Utilisation of Artificial Intelligence in Businesses

Learn about the utilization of artificial intelligence in businesses and how it is being implemented to automate processes and improve decision-making. Explore the goals and objectives of AI, its application in different sectors, and the benefits it brings to businesses. Discover how AI is transforming industries and the ethical considerations that come with its use.

Running head: ARTIFICIAL INTELLIGENCE
Artificial Intelligence
Name of the Student
Name of the University
Author Note

1ARTIFICIAL INTELLIGENCE
Table of Contents
Introduction................................................................................................................................2
Goals and objectives of Artificial Intelligence (AI)...................................................................3
Utilisation of Artifical Intelligence in numerous Bunisnesses...................................................8
Need for responsible AI...........................................................................................................12
AI implementation strategy......................................................................................................15
AI maturity assessment............................................................................................................17
Conclusion................................................................................................................................19
References................................................................................................................................20

2ARTIFICIAL INTELLIGENCE
Introduction
The contemporary stretch of time has been witness to remarkable advanced
developments which has created ripples in the technical ecosystem. One, out of the many
ripples in the world of technology and innovation is the development of Artificial Intelligence
or AI. Artificial intelligence or AI is the simulation of human intelligence processes by self
learning machines or a computer system that interprets the data collected to study and
identify patterns and implement the information to make decisions. The quest for machines to
understand, identify, learn, reason and act intelligently has lead to the development of
Artificial intelligence. The process of acquiring knowledge involves learning of the
recognized data, reasoning to reach a valuable conclusion and lastly self correction. Artificial
Intelligence is a mechanized form of natural intelligence shown by humans. Artificial
Intelligence or Machine Intelligence imitates the cognitive functions and processes of the
human mind to intercept patterns of interaction, learning and problem solving. Currently no
computer system is completely equipped or programmed to portray the wide spectrum of
artificial intelligence. Sooner or later in the next decade artificial intelligence will carve out a
niche for itself as it has already started to display its potential in the field of science,
commerce, healthcare and technology. Artificial intelligence has strong or weak
categorization depending on the task assigned to them. Narrow or weak AI works on a
specified task for which the machine is particularly programmed. A strong AI system
portrays a wide range of human cognitive skills and abilities in its decision making process.
A strong AI when comes in contact with an unfamiliar task, uses the embedded skills to
reason out the situation and device a decision without human intercession.
There are numerous benefits with the use of AI in each of the business filed other than
the much discussed science and technology sector. The use of artificial intelligence will

3ARTIFICIAL INTELLIGENCE
improve the quality of services and product delivered which will positively impact the
society. AI as a service is widely incorporated in the vendor offerings. AI as a Service allows
organizations and individuals to experiment the attributes of AI in the field of business to
process orders and sampling of multiple platforms before signing for a commitment [1]. AI
tools present a plethora of functionalities for businesses, but the extensive use of artificial
intelligence raises ethical questions. The reason behind the concerned ethical issues is that
deep learning algorithms underpins the advanced AI tools as they are smart as the data feed
into the system in the training process. Human bias in the case of AI program is inherent and
requires close monitoring of the process [2]. Artificial Intelligence holds the capacity to
solve critical problems and benefiting the society as a whole. There is a general improbable
expectation and discussion about the way artificial intelligence will change the work culture
and other business processes [3]. This aspect calls for a responsible use of artificial
intelligence in individual field of business and technology. The report will discuss in detail
the significant goals of artificial intelligence in every aspect, the greater good the technology
plans to achieve and the responsible call in its utilization of this advanced technology.
Goals and objectives of Artificial Intelligence (AI)
Artificial Intelligence has promising goals for the human race and the services
provided by augmented intelligence outperform human productivity and efficiency. The goals
set by Artificial intelligence initially seems unrealistic to the general, but the truth of the
matter is that, artificial intelligence extends its services beyond human comprehension. The
motive lies in gaining technological singularity in the business filed by eliminating human
intervention [4]. Artificial intelligence plans to take the dominant form intelligence in
services which will annihilate dehumanizing, mortifying and tedious jobs. The goals set by
artificial intelligence are categorized for the numerous sectors it extends its services to. No

