Artificial Intelligence in business.

The Assignment 2 is a continuation of Assignment 1 which is attach also

6/3/2019
Artificial Intelligence in business
Student’s name
Institution Affilliation

Table of Contents
1. Abstract............................................................................................................................................2
2. Introduction......................................................................................................................................3
3. Related work.....................................................................................................................................3
4. Proposed Research: The impact of using AI Chat bots in business.................................................8
4.1 Problem statement......................................................................................................................8
4.2 Aim of the research.....................................................................................................................8
4.3 Expected outcomes and significance..........................................................................................8
4.4 Method and innovation...............................................................................................................8
4.4 1 Margins for AI Chat bots...................................................................................................10
4.4.2 Future for chat bots............................................................................................................10
5. Conclusion......................................................................................................................................11
6. References......................................................................................................................................12
7 Appendix.......................................................................................................................................13
Appendix A. Literature Review – Broad Scan and Reading (minimum 3 rounds)......................13
Round 1 – Literature Review......................................................................................................13
Round 2 – Literature Review......................................................................................................16
Round 3 – Literature Review......................................................................................................18
1

1. Abstract
Presently, artificial intelligence has found application in various sectors in society to
enhance efficiency in day-to-day activities. In computer science, technological advances have
established an effective means of performing quick statistical analysis, which can be used in the
discovery of patterns in areas of study. Such has been employed in metrological facilities to predict
weather patterns accurately within a limited period. Similarly, tactical patterns can be formulated
using the advancements in AI research during times of war. AI has allowed the use of unmanned
warfare tactics as evidenced by the use of remote-controlled drones for surveillance and
pacification of an area of interest. Military drones are hardly detected by radar, and thus, they can
fly stealthily over enemy territory to deliver air strikes or gather information. In addition,
mechanical robots have been developed with the capacity to deliver ground assaults or disarm
explosives via remote control. These aim at minimizing the number of casualties during tactical
situations. The current research has not dealt with AI chat bots and AI assistants in depth as these
are emerging applications of AI thereby creating a gap that is worth researching about. This
research proposes the use of chatbot in various business sectors and will use the methodology of
systematic analysis of the current literature review from various digital libraries. The review will
be done in three rounds to filter all the relevant information to this research.
2

2. Introduction
Artificial intelligence requires skills of understanding how knowledge can be represented
and the methods of how to use that knowledge. The main aim of AI is to improve human life and
reduce risks faced by humans. According to the late pioneer of Artificial Intelligence, Allan Newell,
man-made world would be permeated by systems to cushion it from danger. With the advent of new
age computers, the dream of smart computers has become a reality.
There are many resins and advantages of why people should study AI. One of the main ones
is because scientists want to extend the range of things and tasks that can be performed by
computers. The ‘ability’ of computers keeps growing with changing times. The limitations are
virtually boundless. The other main reason is the interest in technological applications in the AI
field. These spread out to all disciplines that use any form of computers or electronics to achieve
tasks. Examples of these fields include; Medicine, manufacturing, farming, education, housework,
research and development, and science in general. In business, computers are also very helpful and
essential. Due to the intelligent and adaptive nature of AI, systems can help locate pertinent
information (He et al., 2019).
3. Related work
AI systems have found application in healthcare facilities in the diagnosis and treatment of
various health conditions. Diagnostic systems are based on AI technology to provide automated
diagnosis methods as illustrated by the availability of various equipment such as the MRI, CT, PET,
and x-ray machines. In addition, medical laboratory equipment heavily relies on automation for
analysis of biological samples to render diagnosis results. These systems provide efficiency in the
healthcare services by offering quality and accurate diagnosis of the different disease condition,
which adds value to healthcare. Life support equipment such as ventilators, dialysis machine, heart-
lung machines is illustrative of the success in the application of AI in the health care sector (Allam
& Dhunny, 2019).
