need to apply AI exists, the technology is not yet accessible to all businesses.

A model that applies strategic management to AI is planning for growth and expansion. Bughin and Hazan (2017) state that executives should use AI to develop new products, improve productivity, and expand operations in a particular market. The authors emphasize the importance of this application of AI, as opposed to using it as a tool for cutting costs, which is less effective. For instance, retailers can apply this approach to recommend other products to their customers, which can increase sales by up to 5% (Bughin & Hazan, 2017). Thus, within the strategic management framework, AI can help locate new approaches that enable expansion.

IDEX

The company that applies AI in its operations and is present at the IDEX exhibition is Boeing. This company relies on technological solutions within its operations because it produces systems that allow applying advanced communication systems and other electronic solutions (“Exhibitor list,” n.d.). Boeing applies AI in many aspects of its business, including design and customer support. The company states that it generates an extensive amount of data daily, which helps them analyze information and receive recommendations from AI within minutes (Harish, 2017).

Thus, AI helps Boeing at many stages of developing a product, such as design or supply chain management. Moreover, the algorithm helps this business forecast the customer demand, and using this information; they apply dynamic pricing to leverage this opportunity (Harish, 2017). Therefore, AI presents many benefits for Boeing because it helps plan operations, forecast future events connected to product development, test hypothesis regarding suppliers and design, and provide support to customers.

Conclusion

Overall, AI is a technology that will be applied by businesses to leverage their competitive advantage and meet stakeholders’ expectations. It is necessary because stakeholders expect companies to use digital approaches to improve their operations and introduce new ways to reach clients. Companies such as Boeing apply AI within different elements of their work, which helps them make better forecasts for the future and plan the development based on this information.

References

Bughin, J., & Hazan, E. (2017). . Web.

. (n.d.). Web.

Harish, R. (2017). AI-driven transformation. Web.

Illus, M. A. (2018). Impact of digitalization in the business world. Review of International Comparative Management, 19(4), 350-358. Web.

Marr, B. (2018). . Forbes. Web.

Li, D., & Du, Y. (2017). Artificial intelligence with uncertainty (2nd ed.). Boca Raton, FL: CRC Press.

Ransbotham, S., Kiron, D., Gerbert, P., & Reeves, M. (2017). . Web.

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