Contemporary Issues in Digital & Business Technologies

This article discusses the future role of Artificial Intelligence in business functions, especially in manufacturing and production, and the impact of hackers on international businesses. It also highlights the potential risks and benefits of AI and cyber security firms in the digital age.

Running head: CONTEMPORARY ISSUES IN DIGITAL & BUSINESS TECHNOLOGIES
CONTEMPORARY ISSUES IN DIGITAL & BUSINESS TECHNOLOGIES
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Table of Contents
The Future Role of Artificial Intelligence on a Business Function...........................................2
Impact of Hackers on International Business.............................................................................8
References..................................................................................................................................9

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The Future Role of Artificial Intelligence on a Business Function
Artificial intelligence is used extensively in many industries nowadays such as
commercial, retail, banking and gaming. For the business sector, especially in manufacturing
and production, Artificial intelligence is slowly making its way and the perceived future with
this evolving technology looks promising. Machines which are driven by AI are creating new
benefits by offering better machine – human interaction, increasing production efficiencies
and better opportunities (Nilsson 2014). Artificial Intelligence will bring about a new age of
automation by rebuilding the way humans interact and collaborate with machines leading to a
better digital economy.
The manufacturing and production business process has faced a lot of issues such as
overload of information, integration issues, issues in decision making and expertise shortage.
Introduction of AI has facilitated businesses to mitigate many of these issues.
The future role of AI in this business process will be seen in mass production. Robots
and AI will play a big role in business as well as industrial manufacturing. AI will be used to
power robots for automating solutions, minimising human errors and providing quality
services.AI will be used to automate processes as humans are capable of working in 3 shifts
for continuous production, while AI robots can work all day without interruption. In the
future, AI will be used for expanding businesses for meeting the high demand from
customers all around the world. AI will be also used to make the operational environment
safe. Workplace accidents are common in manufacturing plants (Vasant 2015). AI robots can
be used to operate in risky situations of the manufacturing process, so that less human
resource is employed in carrying out dangerous and tedious work. In the future, most of the
boring and repetitive tasks will be operated by Artificial intelligence. With the AI robots

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working around, humans can concentrate on more innovative and complex tasks which will
enable more innovation for the business.
Another future role of AI in this process will be that the operating costs of
manufacturing processes will condense (Zhou et al. 2015). Although incorporating AI in the
business processes will need a significant amount of investment, still in the long run, it will
make the entire process much easier to manage.
Figure 1: AI effect on manufacturing and production
(Source: Vasant 2015)
The advancement in industrial automation and AI in the recent years have advanced
considerably. A generation of new robots can be produced due to increase in computing
power, sensor advancement and machine learning development (Michalski et al. 2013). In the
future, AI will be able to adapt to new environments, learn and acknowledge patterns and
analyse meaningful data. Artificial intelligence will be able to improve the manufacturing
process due to their decisions which are data driven, promoting better production outcomes,
improve the effectiveness of the process, reduce the operational costs, simplify scalability and
product development (Bench-Capon, 2014). Communicating with Ai will gradually become

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easier as AI is able to translate neural languages efficiently. This can be seen in the world
today where a software automatically recommends us to a preference list which saves the
trouble of navigating through the whole menu. The intention of the user is comprehended by
the AI leading to better outputs and less errors.
Since the 1970s, industrial robots and drones have been used in businesses. With the
rapid advancement in this domain, AI will be involved in keeping the inventories in an
effective manner which will reduce their costs and empower the business development
(Russell and Norvig 2016). AI will be involved in coordinating the quality control,
production line, design team and supply chain of the entire process.
Figure 2: Great value added in 2035 for manufacturing in businesses
(Source: Jeschke et al. 2017)
In the future, AI will be used to detect product defects. Due to the rapid advancement
in computer visualization, AI will be used in quality assurance to defect detection in real
time. Managers will not have to give sensitive information to workers for putting them in