4ARTIFICIAL INTELLIGENCE
two goals are the same as the line of production differs completely moving from one industry
to the other [5]. Initially the goals set by artificial intelligence seem unrealistic but they are
most realistic in nature. The chief goal of artificial intelligence is to cause exponential
intelligence explosion and where technology is the answer to every critical problem [6]. The
additional important goals of artificial intelligence correspond to all the conventional issues
of the research of artificial intelligence for solving and the subsets as well as the particular
sectors of artificial intelligence which includes machine learning, machine consciousness,
machine intelligence, reasoning, logic implementation, natural language processing, robotics
and computer vision [6]. All of the mentioned attributes build by augmented reality and
delivers exceptional performance. Artificial Intelligence will create a smart, mechanized and
intellectually globally networked being [7].
Machine Learning, Machine Intelligence and Machine Consciousness: Machine learning
involves the arrangements of algorithms used by intelligent machine to conciliate information
from the induced system and from its experience [8]. Machine learning is a chief part as well
as an application of artificial intelligence [9]. Chief goal of machine leaning lies in the
scientific studying of statistical models and algorithm to understand pattern for its implicit
use to efficiently perform a mentioned task. The performance of the specified task involves
the use of data acquired from the scientific analysis and the process does not rely on explicit
instructions but on inference instead [10]. The central concept of machine learning introduces
a significantly different approach compared to traditional computer programming. To be
specific about the functionalities of machine learning, the technology involves development
and utilization of complex computer algorithms that process and analyses Big Data fed into
the desired system. The algorithm uses the data extensively to learn and recognize pattern for
implementation [11]. Machine learning provides multiple opportunities and benefits such as
supplementation of data mining, consistent improvements and automation of the given tasks.

5ARTIFICIAL INTELLIGENCE
The real world applications involve ranking of search engines available, delivery of content,
online advertising, autonomous driving and intelligent assistant to list a few [12]. Machine
Intelligence involves the utilization of complex array of algorithms to learn own its own
through experience and comprehension. An example of machine intelligence system is Deep
Neural Networks. Machine consciousness system (MCS) on the contrary gains knowledge
without requiring external data or information. MCS is a self learning and self gaining
system. The applications of these systems lie in multiple fields and cater to several public
services and create ample opportunities for development.
Knowledge representation and Reasoning: The specified field of Knowledge
representation and reasoning or KR&R in artificial intelligence focuses on scheming and
implementation of information which holds the capability to critically process information on
worldly data and use the acquired ability to provide solution to highly complex problems.
Among the many goals of artificial intelligence, the KR&R particularly intends to automate
numerous and different types of reasoning. It includes the complete codification of the factors
of ideas and transitions of the set of facts in one particular scheme which enables easy
interpretation by a computer system [13]. A significant number of knowledge representation
and reasoning application involve the assistance provided to health servers to interpret images
by using computer aided diagnosis [14]. The other applications include the use of human
language as an input to interact with software or computer systems.
Automated scheduling and planning: Automated planning which is referred to as AI
planning is a subset of AI or artificial intelligence. The sector of the artificial intelligence that
is connected with automated generation of the action sequences that corresponds to the
strategies which could be executed by any artificial system like automated robots and
uncrewed vehicles. It can be said that it is one of the many fundamental capabilities that are

6ARTIFICIAL INTELLIGENCE
required for the increasing the flexibility and autonomy of any Artificial intelligence system.
Some of the examples of artificial intelligence planning and scheduling include self-
correction of software applications and computer programs, robotics that can serve as an
autonomous agent, computer-aided recommendations and automated data gathering. Basic
conventional issue with the implementation of artificial intelligence lie in the way AI
processes to aim at complete automation and mechanization of a scheme founded on
predetermined objectives and from previous collection of possible actions [15]. AI has
significant contribution in the automation world and it further promises to provide new means
to improve the existing automated entities.
Natural Language Processing: Another significant goal and prominent subset of artificial
intelligence is NLP or natural language processing. NLP or natural language processing
chiefly deals the generation and extensive analysis of natural languages, which can be put
into use by the humans to execute interaction with the computer interface. In other words it
can be said that natural language processing highly regards the interaction that takes place
between a human and a computer system by utilizing the basic language rather than using any
specific computer language. More so, because, the interaction with the computers is among
the common and the basic issues with artificial intelligence, the intention of NLP is to
develop as well as implement in the computer systems, specifically the computers programs
that could process massive quantities of data regarding natural languages [16]. Achieving of
the mentioned aim requires serious overcoming of certain predefined challenges like speech
recognition and natural language generation. The assistant services provided by multiple
companies that are significantly intelligent such as the Google Now and the smart application
of Siri developed by Apple Inc. utilizes NLP or natural language processing with other
additional attributes of artificial intelligence like machine learning, data mining, automated
planning and scheduling to mention a few.