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Most manufacturing industries rely on automation for their operations, and as such, AI
technology is employed to handle heavy assembling procedures. This technology is credited for
effectively handling highly repetitive procedures, which often lead to mishaps or errors if humans
are involved as a result of a lapse in concentration.AI technology not only helps in scheduling
manufacturing operations but also in performing quality control. Application of AI technology has
improved productivity in most industries with large-scale assembly lines.
The presence of artificial intelligence systems within the transport and communication
industries facilitate smooth operations by handling an enormous number of computations per
second. Most telecommunication companies utilize heuristic search systems to manage their
workload and create efficient schedules for their workers. In addition, customer service providers
have adopted AI technology to respond to numerous calls made to them by customers seeking
clarification or new information. The transport industry embraces AI technology to ensure
reliability, safety, and a pollution-free environment (Corinne, 2018). This especially so since AI
technology addresses most challenges that face the transport industry. As such, AI technology is
used in control towers to plot and schedule take offs as well as landings. Automobile traffic has
effectively been controlled by AI systems through traffic lights. The technology also allows the
mapping of traffic snarl-ups and advice on alternative routes to ease the flow. In addition, most
modern electric trains are automated to ease transportation of passengers and improve the efficiency
of the services rendered.
The economic growth of any country requires detailed analysis during the assessment of
development potential and evaluation of the social status of its citizens. Such assessment is critical
in the determination of the gross domestic product to aid in the estimation of the economic growth
rates. It is also essential in the formulation of policies that are geared towards the improvement of
the economic status of the country (Davenport, 2018). These evaluations are possible through
artificial intelligence systems that effectively compute all variables to provide an accurate
assessment. Similarly, banks make use of AI systems to process finances, invest, and manage stocks
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on behalf of their clients. Investors in stocks also utilize AI technology to analyze markets and
predict future trends.
Artificial Intelligence computers are commonly known as intelligent systems. This is
attributed to their ability to learn from examples and use the statistics or data fed to them to solve
problems. Most learning programs are either experience or data oriented. The systems use a
knowledge base created with many different aspects to simulate experiences. These experience
oriented systems use common sense knowledge to discover how people usually reason about new
experiences. This stimulates a reaction. Data-oriented systems create programs to search
specifically and mine for data in databases to get exploitable regularities. These intelligent systems
can give answers to questions using free text and structured data. AI is becoming essential to us and
yet less conspicuous. The rapid development of this field has helped business people achieve
strategic business goals (Miller, 2019).
Expert systems are computer systems that imitate the decision- making the ability of a
human expert. They are the most common form of AI because they can be used when humans may
be too expensive or hard to find. Some examples of expert systems would be a computer chess
player or medical diagnosis system which help doctors. Neural networks, which are also referred to
as artificial neural networks, are used to mimic how the human brain works. They are used to
estimate patterns when there is a large amount of data the rules are unknown. An example of neural
networks is that credit card companies use them to check for fraud. Fuzzy logic, which is a form of
logic which deals with reasoning, is also used with neural networks, so it is easy to simplify a
complicated concept.
Genetic algorithms mimic the process of natural selection. They are best used in decision-
making environments when there are many solutions possible and can find those solutions
extremely faster than a human would. An example of generic algorithms would be to help
investment companies use them to help them in deciding which trading decisions to make.
Intelligent agents are used to performing particular jobs on behalf of their users. The most simple
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form of this is a shopping bot, which searches the internet for a product and compares prices and
also if it is in stock. When there are a group of intelligent agents, this is called a multi-agent system,
which each system works by themselves but can also easily work with each other together if needed
(Mazurowski, 2019).
Virtual reality is when a computer can simulate physical presence in places that are in the
real world or imaginary worlds. They can recreate the senses of taste, sight, smell, sound, and touch.
A great example of this would be virtual surgery where the surgeon and patient can be anywhere in
the world and still perform surgery. Another big examples are virtual workplaces where some
employees work in the office and other work from home.
Chat-bots are intelligent software that is coded to enable verbal and textual conversations in
a manner that is intelligent and logical. In most cases, it is hard for humans to believe that they are
not holding a discussion with a machine. Utilization of this property of transparency of Chat-bots
can allow for the adopting of artificial personalities and characters within a specific field. This study
is primarily focused on evaluating Chat bots that have implemented artificial intelligence platforms.