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manually. AI will be able to understand how to apprehend the information (Kittur et al.
2014). Stock transactions can be carried automatically as soon as an employee takes raw
materials from the shelf. Similar to this, other tasks will be automated where inputting things
via hands is not necessary.
The internet of things or IoT will become more integrated with AI in the future. With
IoT powered by AI, services and supplies can be provided to customers in a way that was not
comprehended before (Springer et al. 2015). It can also provide distributors and producers an
in depth analysis report to evaluate factors and quality that can decrease productivity. In the
future, AI will be able to improve design processes of manufacturing products. Augmented
generative designing is implemented in this method where the products are made based on
their evolution.
In the manufacturing processes, the profit margins are low in contrast to the initial
capital investments which remain high. This has led the manufacturing processes to migrate
to the low wage countries where the cost of hiring human resource is comparatively low. For
a while now, the people of developing countries such as US and Europe has lamented about
the loss of jobs in their respective countries (Bond and Gasser 2014). In the future, with AI
controlling most of the manufacturing processes, companies would not have to migrate to
other countries for cheaper resources. Moreover, as the workers will be replaced by AI
controlled machines, they will be retrained to perform maintenance, programming and high
level tasks. Most of them will have to develop applications so that the AI can automate
normal tasks making the entire business procedure profitable as well as feasible.
In the future, one of the roles of AI in the manufacturing processes will be machine
vision. With High resolution cameras, AI will be able to detect images with way more
sensitivity than the normal eye can perceive. It will be able to make sense out of images

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which was not perceivable before. Machines powered by AI will be able to conduct quality
analysis on circuit boards and use machine learning to detect any flaws. In a macroscopic
environment, AI will be used to sense and avoid dangers in the manufacturing and production
environment. Just like self-driving cars, AI will have a huge role in businesses as it will be
able to move materials on its own using conveyors and forklifts (which can self-drive).
Machine sensors will be able to detect obstruction and stop automatically (Nickerson and
Zodhiates 2013). AI will be able to work cooperatively with their human colleagues in the
manufacturing processes. AI and humans will be able to communicate in a common language
that can be anticipated by the programming language of the machine. Moreover, AI will be
able to predict maintenance conditions in the machines with the help of sensors that track the
performance and the operating conditions of the machines. It will also be used to predict
malfunctions and breakdowns and take pre-emptive actions on its own saving time and
money (Cohen and Feigenbaum 2014). The data that will be collected from the embedded
sensors in the equipment will be not used in the manufacturing unit only but also to other
areas of the business such as distributor locations, retail outlets, facilities of the suppliers and
inventories.
In the future, AI will be able to provide subtle hints about predictable demand to
manufacturers before the product manufacturing is started. The AI will be used by
manufacturers to predict stock markets. Sentiment analysis can be conducted by the AI to
predict demand for certain brands and products (Tao et al. 2015). In the present world
scenario, AIs are already being trained by consumers to predict their behaviours with the help
of Amazon Alexa and Google Assistant. With time, the analysis methods in the AI will
improve. Political opinions as well as social media data will be analysed effectively by the
AIs to provide an insight into the consumer’s mind to the manufacturers.

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According to Greg Kinsey, the process of manufacturing will become more about
brains in the future and will involve less utilisation of muscles. Manufacturing businesses will
be able to revolutionise the way they interact with products and ship them (Jeschke et al.
2017). The process of creating something in bulk is receding as consumer’s expectations of
products are evolving. In the future, consumers will be able to scan their feet in a machine for
the shape and size and pick up the shoe later on the same day. In this context, the method of
production in bulk and transporting to other countries seems not feasible.
The businesses will see a drastic reduction in manufacturing costs as the machine
learning of AIs improve with time. Customers will be able to enjoy a wide variety of products
as mass customization in manufacturing will become common. In the future, the first fully
automated application of AI in the manufacturing process will be to get rid of paper based
tasks. The data could be cut down and analysed with AI decreasing the need for human
personnel (Bostrom and Yudkowsky 2014). The production line can be customised with the
help of AIs to make the whole procedure efficient. To conclude, AI will play a huge role in
the future manufacturing processes of businesses if the technology is embraced openly.
Currently, the technology is facing a lot of flak from people as the common misconception
that AIs will lead to losses of jobs keep revolving. Time will tell if AI technology has the
capacity to change how workplaces work or if it is just another technological bubble.