7ARTIFICIAL INTELLIGENCE
Computer vision: The computer vision involves the acquiring and comprehension or
understanding of the visual data collected explicitly from still or mobiles digital and live
images available inexpensively all around for the efficient utilization by the artificial
intelligence to analyze for the purpose of valued decision making. True intention of this
particular subset of artificial intelligence lies in impersonating the human visionary system to
collect, harness, recognize, analyze live images for the purpose of understanding the given
circumstances and provide effective solution to any visible underlying problem [17]. The
system truly replicates the optical process and function of a human to interpret any live or
animated image for collecting significant data out of it. The data gathered is later harnesses to
add value to the thinking process of the machine to help identify similar situations in the
future.
Robotics: Robotics is the promising entity of automation and technology. The use of robots
has significantly helped the human race to solve severely complex process or get access to
locations which were not accessible to humans due to its atmospheric conditions. Robotics is
yet another application and an important subset of Artificial Intelligence. Robotics is an
amalgamation of technology and innovation which brings about almost all the technological
disciplinary sector like computer science, mechanical engineering, electronic engineering and
information engineering. Robots are designed to impersonate the human locomotive actions
and completely replace manual work by total mechanization of the process. The integration
of artificial intelligence and mechanical engineering have given a device so productive and
advanced which has solved a large number of human problems [18]. The robots are equipped
with sensors and are programmed in such a fashion to provide them a mind of their own
which is put in use by the robots to send feedbacks and perform predefined tasks. The mind
designing of the robot allows the mechanized devices to operate on their own without
requiring any human intervention [19].

8ARTIFICIAL INTELLIGENCE
The present research in the field of advanced robotics intends to introduce
commercial, domestic and military submissions [20]. For example, Amazon could be
considered where the robots are used for the automation of numerous jobs. The company
utilizes the robotics in their facilities system of the warehouse, burdening the robots with the
job to efficiently organize the selected products ordered in each numbered row making it easy
for the delivery process. It helps in the simplification of Amazon’s delivery and business
processes. Robots can be made to work throughout the day without any weariness identified
in them which surely cannot be done by a human. Using robots in delivery and production
process improves the productivity of the working system, accuracy is maintained and the
entire process is quick and smooth without the involvement of any technical glitches or
exhaustion.
Utilisation of Artifical Intelligence in numerous Bunisnesses
In the significant quest for sophistication and to satisfy the growing demand, human
beings have constantly developed and improved the pre-existing technologies. Chief purpose
behind exercising innovation and development practice is to ensure the constant growth and
evolution of the products and services available in the market with added motive to improve
and launch new services to meet the ever growing customer demand in the contemporary
competitive market space. There are numerous activities which are being regularly executed
as man developed and diverged into the field of artificial intelligence. The inception of the
idea was majorly focussed on the creation for the purpose of performing jobs that humans are
unable to execute. This concept of artificial intelligence outlines the utilization of the
computer systems for the performing of the tasks that commonly requires significant human
intelligence and intervention. There are several instances where artificial intelligence could
be superior to humans like speech recognition, visual perception and decision making [21].