Time is one of the main assets which is genuinely dispersed among all people regardless of their
religion, educational qualifications, gender, and geographical location, and so on. Be that as it may,
a few people achieve zeniths of accomplishment whereas others regularly remain excessively
involved in their daily exercises with no time left to something out of their schedules
The AI field has been incorporated in many industries, and this has brought about their
growth. This incorporation is by the development of intelligent agents that are set put into
completing the different tasks and requirements needed by the field. This, however, does not come
without challenges. Some of the challenges faced include; the need for information exchange with
databases in the mainframe. The need to provide rapid hardware recoveries should failures occurs a
major function of AI that presents many challenges (Becker, 2019). The need for effective
information distribution to all personnel involved in system development is another crucial function
that is challenging. These are some of the problems that should be addressed to achieve the
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successful implementation of an AI system. Some examples of successful implementation are
discussed in the following paragraph.
Siri is an application developed by the Apple Company to help users interact better with
their mobile phones. It is considered an intelligent agent that acts as a personal assistant and has
access to knowledge navigation. The main platform used for user interaction with the device is the
use of natural language. The user issues a command to the phone via the voice interface, and the
application sends the requests, delegating to different web applications, to perform these tasks. One
of the main characteristics of intelligent systems is being adaptive, and this is shown here. The
application adapts to the user's schedule, and preferences over time and automatically generates
results. These include places to eat, alarms, favorite music, directions, and other individual
preferences (Abduljabbar, Dia, Liyanage, & Bagloee, 2019).
The development of Siri involved a lot of data collection to create the appropriate responses
that it gives to queries by the user. This involves programming that recognizes a particular set of
words that simulate a response. This database is run online, and the environment is constantly
updated to keep the responses relevant. As the application continues to operate, Apple keeps
collecting information from it to improve its performance. The more users interact with Siri, the
more the information Apple will collect, leading to better responses from Siri.
Another example of an intelligent system is the stock market system. In the stock market,
shares change value virtually every second. Computer systems were developed to monitor these
changes and help traders make correct choices about their stocks. These intelligent systems are data
oriented in that they collect all the relevant data about the stocks and generate responses
appropriately and accurately. These systems are common in Wall Street, where a lot of the stock
exchange takes place (Chen et al., 2019).
In the military, a lot of data collection and intelligence is also necessary. Most of the data
gathering and surveillance is done by drones. These are intelligent drones programmed to only
monitor. They are usually sent to places where human surveillance is not very east. This is an
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example of the application of intelligent systems. The military leads in research and development of
new systems to improve human lives and reduce the risk posed to soldiers during wars.
4. Proposed Research: The impact of using AI Chatbots in
business
4.1 Problem statement
Some questions asked by users may be answered incorrectly or not answered at all, too
many questions and how long a question is testing the chatbot to its core, also too many unanswered
questions may lead to a phone call to further understand the requirements of a customer which is
less preferable (Kalis, Collier, & Fu, 2018).
4.2 Aim of the research
The main aim of the research is to study and further elaborate both usage and flexibility of a
chatbot in action, the chatbot is able to keep a conversation up and be able to respond to whatever
the user says or may imply base on his choice of words and what the user expects as an answer in
return.
4.3 Expected outcomes and significance
Chatbot has been around us for some time and implemented, and in some point of our lives
we’ve used them first hand, and they need an enhancement when it comes to cost efficiency,
response time and answer accuracy.
4.4 Method and innovation
The Chatbot is an AI-based chat option, by which businesses can now make their own chat
representative for the Messenger to tackle the most reasonable queries by the customers. Chatbot
development creates chatbots, which is nothing but austere software that interprets anything you
type or say and accordingly respond by answering or executing the command. A most popular
example of a bot in Chatbot development currently is Apple’s Siri. But Facebook has taken a leap
from these personal bots by amalgamating two most popular technologies – instant messaging and
artificial intelligence.