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Impact of Hackers on International Business
The number of cyber-attacks have increased exponentially in the past decade.
International businesses are increasingly adopting cyber security systems to manage this
threat but no security system is currently available that is 100% fool proof from cyber-
attacks.
The potential impact of the hackers on an international business can cost billions of
dollars. Due to globalization and rapid advancement in the digital age, most of the businesses
which are operating have migrated their business functions globally. Businesses which deal
with private user data and banking details are widely targeted by hackers. The reason for
hacking these financial data centres is for identity threat (Taylor, Fritsch and Liederbach
2014). The immediate impact of the attack will be the loss of reputation of the business in the
eyes of its loyal customers. For other international businesses, the interconnected cost can be
enormous and leads to the loss of time for the employees unnecessarily. Businesses which
deal with client information can lose their competitive edge and even lose their entire client
base due to a single instance of hacking. Moreover, from the opposite scenario, hacking can
provide other organisations with valuable information about a client base helping it to get a
leverage in this competitive market. Businesses which have digitized most of their business
functions have to appoint new IT teams and invest in new infrastructures for preventing
cyber-attacks (Smith 2014).
Cyber security firms on the other hand will profit from these attacks and possibly
benefit tremendously due to the hackers. The impact of hackers on international business can
potentially risk their reputation and prevent them from gaining new clients in the future.

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References
Bench-Capon, T.J., 2014. Knowledge representation: an approach to artificial
intelligence (Vol. 32). Elsevier.
Bond, A.H. and Gasser, L. eds., 2014. Readings in distributed artificial intelligence. Morgan
Kaufmann.
Bostrom, N. and Yudkowsky, E., 2014. The ethics of artificial intelligence. The Cambridge
handbook of artificial intelligence, pp.316-334.
Cohen, P.R. and Feigenbaum, E.A. eds., 2014. The handbook of artificial intelligence (Vol.
3). Butterworth-Heinemann.
Jeschke, S., Brecher, C., Meisen, T., Özdemir, D. and Eschert, T., 2017. Industrial internet of
things and cyber manufacturing systems. In Industrial Internet of Things (pp. 3-19).
Kittur, A., Nickerson, J.V., Bernstein, M., Gerber, E., Shaw, A., Zimmerman, J., Lease, M.
and Horton, J., 2013, February. The future of crowd work. In Proceedings of the 2013
conference on Computer supported cooperative work (pp. 1301-1318). ACM.
Michalski, R.S., Carbonell, J.G. and Mitchell, T.M. eds., 2013. Machine learning: An
artificial intelligence approach. Springer Science & Business Media.
Nickerson, R.S. and Zodhiates, P.P. eds., 2013. Technology in education: Looking toward
2020. Routledge.
Nilsson, N.J., 2014. Principles of artificial intelligence. Morgan Kaufmann.
Russell, S.J. and Norvig, P., 2016. Artificial intelligence: a modern approach. Malaysia;
Pearson Education Limited,.

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Smith, P.A. ed., 2014. Impact of Emerging Digital Technologies on Leadership in Global
Business. IGI Global.
Springer, Cham. Strasser, T., Andrén, F., Kathan, J., Cecati, C., Buccella, C., Siano, P.,
Leitao, P., Zhabelova, G., Vyatkin, V., Vrba, P. and Mařík, V., 2015. A review of
architectures and concepts for intelligence in future electric energy systems. IEEE
Transactions on Industrial Electronics, 62(4), pp.2424-2438.
Tao, F., Zhang, L., Liu, Y., Cheng, Y., Wang, L. and Xu, X., 2015. Manufacturing service
management in cloud manufacturing: overview and future research directions. Journal of
Manufacturing Science and Engineering, 137(4), p.040912.
Taylor, R.W., Fritsch, E.J. and Liederbach, J., 2014. Digital crime and digital terrorism.
Prentice Hall Press.
Vasant, P., 2015. Handbook of Research on Artificial Intelligence Techniques and
Algorithms, 2 Volumes. Information Science Reference-Imprint of: IGI Publishing.
Zhou, K., Liu, T. and Zhou, L., 2015, August. Industry 4.0: Towards future industrial
opportunities and challenges. In Fuzzy Systems and Knowledge Discovery (FSKD), 2015
12th International Conference on (pp. 2147-2152). IEEE.