9ARTIFICIAL INTELLIGENCE
While artificial intelligence is being immensely implemented in a lot of business models for
automating several processes Artificial intelligence not only proved its worth in the
technological service fields but is receiving major attention from commerce and military
sectors. Artificial intelligence can be implemented in financial business module to understand
businesses growth, financial structure and market patterns to device flexible and effective
strategy for business to bloom. Majority of the researchers in the artificial intelligence sector
considers rational thinking and then acting as a prerequisite for intellectual behavior. AI helps
in the study of complex market pattern to simplify the understanding and aids in devising
flexible module for the business framework. Artificial Intelligence extensively delves and
studies the forecasting loop to reach a unanimous conclusion that is undertaken to make
decisions on the identified factors [21].
Some of the benefits of artificial intelligence in organizations and businesses include:
Effective decision making using AI: AI investigates the theory of decision making and
utilizes the preferences of the many rational agents to determine the actions that are required
by the agents to perform for maximizing the functional utility. The decision theory has the
roots in economics as it investigates circumstances where the agents are required to tackle
with any uncertainty regarding the present state of the world and its future. Artificial
intelligence allows individuals to hold a better understanding of a complex situation and chart
out a plan that will effectively solve the given crises [22]. AI uses statistical data inputs to
study pattern related growth and current situation, analysis of the information acquired is
done critically with the chief purpose to provide a simplified solution to the highly classified
problem. Business which have taken the help of artificial intelligence for the purpose of
effective decision making have hugely benefited from its application. The decision making
theory permits the agents in evaluating the uncertainty of a conflicting circumstance under

10ARTIFICIAL INTELLIGENCE
finite or infinite decision horizons as well as the provided set of all the acquired references.
The preferences are then represented in the form of utility functions and rewards which are
assigned numeric values for the possible states of the world to express any desirability for the
particular agent. The rational agents would then select the actions based on the principle of
maximum expected utility meaning the agent would prefer to choose the actions which would
surely help in maximizing the reward or the expected utility that is being tried to accomplish.
The evaluation must methodically differ the bounds of the model of the decision theory for
exploring the means by which sensitivity of any outcome of the decision could be of tiny
alteration for any assigned utility and probability. The models of the decision-theoretic could
underlie a decision that has to be swiftly taken into the business process like buying or selling
of stocks, providing accurate recommendations to consumers of the business services [23].
The artificial intelligence system benefits from the models of decision making-theory for
efficient dealing with all uncertain information or data. The present trends in the commercial
market like the personal digital assistants and cognitive computing offer interesting
connections to the decision making theory.
Efficient prediction using data with the help of Machine learning: Machine learning has
hugely benefited the working and prediction process of organizations. The methods of
machine learning could be extensively applied to any available data for specified business
process for the effective computation and prediction of future trends [24]. AI or artificial
intelligence has developed several distinct algorithms for machine learning like neural
networks, or the decision trees that are presently available in the libraries and these
technologies are prepared to be used. The effective learning permits any agent to enhance the
performance based on the perceptions that are made in the world. Research on the field of
machine learning distinguishes from the subject others between the supervised and
unsupervised modules of learning. In unsupervised learning, the agent understands the

11ARTIFICIAL INTELLIGENCE
patterns from the input without any feedback being received. In supervised learning, the
agents comprehend from all the labeled instances of I/O (input-output) pairs and data fed into
the training process. The conclusion of the learning process is then evaluated extensively on
the test data using which the agent makes effective prediction of the relatable output based on
the provided input [25]. The algorithms that are designed for the learning differs significantly
in representation of any outputs and inputs, the kinds of the models that could be learnt by
them and the methods by which the learning is executed [26]. The community of machine
learning has been successful in the development of the various measures like recall, accuracy,
precision, and AUC for efficiently describing of quality of the algorithm. Additionally, the
methods of the statistics offer information on standard deviation and on the confidence
intervals. When evaluation of several algorithms of machine learning is conducted for any
business application process, then the measures could be applied for deciding the proper
method of learning the appropriate mean business process functionality [27]. Machine
learning is being extensively utilised for numerous business process management because it
has the capability of detecting any underlying problems and predefined patterns as well as
business functions that are related to the output and input that have prevailed in the system
without the knowledge of the man monitoring the process[28]. These specific methods could
be significantly useful for pattern when men face difficulties in stating the properties of the
input data that is extensively utilised for determining of the input fed [29]. In the business
process, the major ability of the detecting the patterns have been successfully utilized for
spotting deviating behavior such as frauds of digital or for the classification of sensitive,
segregation of customers for digital and traditional marketing process [30]. Machine learning
methods are highly flexible when applied to altering inputs. This flexible property of the
system surges the overall flexibility of the business framework for an organization. The
organization can easily deal with altering framework and adjustment of business assets [31].