Technology is taking over the world, and chatbots are riding the wave. With social media
power in digital marketing space, there has been an increased technological advancement on the
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power of chatbots. The rapid rise in chatbots, artificial intelligence, and machine learning is
overwhelming among tech consumers. They find it convenient to communicate with their preferred
brands and companies through chat bot interactive messenger mimicking the real people’s
conversations (Allam & Dhunny, 2019). What follows, is, do these chatbots really assist individuals
in remaining productive in their workplaces?
Consider a scenario where you will require some help to complete a particularly complex
task. Take, for instance, traveling that will require you to book flights, make hotel reservations, and
call a cab. At the same time, you need to interact with some people to plan for this trip. A single bot
can do this, or several chatbots can do it comfortably at your office. E-commerce support platforms
have been integrated into existing social media platforms by availing products to customers upon
search or giving recommendations on tailored products on their messaging account profiles.
Facebook messenger has traversed the conversational thread to include peer-to-peer payments by
creating a full chatbot API. End to end customer interaction is just one click away. One can make
online orders and transact via the app.
Employees in companies are assisted by chatbot software to conduct their everyday tasks.
Siri or Echo software has been known to give accurate time, weather updates or order swift Uber
rides. The Hello Jarvis bot, for example, is a messenger that reminds workers to get some sort of
work done. The bot will remind an employee the exact time a certain task needs to be done. This is
done through text notification rather than voice instructions. Workers find it more convenient and
efficient in their daily operations (Davenport, 2018).
Human employees are provided with diverse reforms on certain procedures that are time
costly and energy consuming in their executions. Companies are utilizing chatbots, such as kukie to
help new employees in their full training periods. Kukie bot offers free recommendations to a
beginner on which tools to use or procedures to follow. This is done through a click, “ask
@KukieBot,” while the messenger is being updated with the necessary information.
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Several companies hire robots that work exactly like human beings. These chatbots do not
require salaries or any benefits. Also, due to the complexity of machines, they are commanded to
think like human beings rendering some human capital roles out of service. Through this,
businesses save money, time, and other resources as well as increased productivity.
4.4 1 Margins for AI Chatbots
As for any technological invention, chatbots have come up with associated problems too.
Chats bots have been known to fail to understand specific requests, as user requests do not come
with a different form of the question. Turing tests exposed a limitation in this artificial intelligence.
It highlighted the challenges developers will face when building chatbots and instructing computers
on how to interpret the written words. Chatbots, therefore, have to be comprehensive in order to
understand informal language, local jargon, an official language (Becker, 2019).
While implementing a chatbot, one needs to consider a scenario where employees need to
stop and rectify a mistake committed by a chatbot. To fix this mistake, it will cost time and money
for you and your worker.
4.4.2 Future for chatbots
The fast advancements in technology are a bonus for the chatbots since they will soon
analyze different languages better. They will have more features and exhibit increased performance.
Growth in the application of chatbots and overwhelming increase in usage is promising. Businesses
will benefit from the use of chatbots and the employees to can utilize the power of bots to handle
tasks swiftly. However, appropriate monitoring and enhanced learning software ought to be initiated
continuously. Clearly, chatbots have an impact on productivity levels of workers; it just depends on
the business model in question (Abduljabbar et al., 2019).
Artificial intelligence promises a bright future is owing to the enormous research within the
discipline and the advances made. Presently, AI has become an integral part of everyday life as
witnessed by heavy reliance on machines to perform most tasks. Research into intelligence is bound
to lead to the development of heavily intelligent robots with the capacity to perform independent
actions. The robots would have the capacity to think reason and make independent decisions. In
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addition, technological advances may lead to the merging of biological beings with machines to
create cyborgs. This can be applied in healthcare to provide solutions to ailing persons where
mechanical devices are used to replace the defective body organs such as the heart, kidneys, liver
among others (Kalis et al., 2018).
