Artificial Intelligence: Three Areas of Business Benefit

This paper summarizes the three areas where artificial intelligence is being used to provide benefit to the business organization. It also summarizes sources or types of data used to train the artificial intelligence.

Running head: ARTIFICIAL INTELLIGENCE
Artificial Intelligence
Name of the Student:
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Table of Contents
Introduction......................................................................................................................................2
1. Three areas where AI could be used to benefit the business.......................................................2
2. Sources or types of data used to train AI.....................................................................................4
Conclusion.......................................................................................................................................5
References........................................................................................................................................6

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Introduction
Russell and Norvig (2016) stated that artificial intelligence is district of the computer
science which highlights conception of the intelligent equipments which employ as well as
respond like the humans. The computer actions with the artificial intelligence are being
considered for including speech recognition, knowledge, and problem solving and planning. This
paper summarizes the three areas where artificial intelligence is being used to provide benefit to
the business organization. It also summarizes sources or types of data used to train the artificial
intelligence.
1. Three areas where AI could be used to benefit the business
Artificial intelligence which is defined as intelligence is being exhibited by the machines
has various applications. AI is used in various areas where it benefits the business operations of
industry. This new technology develops and offers notable development opportunities which the
business is used to capitalize their functions. Following are areas where AI is used to benefit
following businesses such as:
Educational sector: The future of artificial intelligence in the classroom looks bright.
This innovation is idea for the private AI tutor for each human being student. A solitary tutor
cannot employ with each scholar at once, therefore AI tutors would let for the scholars to acquire
additional help in areas of educational growth. AI tutors can eradicate idea of the tutor labs
which can reason stress for the students (Roll and Wylie 2016). AI helps to fill needs of gaps into
learning as well as teaching. It allows the schools and also teachers to do more than it is done
before. AI tools assist to create global classrooms obtainable to those who can converse various

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languages and might have illustration in addition to hearing impairments. The educator spends
amount of time for grading homework (Jiang et al. 2017). AI tool can make quick work and
automate the admin tasks. The machines can grade numerous option tests as it is close to being
review written replies. AI has potential to create effective student enrollment in addition to
admission processes.
Healthcare sector: AI is used in healthcare by using algorithms as well as software for
approximate the human cognition for analyzing the medical data. The algorithms can identify
patterns in the human behavior as well as create own logic. In order to reduce human error, AI
algorithms are being used to test continually (Yu, Beam and Kohane 2018). AI tools can manage
medical records and data for compiling in addition to analyzing the information. Data
management is used as an application for the artificial intelligence. The AI system is created to
analyze medical data and reports from patient’s file. It may help clinical expertise to select
corrected and customized treatment path. AI implementation enhances care delivery, but it is
disruptive to the healthcare providers. Some of the diseases need immediate actions when it
becomes severe. In case of AI, the neural network of brain is look similarly, which has potential
to study as of earlier cases (Zahraee, Assadi and Saidur 2016). The artificial neural network can
diagnose faster and accurate the diseases such as eye problems and others. There are lots of
patients which are exhausted require attention as well as knowledge of the patients. Due to lack
of activeness, the human errors are threatening safety of patients. In order to overcome with
these human errors, AI as super spell checker can assist doctors by elimination of errors.
Banking sector: AI in banking is one of the key significant applications for the artificial
intelligence throughout using conversational assistants to engage the customers 24*7. AI
assistants help in customer banking transactions help to get positive ROI (Ekinci and Erdal

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2017). The assistants are aware of customer’s patterns which engage the customer at accurate
times when they are on mobile app or banking site. AI based system can help to make informed
and profitable loan plus credit decisions. The banks are confined to use of credit cards, history of
credit, references of customer and banking transactions which determine whether or not the
individual is creditworthy. Main role of AI in banking sector is improving the customer services.
AI based mobile applications can process data to offer information and redirect users to source
the data information (Russell and Norvig 2016). The mobile app can handle communication by
means of analyzing the user’s data. Banks can provide online management services by
integration of AI advancements into the mobile application.
2. Sources or types of data used to train AI
The machine learning models are trained by means of data with particular features. The
data is structured in such a way that it helps models to learn as well as develop relationship
among the features. A processed training set is needed to build robust model that can generate
accurate results. In order to build a model, one can keep in mind flow of the operations which
involve building quality datasets (Steels and Brooks 2018). Training data is used to train AI. For
example, in order to determine height of a person features such as age, weight, height and size of
clothes are being considered. The clothes of person will account the height while color and
materials will not add any value to the features. Once the training data is being prepared, then it
is time to train neural network (Ghahramani 2015). The organizations such as IBM, Google,
Microsoft and others have prepared services for the speech data, therefore those services are pre-
trained to specific extent. After completion of this, it is ready to test quality of AI. The

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professionals can measure correctness of the trained AI. This process can need lot of human
interventions, and efforts.
Data preparation is required for training and real time decision making for AI. It is most
key significant task for AI projects. The key for AI success is quality as well as quantity of the
data. AI can make decisions as it can trace back to data which is used to train it (Lu et al. 2018).
The ethical plus optimization efforts are required to understand as well as recognize the data. In
order to set the organization for the future, it will have to create data as it is key element of the
strategy. It is hard for the business organization as it follows in implementation of vision of AI
(Copeland 2015). The business should invest into data competence as well as breakdown of silos
of IT and then the business achieves efforts. Data is part of the business organizations which
have work together and there is lot of competence will require in order executing. The artificial
intelligence becomes popular to increase data volumes, advanced algorithms as well as improves
into the computing power plus storage.
Conclusion
It is concluded that AI is a method for data analysis which can automate analytical model
buildings. It is based on idea that the system can learn from the data, recognize the patterns plus
make decisions with the minimal intervention of the humans. In this paper, three key areas are
summarized where AI benefits the business such as education, healthcare and banking sector. AI
is designing the machines which have ability to believe. AI plays a key important role into the
healthcare sector which can automate the healthcare processes and decrease the human errors. It
is able to communicate with the computers which can understand the human languages. The

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system can understand, interpret as well as gather data on the computer. The training data is
stored so that the users can understand the main features which are used in AI tools.
References
Copeland, J., 2015. Artificial intelligence: A philosophical introduction. John Wiley & Sons.
Ekinci, A. and Erdal, H.İ., 2017. Forecasting bank failure: Base learners, ensembles and hybrid
ensembles. Computational Economics, 49(4), pp.677-686.
Ghahramani, Z., 2015. Probabilistic machine learning and artificial
intelligence. Nature, 521(7553), p.452.
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q., Shen, H. and Wang,
Y., 2017. Artificial intelligence in healthcare: past, present and future. Stroke and vascular
neurology, 2(4), pp.230-243.
Lu, H., Li, Y., Chen, M., Kim, H. and Serikawa, S., 2018. Brain intelligence: go beyond artificial
intelligence. Mobile Networks and Applications, 23(2), pp.368-375.
Roll, I. and Wylie, R., 2016. Evolution and revolution in artificial intelligence in
education. International Journal of Artificial Intelligence in Education, 26(2), pp.582-599.
Russell, S.J. and Norvig, P., 2016. Artificial intelligence: a modern approach. Malaysia; Pearson
Education Limited.
Steels, L. and Brooks, R., 2018. The artificial life route to artificial intelligence: Building
embodied, situated agents. Routledge.

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Yu, K.H., Beam, A.L. and Kohane, I.S., 2018. Artificial intelligence in healthcare. Nature
Biomedical Engineering, 2(10), p.719.
Zahraee, S.M., Assadi, M.K. and Saidur, R., 2016. Application of artificial intelligence methods
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630.