12ARTIFICIAL INTELLIGENCE
It could also be utilized for data mining and detecting of business norms when business
processes are monitored [32].
Need for responsible AI
The field of AI is rapidly growing and the near decade will see more development in
its application in business process and organizations. Even though AI provides the mentioned
benefits for organizations and business there are adjoining risks which are to be considered
while utilizing artificial intelligence in enterprises or organizations [33]. Artificial
intelligence has major challenges in its working process. The narrow applications of AI
which are chiefly used in recent business model are designed to handle a specific problem in
a particular domain. When such an approach is implemented, the application cannot adapt to
changing or new broader challenges until and unless the system framework is redesigned. In
a business scenario, there is always a new challenge every other day which the managers tend
to. The application of artificial intelligence is limited here as the system will require complete
revolution and fresh programming to understand and critically analyze the new cropped up
challenge. Another challenge lies in the data collection process and the type of data gathered.
The heterogeneous and the unstructured sources of the data are being increasingly combined
for establishing prediction structure for businesses. Majority of the data is significantly
uncertain, and no one could be sure regarding the veracity of the data. The practitioners first
integrate the data and then perform data abstraction. But it has been observed that the
reliability of the data is easily lost due to this method [34]. The output of any of the
prediction model could be increasingly uncertain. It has been observed that the majority of
the techniques of the machine learning solely focus on the model which is completely
deprived off offering any estimate on process accuracy. For arriving at any prediction, there

13ARTIFICIAL INTELLIGENCE
is a requirement to utilize the learning methods of the total data set readily available for any
business process [35].
Moreover, it has been displayed that machine learning algorithms can make erroneous
decisions with the hidden patterns and the states in data. Such problems grow to be
increasingly critical if the approaches of machine learning have been applied to the data set
where no dependable test oracles are prevailing or even when the unsupervised methods of
learning are executed [36]. As it has been predicted in the earlier stages, the unpredictable
alterations of the data are highly to emerge from the actions and the predictions that are
applied across the complete universe of the business processes. But it has been observed that
there is no information on the methods by which the learning algorithm would behave on the
altered data that is the confidence would be immensely dissimilar and the effects would
directly be imparted on data alteration. Additionally, the algorithms of learning seems to
perform increasingly well on the narrow domains where complete information is considered
as explicit in the representation of the data but the wider domains where information or data
contain hidden states which are commonly found in Big Data application and it seems to pose
larger problems.
There are some ethical issues which needs consideration while working with artificial
intelligence in businesses [37]. Some of the common ethical issues that are associated with
artificial intelligence (AI) are as follows:
Unemployment: The major hierarchy of the labor class has been concerned primarily with
automation of systems. As the methods have been discovered for automation of jobs, there
has been an incressed change in the thought process of individuals. Automation of tasks
surely reduces mauanl labor and monotony yet it comes around with significant

14ARTIFICIAL INTELLIGENCE
disadvantages. It helps in strategic characterising of administrative work in the globalised
society. In this era of innovation and automation, a greater section of the labor class will lose
out on jobs. As it is seen that mostly labors depend on physical work to earn a livelihood,
such group all labors have already started losing out on jobs and are rendered jobless. The
application of artificial intelligence in the field of manual jobs, have revolutionized the entire
process by enhancing product and service quality, delivery speed and creation of real time
applicable data. Only skilled workers are able to retain their job. In the near future AI will
render a larger section of the society jobless and this raises certain ethical concerns.
Inequality in jobs: The economic systems are majorly based on the compensation and
economic contribution. The majority of the companies are still significantly dependent on the
hourly work where services and products are concerned. But with the utilization AI or
artificial intelligence in their business module, the company or the business enterprise could
drastically cut down the dependency on human labor and the change will surely minimize
company expenditures which will directly impact the company’s revenue positively. This will
create segregation in job profile and give rise to inequality in jobs.
Behavioral change in business due to the implementation of AI: Artificial intelligence
equipped bots are growing to be increasingly intelligent at mimicking and modeling human
interactions and relationships. This could impact negatively on the businesses as it would
create huge dissimilarity among the employees. The extensive modeling of human behavior
by the artificial intelligence system will create a situation when man would not be required in
any business process as the complete work could be done by the intelligent systems. The
interactions within the business ecosystem would be severely reduced raisng coordination
issue between the management and the employees of the organisation.