5. Conclusion
Artificial intelligence is rapidly improving in development and growth. It has been
embedded into most systems, to improve performance. My analysis and opinion of AI are that the
integration of intelligent systems has led to tremendous growth in different industries. With time,
most computer systems will be converted to intelligent systems. This is the goal that scientists are
working towards. With the analysis of the example discussed in this essay, it is evident that
Artificial Intelligent systems improve lives and will continue to do so. The criteria followed to
achieve successful application include, clear problem definition, implementation of a procedure to
achieve a task, the feasibility of the solution to be applied, and opportunities brought with it. With
this guidance, AI application can be made successfully.
Artificial intelligence is when a computer can imitate the knowledge or skills of a human.
The five most common kind of AI can do various things, such as mimic natural selection or even
simulate the real world. They can all help with making decisions when it comes to a business, for
example, the intelligent agents can be used by a company to help its users see whether they truly
have low prices on items the customer wants or neural networks can help determine what products a
customer may like based on the previous history. Artificial intelligent programs and Chats bots have
been used to obtain data-delivered results in call centers. They, therefore, help customer service
agents solve frustrations from their customers. Therefore, instead of relying on front office desks to
handle your request, you can rely on a chatbot to solve some situations such as bookings and orders.
The chatbot will do it with a simple text to command on the request.
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6. References
Abduljabbar, R., Dia, H., Liyanage, S., & Bagloee, S. A. (2019). Applications of Artificial
Intelligence in Transport: An Overview. Sustainability, 11(1), 189.
https://doi.org/10.3390/su11010189
Allam, Z., & Dhunny, Z. A. (2019). On big data, artificial intelligence and smart cities. Cities, 89,
80–91. https://doi.org/10.1016/j.cities.2019.01.032
Becker, A. (2019). Artificial intelligence in medicine: What is it doing for us today? Health Policy
and Technology. https://doi.org/10.1016/j.hlpt.2019.03.004
Chen, L., Wang, P., Dong, H., Shi, F., Han, J., Guo, Y., … Wu, C. (2019). An artificial intelligence
based data-driven approach for design ideation. Journal of Visual Communication and Image
Representation, 61, 10–22. https://doi.org/10.1016/j.jvcir.2019.02.009
Corinne, C. (2018). Governing artificial intelligence: ethical, legal and technical opportunities and
challenges. Philosophical Transactions of the Royal Society A: Mathematical, Physical and
Engineering Sciences, 376(2133), 20180080. https://doi.org/10.1098/rsta.2018.0080
Davenport, T. H. (2018). From analytics to artificial intelligence. Journal of Business Analytics,
1(2), 73–80. https://doi.org/10.1080/2573234X.2018.1543535
He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019). The practical implementation of
artificial intelligence technologies in medicine. Nature Medicine, 25(1), 30–36.
https://doi.org/10.1038/s41591-018-0307-0
Kalis, B., Collier, M., & Fu, R. (2018, May 10). 10 Promising AI Applications in Health Care.
Harvard Business Review. Retrieved from https://hbr.org/2018/05/10-promising-ai-applications-in-
health-care
Mazurowski, M. A. (2019). Artificial Intelligence May Cause a Significant Disruption to the
Radiology Workforce. Journal of the American College of Radiology, 0(0).
https://doi.org/10.1016/j.jacr.2019.01.026
Miller, T. (2019). Explanation in artificial intelligence: Insights from the social sciences. Artificial
Intelligence, 267, 1–38. https://doi.org/10.1016/j.artint.2018.07.007
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7 Appendix
Appendix A. Literature Review – Broad Scan and Reading (minimum 3
rounds)
Round 1 – Literature Review
AI was founded as an Academic discipline in 1956 since them a lot has change is used and talked
about more and more also known as machine intelligence this can be very helpful in some types of
business, in today’s date computers are more powerful by the day which this also helps AI to improve its
capability in this review we will notice that we have journal and book from very early days such as 1970 till
today.
The search keyword was Artificial Intelligence, and the database I use was Victoria University Digital
Library, and we had over 318000 search results, and below are the 20 more common and use for AI.
