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Research Methodology

Dsicuss about the Risk Groups For The Electricity Network Objects.

The research was conducted using both the primary and the secondary data. The secondary data was got from the archives of the investigations that have ever been made concerning the trends in the contemporary business environment (Fletcher, 2016). The data collected was beneficial as it enabled us to reach our conclusions about the research. The primary data was got from the first-hand information from the business organisations themselves.

I conducted interviews on the well-performing industries in the market to find out the major trends in the business environment that have enabled them to meet their success. The information gotten was from different levels of management (Snelson, 2016). The different levels of management in the industry was needed to ensure that the results were not only from one source (Lloyd and Hopkins, 2015). I took the findings from the interviewees and analysed them so that I could make a reasonable conclusion.

I also came up with questionnaires about the business environment and how the trends in the business environment have impacted on the daily business activities and what were the new trends in business (Wang, 2014). I gave out the questionnaires to various employees of various organisations in the market so that I could weigh all their answers. I gave out encouragements to the people by giving those refreshments as they answered the questions (KOUNTUR, 2016). I did this to make the people comfortable while answering the questions so that they could not answer the questions for the sake of just finishing. When the answers are given out for just listening, they usually tend not to provide the exact analysis needed.

The data I collected was so direct that I found them more comfortable to analyse. On my report, I ranked the findings on percentages.

Use of Machines

Productivity- from ( 50 to 90)

Supply- from ( 60 to 95)

Profitability- from ( 50 to 95)

Improved management

Productivity- from (50 to 80)

Supply-        from  (60 to 75)

Profits made- from (50 to 78)

Change in business layout

Productivity- from ( 50 to 70 )

Supply-      from   ( 60 to 79)

Profits made – from ( 50 to 90)

The observations led to the outcoming of the idea of using machines in production as the dominant trend in the business environment today. The use of artificial intelligence recorded the highest percentages regarding productivity, supply and the productivity. This showed that a majority of the people were reaping fruits from the use of artificial intelligence in business (Yamato and Kumazaki, 2018). The fruits also came as a result of the automation brought about by the use of the artificial intelligence idea in conducting business activities in the market setting.

From the observations made from the research, it was evident that the idea of artificial intelligence has impacted positively on the current business world. Artificial intelligence refers to the use of machines in carrying out the day to day activities in the business environment (Gluschenko, 2015). The devices used in the day to day activities include the use of the automatic vending machines to deposit and withdraw cash. The devices are convenient as they do not need the help of a teller to operate. The idea of using these machines have impacted positively on the business world since automation has been increased. The need for the artificial intelligence knowledge in business operations is also essential to enable the businesses to meet productivity thus a sustainable development.


Machines also impact on the management of the business organisations. They provide room for supervision of the activities that take place inside the business organisation. The monitoring is essential as it tries to expose the rots that do occur in the business. The use of the CCTV cameras helps in detecting these rots with the help of a computer exposes the evil deeds. This shows why artificial intelligence is at the forefront when it comes to the current trends in the business environment. It has plenty of advantages when compared to the disadvantages that may be realised as a result of it.

Artificial intelligence has plenty of implications it has on the operation of businesses. The impacts lie in the production and the service industries. Its effects are very many since the communities surrounding the business setting also realises them. The managers and the employees of the companies also get to experience the impacts of artificial intelligence. The impacts include:

  1. Artificial intelligence helps save time and money

As a result of artificial intelligence, the companies can be able to save the time and money needed to conduct their operations. The use of machines helps in saving time due to the fastness of the machines. Human labour is usually slow since the humans tend to get tired. When a human mind is exhausted, the operations of the human being are generally brought to a standstill making him less productive. The use of machines increases on-time conservation as the machines only need power or fuel to run (Ward, 2010). This makes the machines to achieve productivity after short periods of time.

The machines also save money since when the machines are used the time spent is usually small. Thus there is no need to pay the extra cost of working hours to the human labour. This provides that the cost of having to pay the human labour can be directed to somewhere else like it can be used in the purchase of new machines. This will see the cost-effectiveness of the use of machines. This will also lead to the increased productivity, and thus sustainable development in the business set up.

  1. Machines help in avoiding Human Error Mistakes

The use of machines is significant in helping to minimise the mistakes that arise due to human error. These mistakes at times cause the companies not to meet their objectives of making surplus profits. The human errors tend to reduce the production process. The ability of the machines to make common mistakes is challenging since they are typically programmed. The human, on the other hand, makes errors due to the issue of emotional problems and even frequent fights at the workplace (Kim, Froese and Cox, 2012). The machines do not tend to get emotional as they do not have feelings. Their efficiency level is also constant as they are not affected by issues to do with stress. This makes the use of machines more reliable. The reliability of the devices implies that the tools are in a position of meeting higher productivity levels within a short period. These productivity levels are usually an advantage to the business.

  1. Artificial Intelligence in Business helps Increase Productivity


Artificial intelligence in the business sector enables the productivity of the businesses to increase. The increased productivity is as a result of the increased efficiency brought about by the use of the machines. The use of these machines serves the purpose of replacing the human labour by the machines (Lack, 2013). The use of mobile banking has been of advantage to the banking industry. It has enabled the banks to realise a lot of customers. The customers can conduct transactions with the help of a mobile phone. Thus it has provided that there is no need for one to go to the banks to make deals. This has increased the productivity of the banks.

