Preparing for an AI-Powered Future: Companies Embrace Advanced Technology

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This article discusses how companies are preparing themselves for an AI-powered future workforce and the impact of advanced technology on business operations. It also explores the potential benefits and challenges of AI integration in various industries.

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Running head: MANAGING PEOPLE AND ORGANISATIONS
MANAGING PEOPLE AND ORGANISATIONS
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1MANAGING PEOPLE AND ORGANISATIONS
Introduction
In the two centuries since the Industrial Revolution, technological change has
continuously reshaped companies and its workforce. Nevertheless, in recent times the pace of
that change has rapidly accelerated with the development of new automation technologies driven
by Artificial Intelligence (AI) (Samson, Donnet & Daft, 2018). These technologies are changing
the way individuals work and further altering association with work (Davenport & Ronanki,
2018). Reports of Wilson, Daugherty and Bianzino (2017) have revealed that overall expenses
on technology expand and further will create millions of new innovative jobs by opening up
extensive areas of work related to marketization of formerly unpaid domestic work as well as
work in developing industrial sectors such as climate adaptation. The following paper will
critically analyse a recently published news article on the Financial Review about the way
companies currently are preparing themselves for an Artificially Intelligent future workforce.
Additionally, it will draw relevance to this particular news article with other scholarly papers to
obtain inclusive insights on this subject.
Discussion
The recently published news article on Financial Review on Artificial Intelligence by
James Eyers in March, 2019 has revealed that the Qantas Airways, renowned flag carrier of
Australia with its operations at Mascot has been performing with operation controllers, cabin
crew representatives, team of engineers and meteorologists (Eyers, 2019). Through their use of
AI every Qantas plane in every region in the world can be located on their databases.
Furthermore, the report has mentioned that emergence of advanced technology has been
allowing machines to critically identify patterns and obtain insights by generating substantial
amount of data.
However, drawing relevance to this news article, Hill, Ford and Farreras (2015)have
claimed that modern businesses in order to successfully thrive in the future of advanced work,
will require operating in accordance to AI. While, comprehensive studies of Doshi, Pawar,
Shelar and Kulkarni (2017) have mentioned that while certain challenges related to the influence
of AI and automation on jobs. Artificial intelligence do not essentially rely on replacing humans,
rather they emphasize on amplifying skills and optimizing jobs in addition to successfully
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2MANAGING PEOPLE AND ORGANISATIONS
creating greater avenues for jobs. For example, it has been noted that AI will successfully
provide employees with adequate time to execute tasks which are accurately suited to humans
related to complex problem-solving approaches, critical analysis along with creativity and
innovation. Additionally, as per Mc Kinsey by 2030, robotics and AI will perceive human jobs in
less than 5% if roles. Moreover, on the other hand, it has been mentioned that advanced
technology will develop 65% of job opportunities rather than displacing humans from workforce
(Eyers, 2019).
Meanwhile, the news article explicitly mentions that advanced technology has been
driven by radical growth in the organized data sets, along with rapid technical expansion in
algorithms as well as inexpensive and ubiquitous computing power (Eyers, 2019). In recent
times, when businesses speak about AI as a disruptive element, they primarily shed light on the
branch of AI which is identified as deep learning. According to Doshi, Pawar, Shelar and
Kulkarni (2017), it is deep learning algorithms that permit certain types of chatbots to enquire
and respond to queries, vehicles to learn how to drive in addition to companies like Facebook to
strategically develop refined and advanced image recognition software.
Similar insights have been shared by author in the news article whereby it mentions ways
in which Qantas has recently designed a new bespoke system known as Constellation by
collaborating with the University of Sydney’s Australian Centre for Field Robotics (Eyers,
2019). Thus, by influencing power by integrating cloud computing, such a bespoken system will
be able to assess substantial rate of routes by strategically modelling huge amount of data points
in order to determine the best flight pathway on the basis of aircraft means and weather
limitations. Eyers (2019) has incorporated the response of Qantas Chief Executive of an
interview who revealed their plan of integrating AI automation in order to aid its customers,
technology as well as development. As per reports of Nadimpalli (2017), it has been noted that
the company has been essentially planning using a huge database of around 10 years of weather
patterns in order to distinguish optimal flight plans which have the capacity to augment the
journey duration and thus embrace AI to smoothen their operations.
