HC3031 - Trends in Global Business: AI Literature Review (T1 2019)

This paper provides a detailed literature review on the role of artificial intelligence in business growth, focusing on Andrew NG's article and other relevant sources. It explores how companies can benefit from AI projects, the positive factors associated with AI, the need for specialized skills in AI implementation, and the effects of creating relevant AI projects. The review highlights the importance of value creation, cost reduction, revenue enhancement, and new business lines through AI. It also discusses the challenges and potential security threats associated with AI, emphasizing the need for companies to survey the landscape of potential threats and develop strategies for mitigation. The paper concludes that while AI offers significant opportunities for business transformation, successful implementation requires careful planning, expert teams, and a focus on creating value for stakeholders.

Running head: SUPPORT OF ARTIFICIAL INTELLIGENCE
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Introduction:
The aim of this paper is to discuss the importance of artificial intelligence in the growth of
Business and how the managers can effectively utilise every factors associated with the
artificial intelligence projects effectively. This paper will be discussing the article written by
Andrew NG who has effectively served some of the biggest companies of the world relating
to Information Technology. This detailing for questions aroused from that particular article
and find answers with the support of different literatures on the same topic.
Overview of the topic:
The artificial intelligence have become one of the major driving force that has helped
business to transform itself within a very limited period of time. This type of technological
guidance have been helping the non-internet sectors like agriculture, education, energy and
Logistics. The article has found out five tryaits of artificial intelligence projects which is
essential for the management of a company am into to implement artificial intelligence in
various departmental reasons. This article by Andrew NG has also detailed how the
management of the company must implement the artificial intelligence project to get the best
results and convince all the stakeholders to describe with the changing technological
development for the production, marketing and sales of the company. Most of the cause of
this article is on the positive results of Artificial Intelligence and how these have helped the
industries to flourish and how the industries can get the best guidance by using small
investment in the AI projects.

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Theme 1:
How the companies get the best help from artificial intelligence?
The article by Andrew Ng give a detail understanding of the features of artificial
intelligence projects and how they are connected with the growth of business of any industry.
The main factors related with artificial intelligence project is the value creation process step
with very limited data and fund the artificial Intelligence can create scope for the business to
flourish in any part of the world. after globalisation as the technological development has
expand in all over the globe, it enhances the scopes for the business Industries to open up new
opportunities through enhancing the quality of their products and services does create a loyal
base of customers and popularity (Furman and Seamans 2019). This article has detailed how
to choose the first AI project to have a quick win over the other competitors with Limited
time and fund. The specificity of artificial intelligence is a vital aspect for its success. To
Ghahramani (2015), the availability and understanding of the credible partners who are
associated with this type of project is essential because AI projects in in the developing
Economics is not very popular experienced. Therefore the acceleration of the pilot project
must be limited to the credible partners. This they will create value.
Theme 2:
What are the positive factors of artificial intelligence?
The positive factors associated with artificial intelligence is mainly the value creation for
which the stakeholders like investors and employees will be convinced to get the training and
the knowledge about artificial intelligence project and implement those particularly to create
efficiency of the company. The positive factors associated with artificial intelligence is the
reduction of cost, enhancement of revenue and creation of new business lines. By utilising

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artificial intelligence the companies get the scope for replacing their human resource or
reducing pressure upon them so that deficiency of the company gets enhanced in one hand
and works are done quite easily and within Limited period of time. This create scope for
reducing employee numbers which can provide cost-effectiveness to the company. Secondly
the projects related to artificial intelligence may lead the companies to enhance revenues
because it can increase production within a specific period of time which can cater the
demand of the market. this gives opportunity for the company to gain competitive advantage
which directly connects to enhancement of revenue. Finally to Crawford (2016) the creation
of value gets exposed when a company can get another business line related to their existing
business. For example clothing company producers designer clothes but cannot sell it as they
do not have proper infrastructure to open a brick and mortar stores. In that case the company
can use artificial intelligence to do the specific tasks for clothing production and use the
online market to reach the customers directly offering them products with reduced expense.
However according to Brundage et al. (2018), the company’s need to have proper survey the
landscape of potential security threats which originates from malicious use of artificial
intelligence. Only through better forecasts and prevention they can mitigate such threats.
Theme 3:
Doe AI projects need special skills to implement?
The artificial intelligence projects are not well expertise by every company because this is a
special kind of knowledge which relates to the technological understanding of mechanism top
most of the companies nowadays are trying to automate their production system but do not
possess particular teams to execute search projects. To Ezrachi and Stucke (2017), more or
less every modern companies are processing Information Technology teams which actually
takes care of this type of projects but in that case the gap between the actual need of the

