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Artificial Intelligence (AI) Systems and Their Use in Businesses
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Table of Contents
I. Introduction 3
II. Differences and similarities among the four techniques 3
III. The difficulties with new Information Technology (IT) approaches in general 4
IV. Advantages and disadvantages of AI systems over traditional business processes 5
Say you were selling specialty teas and had brick and click stores. Would you use the same type of AI systems for each part of your business? In what way would you use them or why would you not? Is there a place for decision support and artificial intelligence techniques in small specialty businesses? 6
V. In what way would decision support add value? 6
VI. How a Decision Support System (DSS) or an AI system would be value reducing (in terms of Porter’s value chain theory)? 7
VII. Provide recommendations that are feasible in all respects (e.g. economically, technically, legally, etc.). 7
VIII. Conclusion 8
IX. references 10
Introduction
Information and technology developments led to the birth of Artificial intelligence which is a science where machines emulate human behavior and thinking. AI is used in many fields to perform different operation in those fields making the operations that would be complex and timely be much easier. In business, artificial intelligence is used in problem diagnostics, problem solving, reduction of human calculation efforts, and automate operational and business processes. In healthcare, AI is used to assign bets t patients, schedule staff, treatment, and diagnosis (Haag & Cummings, 2015). Besides financial analysts use AI systems to invest in stocks, manage assets and carry out financial operations. For government agencies, AI is used diversely in armed forces an IRS to. The use of AI ranges from complex to simple activities in diverse fields (Haag & Cummings, 2015). The systems can be imbedded into other analytic system to perform more specific operations or in some cases, the can be stand alone in decision making or independent. As a consequence, this paper looks into the four major categories of AI systems namely: expert systems, neural networks, agent based technologies, and genetic algorithms; their similarity and differences, merits and demerits, their operationability, applicability in my business, and their value addition in the business.
Differences and similarities among the four techniques
Expert systems are used to diagnose problems and makes solutions based on logic. The system can improve customer services by reducing errors despite the fact that it cannot automate all processes (Haag & Cummings, 2015). On the other hand, neural networks differentiate and find patterns, analyze relationships, and can adapt when it is subjected to volume information and new changes. Elsewhere, the genetic algorithms emulate survival-for-the-fittest and evolutionary processes to generate more feasible solutions (Haag & Cummings, 2015). Nevertheless, intelligent agents are software that act on behalf of humans or assist human to carry out computer related respective tasks. Despite having different roles and abilities, the four AI technologies have similarities and differences.
The systems have roles that can lead to one another. While expert systems help in coming up with a conclusion, neural networks identify different patterns in a system. On the other hand, the genetic algorithm generates alternative that help in reaching optimal solutions. Intelligent agents then can use the solutions to perform computer related repetitive tasks (Haag & Cummings, 2015). It is therefore evident that though different, the techniques can be used alongside one another to enhance system operations and outcomes.
Neural systems and expert systems and use in problem identification and diagnosis. Also, all techniques are used to find feasible solution out of a ray of alternative that are given to them through analyzing the information fed into them.
The difficulties with new Information Technology (IT) approaches in general
New IT approaches come with a number of difficulties when introduced to an organization or a company for the first time. At the first time, the system would experience compatibility problems. As a result, it can take long time for a system to be understood, accepted, and become fully accepted in the organization. Moreover, collection and organization of information can be a big problem with the new IT approaches: for instance, when a company shifts to a data warehouse from a database (Iafrate, 2018). Moreover, new IT approaches require new hardware.
Despite the great benefits that come with artificial intelligence systems, super intelligent AI cannot exhibit human emotions like hate and love and no one can expect them to be malevolent or benevolent. When considering the difficulties of AI, it is based on being programmed to do devastating things and also when AI system are designed to carry out beneficial things but end up developing a destructive route to solve the problem. With regards to performance of devastating things, autonomous weapons are AI systems that are programmed to destroy or kill humanity. As a result, the future can be faced with AI war which can lead to mass casualties. To overcome enemies, the AI systems will be programmed in a manner that it will be difficult to turn them off leading to loss of control by humans.
When AI is programmed to solve problem and ends up developing destructive method to solve the problem is a possible AI difficulty. The difficulty arises when one fails to align personal goals and AI goals. This can be the case when a person can order an intelligent car to take him or her to a shopping mall as fast as possible (Iafrate, 2018). The car end up over speeding leading to braking traffic rules which in turn can cause arrest. Literary, the car did what the owner did not want but what the owner ordered it to do. AI systems are competent but not malevolent. Therefore, when programming AI systems. People should consider the humanity aspect.