Meanwhile, on the other side, the news article has revealed that only 9% of Australian
business enterprises are viewed as important establishments of AI technology. Such a low rate of
of AI establishments in Australia has been estimated to be half of the American companies who
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3MANAGING PEOPLE AND ORGANISATIONS
have been proficiently using AI into their businesses (Eyers, 2019). At this juncture, Murashov,
Hearl and Howard (2016) in their study have observed a significant prospect for Australia in
successfully adapt a collaborative approach between start-ups businesses, academic world as
well as government which can further pave the way for the ethical use of AI. Similarly, Eyers
(2019) in the news article has claimed that the increasing level of AI flourishing significantly in
the domain of consumer devices such as voice-regulated assistants as well as Smartphone
applications with AI systems being increasingly used in global businesses ranging from
diagnosing disease to allocating credit, there can be witnessed a considerable chance for
Australia to successfully enhance their business sector by integrating AI into business.
Furthermore, Eyers (2019) has projected a rise of around $ 56 million in 2021 from $ 12
million in the area of global costs on AI as the number of machine learning pilots as well as
implementations will elevate significantly from 2019 to 2020. Simultaneously, new
organizational structures with flexible working patterns, the gradually extensive international
talent pool along with multi-generational labour force will contribute to the challenges as well as
demand levels of managers as well as workforce (Murashov, Hearl & Howard, 2016). Thus, in
order to arrange for the AI revolution, companies will require expertise to develop as highly
data-driven and further will use advanced technologies to enhance essential working practices.
At this juncture, Eyers (2019) has drawn relevance to this increased use of AI which has enabled
other business apart from Qantas to strategically co-ordinate new, advanced as well as data led
strategy with AI systems at the core of the business. Such an implementation will help these
companies to reduce risks factors of workplace injuries.
Asaro (2016 has cited examples of Cisco and Cortexica Vision Systems Ltd. These
companies have collaborated with other organizations to reduce human error in physical
wellbeing and recuperating productivity. Additionally, it has been noted that AI in prospective
days will be integrated in diverse businesses in order to reduce rates of human error in physical
safety in workplaces such as operating theatres, laboratories as well as construction sites.
Moreover, companies will be strategically using instantaneous and real time video analysis
which will help their business to authorize accurate and appropriate equipment been used in a
physical work environment to endorse safe, welfare and security of all employees.

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4MANAGING PEOPLE AND ORGANISATIONS
The news article has explicitly mentioned companies like Worley Parsons along with
Qantas in Australian has introduced a new product in the market known as Salt-Grid which
scrutinizes historical data of safety performance on its company website (Eyers (2019). Such
advanced software has the ability to predict areas of threats and risks for activities for
forthcoming days. According to Leikas, Koivisto and Gotcheva (2019), this type of AI will not
only help managers in identifying areas of risks but also help in avoiding them. Meanwhile, the
news article further mentions the role of AI in recruitment sector which has facilitated the use of
assessing CVs and further identifying the right talent for the right job role. Thus, several
companies recently have started using this technical expertise by incorporating some search
online as well as in databases for matching candidates, strategically filtering through several job
applications and further using machine learning.
However, Fernández-Macías, Gómez, Hernández-Orallo, Loe, Martens et al. (2018)have
noted that with the rapid pace in which business style in management has shifted from big data to
machine learning to artificial intelligence has been outstanding and will lead to greater number of
job opportunities. Furthermore, the energy sector has been highly dynamic in the investment of
AI. At this juncture, power utilities have been seeking AI to successfully alleviate the grid as
renewable into the system and further to accomplish projecting analytics for equipment
breakdown and malfunction (West, 2018). These achievements have led resources companies to
strategically integrate AI in order to regulate automated fleets of vehicles as well as processing
plants.