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department for which the artificial intelligence is being created and the offerings of this
projects become too wide. This is the reason why most of the artificial intelligence projects
cannot succeed. For utilising Artificial Intelligence project to meet the need of the
departments, the company needs to have a leader who can work cross functionally. In that
case, to Hill, Ford and Farreras (2015) the leader will have proper knowledge of the artificial
intelligence project in one hand and understanding of the requirement of the departments so
that the gap between the item and the other department do not affect the whole project. Along
with the leader having perfect knowledge of Artificial Intelligence and the need of the
department it is also expected that the team which will be implementing the project for doing
the task must have proper knowledge of meeting the requirement. According to Andrew Ng
the team for implementing AI will be smaller and having experts with intense knowledge of
AI. This only can increase the relevancy and effectiveness of the project to meet the need
Theme 4:
What are the effects of creating relevant AI projects?
The relevance of the artificial intelligence project is another factor which Andrew NG in his
article has pointed out. A pointed out by Kolbjørnsrud, Amico and Thomas (2016), case the
team or the leader does not understand the actual need of the department will not be able to
you suggest or create artificial intelligence project. Therefore the investment on this project
will have no use. Hear the author has pointed out that relevancy is important for efficiency.
He has given example of medical device manufacturing company which has invested in
develop AI projects in the recruitment process. First of all this project will be imitated easily
by any other company with enhanced effectiveness of same type of results. Secondly this
type of artificial intelligence project will give no positive outcome because they are not
relevant to create value for the company. In that case the author has recommended that if

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companies try to invest in developing AI project they must invest in the relevant technology
because this will only create value for the development of the company to contribute in the
industry. If this particular company will invest and develop artificial intelligence project to
measure the health check-ups of the patients for the number of check-ins in the hospitals will
be more effective and acceptable by the stakeholders. To Bryson and Winfield (2017) the
companies must be developing such projects in which they can divide the whole job to some
small tasks and make the AI to do those for reducing the physical and mental engagement of
the human employees.
Conclusion:
Therefore it can be concluded that artificial intelligence is one of the most debatable topic for
business companies. some of the authors have pointed out the positive factors associated with
the artificial intelligence projects on the contrary some others have pointed out the negative
aspects of the same for growing business through automation process. As the article has
pointed out there are five traits of perfect artificial intelligence project and what can be done
to get the best result for the business. The most important factors related to this type of
project is the creation of values for the companies in this competitive business world. The
author has also detailed the methods of implementing successful AI project buy depending
upon the expert teams so that convincing the stakeholders to use artificial intelligence in
every department of the company becomes easy.

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References:
Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., Dafoe, A., Scharre,
P., Zeitzoff, T., Filar, B. and Anderson, H., 2018. The malicious use of artificial intelligence:
Forecasting, prevention, and mitigation. arXiv preprint arXiv:1802.07228.
Bryson, J. and Winfield, A., 2017. Standardizing ethical design for artificial intelligence and
autonomous systems. Computer, 50(5), pp.116-119.
Crawford, K., 2016. Artificial intelligence’s white guy problem. The New York Times, 25.
Ezrachi, A., & Stucke, M. E. (2017). Artificial intelligence & collusion: When computers
inhibit competition. U. Ill. L. Rev., 1775.
Furman, J. and Seamans, R., 2019. AI and the Economy. Innovation Policy and the Economy,
19(1), pp.161-191.
Ghahramani, Z., 2015. Probabilistic machine learning and artificial intelligence. Nature,
521(7553), p.452.
Hill, J., Ford, W.R. and Farreras, I.G., 2015. Real conversations with artificial intelligence: A
comparison between human–human online conversations and human–chatbot
conversations. Computers in Human Behavior, 49, pp.245-250.
Kolbjørnsrud, V., Amico, R. and Thomas, R.J., 2016. How artificial intelligence will redefine
management. Harvard Business Review, 2.