Title Authors Year Journal
Advances in artificial intelligence New York, NY : Hindawi Publ. 2008 Book
Modeling the Evolution of Legal
Discretion: An Artificial Intelligence
Approach
Kannai, Ruthi
Schild, Uri J
Zeleznikow, John
2007 Ebook
Artificial Intelligence as a Growth
Engine for Health Care Startups:
EMERGING BUSINESS MODELS.
Garbuio, Massimo
Lin, Nidthida
Book
Artificial intelligence [electronic
resource].
[Amsterdam] : Elsevier Science
BV.
1970 Book
Sales profession and professionals
in the age of digitization and
artificial intelligence technologies:
concepts, priorities, and
questions.
Singh, Jagdip1
Flaherty, Karen2
Sohi, Ravipreet
S.3 [e-mail]
Deeter-Schmelz, Dawn4
Habel, Johannes5
Le Meunier-FitzHugh,
Kenneth6
Malshe, Avinash7
Mullins, Ryan8
Onyemah, Vincent9
2019 Journal
Artificial intelligence : 29th
Benelux Conference, BNAIC 2017,
Groningen, the Netherlands
Verheij, Bart, editor
Wiering, Marco, editor
2018 Conference
13

Artificial Intelligence : Evolution,
Ethics and Public Policy.
Sarangi, Saswat 2018 Book
Artificial Intelligence : Its
Philosophy and Neural Context. George, F. H.
2018 Ebook
Artificial Intelligence : The Case
Against.
Born, Rainer 2018 Book
Artificial Intelligence : With an
Introduction to Machine Learning,
Second Edition
Citation
Title:
Artificial Intelligence : With an
Introduction to Machine Learning,
Second Edition.
Neapolitan, Richard E. 2018 Book
Artificial intelligence : concepts,
methodologies, tools, and
applications
Hershey, Pennsylvania (701 E.
Chocolate Avenue, Hershey,
PA 17033, USA) : IGI Global,
[2017]
2017 Ebook
Artificial Intelligence : Clever
Computers and Smart Machines.
Greek, Joe 2017 Journal
Artificial Intelligence : What
Everyone Needs to Know. Kaplan, Jerry
2016 Book
Artificial intelligence [electronic
resource].
[Place of publication not
identified] : C S R E A Pr, 2015.
2015 Ebook
Artificial intelligence [electronic
resource] : approaches, tools, and
applications
New York : Nova Science
Publishers, c2011.
2011 Journal
Artificial intelligence : theories, Berlin ; New York : Springer, 2010 Conference
14

models and applications : 6th
Hellenic Conference on AI
©2010.
Artificial intelligence : structures
and strategies for complex
problem solving
Luger, George F.
2005 Book
Artificial intelligence : a guide to
intelligent systems
Negnevitsky, Michael 2005 Book
Artificial intelligence : a modern
approach
Russell, Stuart J. (Stuart
Jonathan)
2003 Book
With all these results it can be clearly seen how AI has multiple points of views, and is seen as a
good thing and also a bad thing both sides have valid arguments but with today’s day is very hard to get
away from that, so in a lot of books, articles and journals is mentioned how that can be used as a business
tools and how a lot of big corporation is using that one their day today.
The common keyword when you research AI is Artificial Intelligence for Business
TITLE AUTHOR YEAR ABSTRACT
Artificial intelligence
: a modern approach
Russell, Stuart J.
(Stuart Jonathan)
2003 Summary: Intelligent Agents - Stuart Russell
and Peter Norvig show how intelligent agents
can be built using AI methods, and explain
how different agent designs are appropriate
depending on the nature of the task and
environment. Artificial Intelligence: A Modern
Approach is the first AI text to present a
unified, coherent picture of the field. The
authors focus on the topics and techniques
that are most promising for building and
analyzing current and future intelligent
systems. The material is comprehensive and
authoritative, yet cohesive and readable.
State of the Art - This book covers the most
effective modern techniques for solving real
problems, including simulated annealing,
memory-bounded search, global ontologies,
dynamic belief networks, neural networks,
adaptive probabilistic networks, inductive
logic programming, computational learning
15

theory, and reinforcement learning.