15ARTIFICIAL INTELLIGENCE
The sole purpose for the development of artificial intelligence is to achieve technological
singularity and super intelligence. When an artificial intelligence system becomes powerful it
starts to be super intelligent [38]. A super intelligent AI system is superior to any human
performance in any given sector. Artificial intelligence will truly be a superior power
irrespective of various domains. This is will bring about a transformation economically,
politically and socially [39]. A super intelligent AI system poses catastrophic risk and threats
of misuse. Failure in such a super intelligent system will wreak havoc in the world of
technology and bring about serious destruction. This will lead to loss of billions of jobs and
strain human interactivity and activity. A misuse of these super intelligent techniques can
lead to national security risk and bring about potential damage to citizens [40]. Therefore,
there is an urgent need for the responsible use of AI applications. A responsible call in the
application field of AI includes the positive aspects and benefits AI have to offer to the
human race. When the positive attributes are used in the tight manner, the generals achieve
satisfying delivery of services.
AI implementation strategy
The prime goal of any artificial intelligent system must be to motivate man and blend
the ingenuity with advanced technology, ethical codes, inclusive design and the
accountability to empower a large section of the ever growing population [40] . The artificial
intelligence systems must benefit society but also should not dehumanize this particular
aspect.
The five-step process that is suggested for the implementation of artificial intelligence
in buisness is:

16ARTIFICIAL INTELLIGENCE
Strategy definition: Identification of the desired outcome by implementing artificial
intelligence methods tagging along the required resources for the process installation. With
the implementation of the strategy, the company is now ready to initiate the development and
working of AI in its system. It is important to note that the strategy that has been developed
would act as a foundation for the work that would be done in the future regarding the
implementation of artificial intelligence in the business framework. The next stage that is
associated with this is the identification of the attributes which requires prior focus; they are
the technical method of required to easily blend with the human ingenuity to provide an
solution for the complex problem at hand.
Recruiting and training: This particular stage involves hiring of highly skilled staff that is
required for transforming and converting the organization’s proposed vision into reality. The
process involves simultaneous training of the existing staff for taking the desired advantage
of the new systems. When the hiring process is initiated to take in skilled personnel in the
organization for the enhancement of the business process using AI, it is required to analyze
the talent the new personnel hold. The development of the complex software for custom
modeling is another aspect; therefore, it is a requirement to have proper idea about the
technical knowledge of the staffs that are being hired.
Operationalise: There is the requirement for preparing the launch of the new artificial
intelligence based systems by converting them as part of the current operations. Ensuring
every system, process and tools are in their respective place and it has been clearly
understood by all the employees prior to going live.
Deployment: This particular stage at which the new systems of artificial intelligence go live
as well as start supporting business modules and processes. This particular stage is the stage

17ARTIFICIAL INTELLIGENCE
where all the hard work that has been dedicated pays off and then it starts the required
delivering results. The deployment stage is a crucial stage for the organization as a lot
remains at stake.
Optimization: Major advantage of using digital technologies such as artificial intelligence lies
in the metrics and analytics which have been designed to assist additional improvement in the
existing systems.
AI maturity assessment
The framework that is most suitable for the effective assessment of the artificial
intelligence maturity of any organization is:
AI novice: This is the immature phase in which business is not taken into the proactive
stages on AI journey as well as at best is in the mode of assessment. This business would not
be in the position of taking any significant advantage of all the provided opportunities by the
capabilities of the artificial intelligence. The process is hindered by lack of the cohesive
strategy, restricted organizational alignment and the insufficient availability and accessibility
of data.
AI-ready: The businesses, which are significantly AI ready, are in a suitable position for
initiating the journey of AI in their business structure. They are adequately prepared in terms
of specific implementation strategy, setup of enterprise availability of data for moving ahead.
AI technology is then implemented; the solutions are received in the defined scenarios of the
operation. The business must take the next step by investing tactfully to enable the connected
skills, data and the technology for realization of the plan.