Advantages and disadvantages of AI systems over traditional business processes
Just like any other system, AI systems have advantages and disadvantages associated with it. The fist advantage of AI systems is that they deal with mundane tasks through automation and results in increased productivity. Therefore a company can free humans from “boring tasks” and assign them to a machine. Also, AI systems are beneficial because they make faster decisions compared to traditional business processes. When AI systems are used alongside cognitive technologies, quick actions and faster decision rates are achieved. Moreover, traditional businesses processes are more associated with “human error” but AI systems eliminate and avoid errors (Iafrate, 2018). For AI systems, they only require proper programming for them to process data without errors no matter the size of data. Moreover, AI systems are better than traditional business processes because they take risks on behalf of human beings. For instance in companies that deal with harmful chemicals, AI systems can be used in these places instead of human beings thus minimizing exposure of human beings to health risks. Lastly, AI systems create new job opportunities for programmers and database managers.
On the other hand, AI systems come with negative impacts. Despite the fact that AI systems create new job opportunities, they lead to massive job losses given that one system can handle a job that many employees could do at a given period (Iafrate, 2018). Also, with AI systems, comes distribution of power whereby countries with AI tend to tend to destroy humanity.
Say you were selling specialty teas and had brick and click stores. Would you use the same type of AI systems for each part of your business? In what way would you use them or why would you not? Is there a place for decision support and artificial intelligence techniques in small specialty businesses?
If I were selling specialty tea and had brick and click stores, I would use expert system on the two stores to analyze customer information and use it in specialty tea to enable customers have the tea that suit their taste (Grey House Publishing, 2018). The expert system is will enable customers to have their taste on a daily basis without variations because human activity and errors can lead to variations in tastes due to inconsistent measurement of recipes. Also, I would use neural network to analyze web traffic from the business website.
In what way would decision support add value?
The computerized decision tools is important for the businesses because it will help in collecting information based on customer preferences and tastes and end up producing specialty tea that is in line with the customer needs. Despite the fact that the decision support systems would be expensive for the small business, it would improve the efficiency of the business an in turn attract more customers (Iafrate, 2018). Though at first the decision would seem not feasible, the long term goals of the business to grow and attract more customers would be achieved. Customers prefer a business that meets their needs and demands at any given time, at the right quantity and quality, in other words, customers prefer getting value for their money. And with the system in place, customers will get high quality services thus making them return customers and even refer other customers. The artificial techniques and decision support will provide information for the system and make it easy for the business to obtain data to support business operations though on a small scale compared to big companies.
How a Decision Support System (DSS) or an AI system would be value reducing (in terms of Porter’s value chain theory)?
Based on Porter’s value chain theory, AI systems and DSS would be value reducing when reflecting on the generic business as a whole. Therefore, it is not clear whether companies that use DSS and AT systems would stand completion from their rivals who use the same systems (Grey House Publishing, 2018). Companies use DSS systems to collect, analyze, and interpret the collected data and then use the data to make informed decisions and develop desirable strategies to move the business forward.
Provide recommendations that are feasible in all respects (e.g. economically, technically, legally, etc.).
In this case, the specialty business is small businesses that require small information compared to bigger businesses. The difference in managing a small business and a big business is how well a business can connect with its customers. Also, how well a company utilizes its Artificial intelligence systems in the businesses determines its success. AI system is an expensive venture and small businesses with limited data, limited data science, and limited resources need to invest in it when they are sure of return on investment (Grey House Publishing, 2018). Therefore, small businesses need to effectively use the artificial intelligence systems to save advertisement cost, grow revenue, attract customers, and retain their current customers.
Therefore, the specialty business should use AI systems to grow its customer base on social media platforms. To achieve this, AI can be used to develop better advertisements on Facebook by identifying the right audience for a given ad (Grey House Publishing, 2018). Moreover, small businesses can use AI system to enhance development and team engagement besides helping the business in looking after its customers. The team and customers is the key for any business success and when they are happy, the productivity of a business increases. AI system can therefore provide businesses with platforms where employees and Human resource management communicate and issues raised and recommendations made to reach strategies that will enable a business meet its set goals and objectives (Grey House Publishing, 2018). On the other hand, AI systems can provide a platform where customers interact with the business and the concerned concerns are incorporated in the business to improved service delivery. Moreover, AI system can help businesses improve the design of their website. Building a company website with expert human designers and a cutting edge AI technology can lead to a superfast turn around without recurring huge costs.
Conclusion
Artificial intelligence system is vital in the modern era business given the rapid change in information technology and dynamic in consumer choice and preferences. New information system approaches have come with benefits as well as loss in business and the world at large. AI systems deal with mundane tasks, avoid human errors, take risk for humans, and in turn increase productivity and service delivery (Grey House Publishing, 2018). On the other hand, AI systems lead to loss pf jobs, distribution of power, and lacks judgement. Though an expensive venture, small business can use it achieve turn around in business through integration.
references
Haag, S., & Cummings, M. (2015). Management information systems for the information age. New York, NY: McGraw-Hill Irwin.
Iafrate, F. (2018). Artificial intelligence and big data: The birth of a new intelligence.
Grey House Publishing, Inc.,. (2018). Artificial intelligence.
International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems, In Dash, S. S., In Naidu, P. C. B., In Bayindir, R., & In Das, S. (2018). Artificial intelligence and evolutionary computations in engineering systems: Proceedings of ICAIECES 2017.