Conclusion
Therefore, from the above discussion it can be concluded that AI is speedily altering
business operations ranging from digital assistants to robot contemporaries. Moreover, parallel to
the Industrial Revolution previous to this, modern businesses will require preparing their
workforce to adapt as well as thrive in the prospect of work. Furthermore, AI should not be
viewed as something to be stressed upon. However, it is important to apply essential movement
to drive businesses into the next age in which advanced technology can advance the lives of
individuals, businesses along with the wider society.
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5MANAGING PEOPLE AND ORGANISATIONS
References
Asaro, P. M. (2016, March). The liability problem for autonomous artificial agents. In 2016 AAAI
Spring Symposium Series. Retrieved from
https://www.aaai.org/ocs/index.php/SSS/SSS16/paper/viewFile/12699/11949
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard business
review, 96(1), 108-116. Retrieved from
https://www.kungfu.ai/wp-content/uploads/2019/01/R1801H-PDF-ENG.pdf
Doshi, S. V., Pawar, S. B., Shelar, A. G., & Kulkarni, S. S. (2017). Artificial Intelligence Chatbot in
android system using open source Program-O. International Journal of Advanced Research in
Computer and Communication Engineering. DOI10.17148/IJARCCE.2017.64151
Eyers. J., (2019). Companies Prepare For an AI-Powered Future, Financial Review. Retrieved from
https://www.afr.com/technology/companies-prepare-for-an-aipowered-future-20190315-h1cegr
Fernández-Macías, E., Gómez, E., Hernández-Orallo, J., Loe, B. S., Martens, B., Martínez-Plumed, F.,
& Tolan, S. (2018). A multidisciplinary task-based perspective for evaluating the impact of AI
autonomy and generality on the future of work. arXiv preprint arXiv:1807.02416. Rerieved from
https://arxiv.org/pdf/1807.02416.pdf
Hill, J., Ford, W. R., & Farreras, I. G. (2015). Real conversations with artificial intelligence: A
comparison between human–human online conversations and human–chatbot
conversations. Computers in Human Behavior, 49, 245-250.
http://dx.doi.org/10.1016/j.chb.2015.02.026
Leikas, J., Koivisto, R., & Gotcheva, N. (2019). Ethical Framework for Designing Autonomous
Intelligent Systems. Journal of Open Innovation: Technology, Market, and Complexity, 5(1), 18.
doi:10.3390/joitmc5010018
Murashov, V., Hearl, F., & Howard, J. (2016). Working safely with robot workers: Recommendations
for the new workplace. Journal of occupational and environmental hygiene, 13(3), D61-D71.
doi: 10.1080/15459624.2015.1116700
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Nadimpalli, M. (2017). Artificial intelligence risks and benefits. Artificial intelligence, 6(6). Retrieved
from https://www.researchgate.net/profile/Meenakshi_Nadimpalli2/publication/
319321806_Artificial_Intelligence_Risks_and_Benefits/links/59a47dd20f7e9b4f7df37ab9/
Artificial-Intelligence-Risks-and-Benefits.pdf
Samson, D., Donnet, T., & Daft, R. (2018). Fundamentals of Management [6th Asia-Pacific Edition].
Cengage. Retrieved from https://eprints.qut.edu.au/121574/
West, D. M. (2018). The future of work: robots, AI, and automation. Brookings Institution Press.
Retrieved from http://www.insidepolitics.org/Preface.pdf
Wilson, H. J., Daugherty, P., & Bianzino, N. (2017). The jobs that artificial intelligence will create. MIT
Sloan Management Review, 58(4), 14. Retrieved from
http://ilp.mit.edu/media/news_articles/smr/2017/58416.pdf
Yeow, J. A., Khan, M. K. B. J., & Ng, P. K. (2017). Enforcement of Safety and Health Policy Reduces
Human Error in SMEs in the Manufacturing Industry. Advanced Science Letters, 23(11), 10656-
10659. Retrieved from
https://www.researchgate.net/profile/Poh_Kiat_Ng/publication/316963547_Enforcement_of_Saf
ety_and_Health_Policy_Reduces_Human_Error_in_SMEs_in_the_Manufacturing_Industry/
links/591a943f0f7e9b1db652aecd/Enforcement-of-Safety-and-Health-Policy-Reduces-Human-
Error-in-SMEs-in-the-Manufacturing-Industry.pdf
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