18ARTIFICIAL INTELLIGENCE
AI proficient: The businesses at this particular phase is in the development mode of AI that
have reasonable degree of experience as well as clear comprehension of the means by which
the business is intending to move ahead with AI or artificial intelligence. But there are
prevailing gaps and the restrictions in the roadmap of the decided strategy, the data
capabilities, as well as the technology resources. These specific pitfalls affect range and the
depth of the AI-powered structures, the addressing of the operational scenarios that ultimately
denotes all the missed opportunities.
AI advanced: The business with AI advanced score has been observed to have achieved better
level of AI maturity. These businesses are easily moving ahead for the implementation of the
artificial intelligence in the businesses. These businesses have the required experience and
expertise in artificial intelligence, with the established track record in the use cases that are
powered by artificial intelligence. But the businesses that are increasingly using advanced
modules of artificial intelligence driven system could not be complacent and they should
ensure that the companies stay ahead of the new development in AI as well as the probable
impacts on the business that could be both positive as well as negative.

19ARTIFICIAL INTELLIGENCE
Figure: AI maturity assessment
Conclusion
Thus, it can be concluded that Artificial Intelligence or AI has several benefits in the
business line. The benefits provided by AI create ample opportunities in technology and
business. Advancement in the field of AI will not only benefit the technological aspect of AI.
But will extensively aid in the development and expansion of business entities. As it is known
every advantage tags along with a disadvantage, AI has certain disadvantages which will
disrupt the traditional working culture of organizations. Overall AI promises to gift a bright
future for organizations and businesses to expand and flourish.

20ARTIFICIAL INTELLIGENCE
References
[1] SJ Russell, P Norvig. Artificial intelligence: a modern approach. Malaysia; Pearson
Education Limited,; 2016.
[2] NJ Nilsson. Principles of artificial intelligence. Morgan Kaufmann; 2014 Jun 28.
[3] A Barr, EA Feigenbaum, editors. The handbook of artificial intelligence. Butterworth-
Heinemann; 2014 May 12.
[4] AH Bond, L Gasser, editors. Readings in distributed artificial intelligence. Morgan
Kaufmann; 2014 Jun 5.
[5] R Gasser, MN Huhns. Distributed artificial intelligence. Morgan Kaufmann; 2014 May
23.
[6] E Wenger. Artificial intelligence and tutoring systems: computational and cognitive
approaches to the communication of knowledge. Morgan Kaufmann; 2014 May 12.
[7] D Li, Y Du. Artificial intelligence with uncertainty. CRC press; 2017 May 18.
[8] E Charniak, CK Riesbeck, DV McDermott, JR Meehan. Artificial intelligence
programming. Psychology Press; 2014 Jan 21.
[9] PR Cohen, EA Feigenbaum, editors. The handbook of artificial intelligence. Butterworth-
Heinemann; 2014 Jun 5.
[10] Z Ghahramani. Probabilistic machine learning and artificial intelligence. Nature. 2015
May;521(7553):452.
[11] J Copeland. Artificial intelligence: A philosophical introduction. John Wiley & Sons;
2015 Jul 29.
[12] LN Kanal, JF Lemmer, editors. Uncertainty in artificial intelligence. Elsevier; 2014
Jun 28.
[13] L Steels, R Brooks. The artificial life route to artificial intelligence: Building
embodied, situated agents. Routledge; 2018 May 15.