Leading edge AI techniques are integrated
into intelligent agent designs, using examples
and exercises to lead students from simple,
reactive agents to advanced planning agents
with natural language capabilities.
Round 2 – Literature Review
Search keywords for Round 2 of this literature review are Artificial Intelligence in Business, with
23.939 search results, below are the most important ones.
Title Authors Year Journal
Understanding the Artificial
Intelligence Business Ecosystem
Quan, X.I.
Sanderson, J.
2018 IEEE Engineering
Management Review IEEE
Eng. Manag. Rev.
Engineering Management
Review, IEEE. 46(4):22-25
Jan, 2018
THE POWER OF HUMAN-
MACHINE COLLABORATION:
ARTIFICIAL INTELLIGENCE,
BUSINESS AUTOMATION, AND
THE SMART ECONOMY.
BOLTON,
CHARLYNNE
MACHOVÁ,
VERONIKA2
KOVACOVA,
MARIA3
VALASKOVA,
KATARINA
2018 Economics, Management &
Financial Markets. Dec2018,
Vol. 13 Issue 4, p51-56. 6p. 4
Graphs.
Can artificial intelligence and
online dispute resolution enhance
efficiency and effectiveness in
courts
Zeleznikow, John 2017 Article
The rising tide of artificial
intelligence and business
automation: Developing an
ethical framework
Wright, S.A.
Schultz, A.E.
2018 Article
AIQ: Measuring Intelligence of
Business AI Software
BenBassat, Moshe 2018 Working Paper
16

How real is the impact of artificial
intelligence?
Carter, D.2018 2018 In: Business Information
Review. (Business
Information Review, 1
September 2018, 35(3):99-
115)
The rising tide of artificial
intelligence and business
automation: Developing an
ethical framework
Wright, Scott A. ⁎
Schultz, Ainslie E.
2018 In ETHICS, CULTURE, AND
PEDAGOGICAL PRACTICES
IN THE GLOBAL CONTEXT,
Business Horizons
November-December 2018
Advanced Business Model
Innovation Supported by Artificial
Intelligence and Deep Learning
Valter, P.1
Lindgren, P.1,2
Prasad, R.1
2018 Wireless Personal
Communications. (Wireless
Personal Communications, 1
May 2018, 100(1):97-111)
integration of Knowledge
Management and Business
Intelligence for lean
organisational learning by the
Digital Worker
Kannan, Selvi
Miah, Md shah
jahan
2018 Book Section
The Human Lawyer in the Age of
Artificial Intelligence: Doomed for
Extinction or in Need of a Survival
Manual
Dobrev, Dessislav 2018 18 J. Int'l Bus. & L. 39
(2018) / Journal of
International Business and
Law, Vol. 18, Issue 1 (Winter
2018), pp. 39-68
In this second round of literature review it is something that is getting quite popular, for example they are
studying a way to use AI as a lawyer consultant which is an amazing idea and also a bit scary what else
could be done with AI, the main word it can derived from this search is Software from my research you can
see how popular AI is in software and how they can be use more and more from day to day tasks.
TITLE AUTHOR YEAR ABSTRACT
AIQ: Measuring
Intelligence of
Business AI Software
BenBassat,
Moshe
2018 Focusing on Business AI, this article introduces the
AIQ quadrant that enables us to measure AI for
business applications in a relative comparative
manner, i.e. to judge that software A has more or
less intelligence than software B. Recognizing that
the goal of Business software is to maximize value in
terms of business results, the dimensions of the
17

quadrant are the key factors that determine the
business value of AI software: Level of Output
Quality (Smartness) and Level of Automation. The
use of the quadrant is illustrated by several
software solutions to support the real life business
challenge of field service scheduling. The role of
machine learning and conversational digital
assistants in increasing the business value are also
discussed and illustrated with a recent integration
of existing intelligent digital assistants for factory
floor decision making with the new version of
Google Glass. Such hands free AI solutions elevate
the AIQ level to its ultimate position.