The reduced need for the courier companies has enabled the companies to be productive. The courier companies was a disadvantage as it made the companies incur a lot of costs for their products to be transported. The use of machines has enabled the companies cut on this cost as the companies use the machines in transport. The excessive expenses incurred on the couriers have been shifted to other uses in the company which has enabled the companies to meet increased productivity.

  1. Offering Intelligent Support and Advice

The use of machines has enabled the companies to be able to access the advantages brought by the exceptional support and advice. The smart support comes from the use of the computers to advise the management. The computer can store the information about the past events that can be of benefit to the administration when making decisions. The information can be stored in the clouds thus ensuring that they do stay for a long time. The information can be the income statements and the balance sheet figures that may be needed by the company for decision making (Yan, 2016). This information will be readily available on the computers. Thus the management will be able to trace them with great ease. 

The support brought about by the use of machines include the support of performing tasks. One does not need to write minutes manually in a meeting as he can easily do that with the help of a computer. One does not need to store the minutes in files as he can store them in the computers. The computers provide a safe means of storing information as they have passwords which make illegal access to information difficult.

  1. Online Shopping

The use of websites has enabled shopping to be made much easy. The sites contain the goods that are available in the stores of the companies. People can get information relating to the products with much ease as they are readily available (Laudon and Traver, 2018). The online shopping also increases the efficiency and production of the companies as they can be able to make many sales without the need of people to come and crowd in the stores (Vezir O?UZ, 2018). They later come up with spots in the cities where the delivery services are offered to the people. This increases productivity and makes the businesses to realise profits.


Artificial intelligence is of importance to the business set up as it leads to increased productivity. The productivity increases as the time needed to produce goods will be saved as plenty of products would be produced within a short period. This will leads to the replacement of the human labour with the most competitive machines (Boddington, n.d.). The replacement will mean that the money that was set aside for the paying of the workers will be redirected to other departments of the company. It will lead to these departments also improving to meet the organisational goals of improved productivity.

The idea of artificial intelligence will also affect the community negatively as it sees the replacement of the human labour by the use of the machines. The replacement of the human labour will lead to most people becoming jobless (Husbands, Holland and Wheeler, 2008). Joblessness will lead to the people engaging in evil acts to get the money to keep them going. Thus the level of criminal activities will be reduced in the companies.

The machines can also experience breakdowns. The breakdowns will lead to a stoppage in the production process. This can lead to a reduction of the speed used in producing goods in a company. The reduced rate will also affect production (Yang et al., 2013). Thus even if the companies embrace the use of the machines in production, they should still supplement with the human labour as human labour can always be relied upon in case of breakdowns. Thus the actions of the company should be neutralised.


It is evident that the use of artificial intelligence in business has impacted positively to the companies. The use of machines is the current primary trend in the business environment. The pattern means that organisations can conduct most of their operations electronically. This trend has led to plenty of gains as compared to its disadvantages. The research has enabled me to find out the importance of artificial intelligence in the conducting of the activities of the business. The study also brings the views of the people concerning the use of machines in the industry. The people have different opinions regarding how useful the devices are in business. Thus this is complete research on the trends in the business environment.


Boddington, P. (2017). Towards a Code of Ethics for Artificial Intelligence. Springer International Publishing.

Djukicin, S., Milankovic, J. and Djordjevic, J. (2011). Contemporary business trends and industrial transformation in Slovenia on the examples of Maribor and Celje. Geographica Pannonica, 15(3), pp.81-89.

Fletcher, A. (2016). Applying critical realism in qualitative research: methodology meets method. International Journal of Social Research Methodology, 20(2), pp.181-194.

Gluschenko, P. (2015). The Definition of Risk Groups for the Electricity Network Objects in their Future Intellectualization. Modelling of Artificial Intelligence, 5(1), pp.9-17.

Husbands, P., Holland, O. and Wheeler, M. (2008). The mechanical mind in history. Cambridge, Mass.: MIT.

Kim, S., Froese, F. and Cox, A. (2012). Applicant attraction to foreign companies: the case of Japanese companies in Vietnam. Asia Pacific Journal of Human Resources, 50(4), pp.439-458.

KOUNTUR, R. (2016). Detecting Careless Responses to Self-Reported Questionnaires. Eurasian Journal of Educational Research, 16(64), pp.1-35.

Lack, J. (2013). Plan to turn your company around in 90 days. [New York?]: Apress.

Laudon, K. and Traver, C. (2018). E-commerce. Boston [etc.]: Pearson.

Lloyd, J. and Hopkins, P. (2015). Using interviews to research body size: methodological and ethical considerations. Area, 47(3), pp.305-310.

Snelson, C. (2016). Qualitative and Mixed Methods Social Media Research. International Journal of Qualitative Methods, 15(1), p.160940691562457.

Spitzeck, H. (2009). Humanism in business. Cambridge: Cambridge University Press


Wang, H. (2014). Methods and Applications of Quantitative Linguistics. Journal of Quantitative Linguistics, 21(4), pp.377-382.

Ward, D. (2010). The cost of saving money: no longer the company reputation. Network Security, 2010(7), pp.15-19.

Yamato, Y. and Kumazaki, H. (2018). Maintenance of business machines with edge and cloud collaboration. IEEJ Transactions on Electrical and Electronic Engineering.

Yan, C. (2016). Peter Licht: working hard & making good use of the internet— advice for young surgeons. ASIDE, 3, pp.451-451.

Yang, R., Kiekintveld, C., Ordóñez, F., Tambe, M. and John, R. (2013). Improving resource allocation strategies against human adversaries in security games: An extended study. Artificial Intelligence, 195, pp.440-469.

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