21ARTIFICIAL INTELLIGENCE
[14] C Glymour, R Scheines, P Spirtes. Discovering causal structure: Artificial
intelligence, philosophy of science, and statistical modeling. Academic Press; 2014 May
10.
[15] M Imran, C Castillo, J Lucas, P Meier, S Vieweg. AIDR: Artificial intelligence for
disaster response. InProceedings of the 23rd International Conference on World Wide
Web 2014 Apr 7 (pp. 159-162). ACM.
[16] J. Hirschberg and C.D. Manning. Advances in natural language
processing. Science, 349(6245), pp.261-266, 2015.
[17] D Gunning. Explainable artificial intelligence (xai). Defense Advanced Research
Projects Agency (DARPA), nd Web. 2017.
[18] H Lu, Y Li, M Chen, H Kim, S Serikawa. Brain intelligence: go beyond artificial
intelligence. Mobile Networks and Applications. 2018 Apr 1;23(2):368-75.
[19] D Hassabis, D Kumaran, C Summerfield, M Botvinick. Neuroscience-inspired
artificial intelligence. Neuron. 2017 Jul 19;95(2):245-58.
[20] RJ Spiro, BC Bruce, WF Brewer. Theoretical issues in reading comprehension:
Perspectives from cognitive psychology, linguistics, artificial intelligence and education.
Routledge; 2017 Nov 3.
[21] R Cellan-Jones. Stephen Hawking warns artificial intelligence could end mankind.
BBC news. 2014 Dec 2;2:2014.
[22] Y Zang, F Zhang, CA Di, D Zhu. Advances of flexible pressure sensors toward
artificial intelligence and health care applications. Materials Horizons. 2015;2(2):140-56.
[23] C Rich, RC Waters, editors. Readings in artificial intelligence and software
engineering. Morgan Kaufmann; 2014 Jun 28.
[24] S Russell, D Dewey, M Tegmark. Research priorities for robust and beneficial
artificial intelligence. Ai Magazine. 2015 Dec 31;36(4):105-14.

22ARTIFICIAL INTELLIGENCE
[25] M Moravčík, M Schmid, N Burch, V Lisý, D Morrill, N Bard, T Davis, K Waugh, M
Johanson, M Bowling. Deepstack: Expert-level artificial intelligence in heads-up no-limit
poker. Science. 2017 May 5;356(6337):508-13.
[26] D. Li, and Y. Du. Artificial intelligence with uncertainty. CRC press, 2017.
[27] VC Müller, N Bostrom. Future progress in artificial intelligence: A survey of expert
opinion. InFundamental issues of artificial intelligence 2016 (pp. 555-572). Springer,
Cham.
[28] BL Webber, NJ Nilsson, editors. Readings in artificial intelligence. Morgan
Kaufmann; 2014 May 12.
[29] M Johnson, K Hofmann, T Hutton, D Bignell. The Malmo Platform for Artificial
Intelligence Experimentation. InIJCAI 2016 Jul 9 (pp. 4246-4247).
[30] FM Brown, editor. The Frame Problem in Artificial Intelligence: Proceedings of the
1987 Workshop. Morgan Kaufmann; 2014 May 12.
[31] MQ Raza, AKhosravi. A review on artificial intelligence based load demand
forecasting techniques for smart grid and buildings. Renewable and Sustainable Energy
Reviews. 2015 Oct 1;50:1352-72.
[32] TJ Bench-Capon. Knowledge representation: an approach to artificial intelligence.
Elsevier; 2014 Jun 28.
[33] F Jiang, Y Jiang , H Zhi, Y Dong, H Li, S Ma, Y Wang, Q Dong, H Shen, Y Wang.
Artificial intelligence in healthcare: past, present and future. Stroke and vascular
neurology. 2017 Dec 1;2(4):230-43.
[34] D Acemoglu, P Restrepo. Artificial intelligence, automation and work. National
Bureau of Economic Research; 2018 Jan 11.
[35] S Jha, EJ Topol. Adapting to artificial intelligence: radiologists and pathologists as
information specialists. Jama. 2016 Dec 13;316(22):2353-4.

23ARTIFICIAL INTELLIGENCE
[36] K Frankish, WM Ramsey, editors. The Cambridge handbook of artificial intelligence.
Cambridge University Press; 2014 Jun 12.
[37] . N Bostrom, E Yudkowsky. The ethics of artificial intelligence. The Cambridge
handbook of artificial intelligence. 2014 Jun 12;1:316-34.
[38] E Davis, G Marcus. Commonsense reasoning and commonsense knowledge in
artificial intelligence. Commun. ACM. 2015 Sep 1;58(9):92-103.
[39] W Ertel. Introduction to artificial intelligence. Springer; 2018 Jan 18.
[40] O.A. Osoba and IV, W. Welser. An intelligence in our image: The risks of bias and
errors in artificial intelligence. Rand Corporation, 2017.