Round 3 – Literature Review
This is Round 3 literature review, in this round it has a lot less search results with Artificial
Intelligence Business and Software, below 6 of the most popular ones ranging from very recent to over 30
year old articles.
Title Authors Year Journal
Artificial Intelligence Is Almost
Ready for Business. Power, Brad
2015
Article
Competitive Intelligence
Platforms
Keiser, Barbie E. 2019 Article
AIQ: Measuring Intelligence of
Business AI Software BenBassat, Moshe
2018 Working Paper
The Chinese Tech Firms Pushing
Boundaries Of Artificial
Intelligence.
Wang, Yue 2017 Article
Artificial intelligence in service-
oriented software design Rodríguez,
Guillermo ⁎
Soria, Álvaro
Campo, Marcelo
2016
Article
Artificial Intelligence and the
Management Science
Practitioner: Expert Systems:
Getting a Handle on a Moving
Kenneth Fordyce
Peter Norden
Gerald Sullivan
1986 The Institute of
Management Sciences and
the Operations Research
Society of America, 1986.
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Target
Article 1
TITLE AUTHOR YEAR ABSTRACT
AIQ: Measuring
Intelligence of
Business AI
Software
BenBassat,
Moshe
2018 Focusing on Business AI, this article introduces the AIQ
quadrant that enables us to measure AI for business
applications in a relative comparative manner, i.e. to
judge that software A has more or less intelligence than
software B. Recognizing that the goal of Business
software is to maximize value in terms of business
results, the dimensions of the quadrant are the key
factors that determine the business value of AI software:
Level of Output Quality (Smartness) and Level of
Automation. The use of the quadrant is illustrated by
several software solutions to support the real life
business challenge of field service scheduling. The role of
machine learning and conversational digital assistants in
increasing the business value are also discussed and
illustrated with a recent integration of existing intelligent
digital assistants for factory floor decision making with
the new version of Google Glass. Such hands free AI
solutions elevate the AIQ level to its ultimate position.
This working paper aims to measure how AI can be implemented on the day to day of a business,
there are several software’s that can be used to improve on the daily productivity and also can help on the
day to day of the normal person, such as a consumer.
But the machine learning can be quite controversial as some people believe AI can create his own
language and have its own life, it happened not too long ago an AI that Facebook was testing had created
their own language and they started to communicate with each other, since them Facebook has shut down
those machines just to prevent anything else from happening.
Article 2
TITLE AUTHOR YEAR ABSTRACT
Artificial
intelligence in
service-
oriented
Rodríguez,
Guillermo ⁎
Soria,
2016
Service-Oriented Architecture (SOA) has gained
considerable popularity for the development of
distributed enterprise-wide applications within the
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software design Álvaro
Campo,
Marcelo
software industry. The SOA paradigm promotes the
reusability and integrability of software in
heterogeneous environments by means of open
standards. Most software companies capitalize on SOA
by discovering and composing services already accessible
over the Internet, whereas other organizations need
internal control of applications and develop new services
with quality-attribute properties tailored to their
particular environment. Therefore, based on
architectural and business requirements, developers can
elaborate different alternatives within a SOA framework
to design their software applications. Each of these
alternatives will imply trade-offs among quality
attributes, such as performance, dependability and
availability, among others. In this context, Artificial
Intelligence (AI) can assist developers in dealing with
service-oriented design with the positive impact on
scalability and management of generic quality attributes.
In this paper, we offer a detailed, conceptualized and
synthesized analysis of AI research works that have
aimed at discovering, composing, or developing services.
We also identify open research issues and challenges in
the aforementioned research areas. The results of the
characterization of 69 contemporary approaches and
potential research directions for the areas are also
shown. It is concluded that AI has aimed at exploiting the
semantic resources and achieving quality-attribute
properties so as to produce flexible and adaptive-to-
change service discovery, composition, and
development.
This is another great use of AI, used to improve on the service oriented Architecture, it has become
more and more popular in the software industry a lot of the corporations gain with SOA by finding and
composing services on the internet.
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