Griffith University: Future Automation Workforce Analysis

This report delves into the critical topic of preparing the workforce for the future of automation. It begins by outlining the transformative impact of automation and artificial intelligence (AI) on businesses, economies, and societies, highlighting the opportunities and challenges that arise. The report explores the effects of AI and automation on work, including workforce transitions and potential job displacement, while also acknowledging the simultaneous creation of new job roles. It emphasizes the importance of reskilling and upskilling the workforce to adapt to these changes, especially in emerging and developing economies. The report discusses the challenges and strategies for workforce transition, including the need for advanced digital and technological skills and the shift in skill demands. It analyzes the impact of automation on emerging and developing economies, such as India and China, highlighting the need for vocational training, foreign direct investment, and effective handling of potential unemployment. Furthermore, it examines the readiness of the current and future workforce to embrace technological advancements and the importance of government support. The report concludes by emphasizing the need for nations to support their workforce in adapting to the digital environment, showcasing the ongoing transformation in the way we work and earn a living.

PREPARING THE WORKFORCE FOR
FUTURE AUTOMATION
STUDENT NAME

TOPICS OF DISCUSSION
■ Automation and AI (Artificial Intelligence)
■ Accelerating progress in automation: opportunities for business, economy and
society
■ AI and Automation: effect on work
■ Key workforce transition and possible challenges
■ Reskill and upskill of workforce
■ Discussion with the help of emerging and developing economies
■ Is the workforce ready?

AUTOMATION AND AI
■ Talent management is an important concern for strategic business leaders in an
organization which is worth 55% (approx.) of total marketing budget of an
organization (Acemoglu and Restrepo 2018). In this regard, AI and Intelligence
Automation has proved remarkable in transforming business processing and
workforce management.
■ Automation has build the right synergy in bridging the gap in between talent
and technology. Machine learning is the new trend of the present Globalized
world (Chui, Manyika and Miremadi 2015).
■ Automation is a task-driven imperative with a single purpose: to involve
machine in the repetitive tasks of the humans which they don’t want to do or
are important to them to perform (Chui, Manyika and Miremadi 2016).
Automation mixed with AI support increase efficiency of output, saves time and
support corrective decision-making.
■ Automation performs calculation, improves communication, runs machinery,
assembles products and supports value added services (David 2015).

ACCELERATING PROGRESS IN AUTOMATION:
OPPORTUNITY FOR BUSINESS, ECONOMY AND SOCIETY
■ Automation technology has improvised value creation in products and
services where companies are using automation holistically to
personalize recommendations of products, find out production
anomalies and identification of fraudulent transactions. As a result of
this value addition, economic growth have widened up manifold
(Dubin 2017).
■ The impact of automation (specially AI) has been a boon for medical
research to sciences of climate change. Societal challenges are
effectively solved by process automation through Intelligent
Automation (Frey et al. 2016).
■ Automation is the ‘Fourth Industrial Revolution’ which have
fundamentally altered all sectors of living be it work or social
environment. The entire systems of production, management and
governance have been transformed by the breakthrough of this
disruptive automation (Hajkowicz et al. 2016).

AI AND AUTOMATION: EFFECT ON WORK
■ People analytics is the new technological advancement in current business
world (Noble 2017). Though Automation has a number of benefits but its
disruptive nature will have significant impact on the current workforce.
■ Some activities are there that are labor incentive and some are machine
incentive. Most of labor incentive activities are easily automatable but
recent data statistics show that among the automated occupations only 5%
can be fully automated (Rübmann et al. 2015) . Other occupations are of
larger proportion which are a mixed of process and people automation.
■ But it is to be noted that in near future automation will displace majority of
workers. Global data survey results show that around 15% of global
workforce that is about 400 million workers can be displaced in the period
of 2016-2030 (Smith and Anderson 2014). Thus the impact of automation
will be far reaching in consideration to global workforce.
■ But in spite of worker displacement, jobs will also be created at the same
time as demand for work will increase and so is the demand for
consequent jobs.

CONTINUED…
■ A data survey result is shown where possible impact of automation on global
workforce is identified.
(Smith and Anderson 2014)
Automation and global
workforce
Description Data statistics
Potential of technical
automation
50% of current work activities
are automatable
6 out of 10 occupations have 30% of activities
which are technically automatable.
Impact of adaptation by 2030 Potential work displacement by
adaptation of automation
Slowest 0% (10 million)
Mean 15% (400 million)
Fastest 30% (800 million)
Workforce change need for
occupational category
Slowest 0% (less than 10 million)
Mean 3% (75 million)
Fastest 14% (375 million)
Impact of demand for work
by 2030
Trend line demand
Step-up demand
Total
Low 15% (390 million) and high 22% (590 million)
Low 6% (165 million) and high 11% (300 million)
Low 21% (555 million) and high 33% (890 million)

KEY WORKFORCE TRANSITION AND POSSIBLE
CHALLENGES
■ In this regard it is to be noted that, job changes will be much
prominent in comparison to job gain or loss.
■ Partial automation will be more prevalent where machines will
complement human labor in workplaces.
■ Repetitive job tasks will have higher risk of automation.
■ To ensure full employment by 2030, it is important to accompany the
significant Automation transition at large. As a result of which,
occupational mixes will change and so is the skill and qualification
requirement for the job role (Smith and Anderson 2014).
Redesigning of work structure will be prominent where scope of
humans and machines working together will rise significantly.
■ Demand for advanced digital and technological skills will increase
whereas demand for physical and manual skills will decline
considerably (Dubin 2017).

CONTINUED…
■ Also social and emotional skill improvement
will be prominent where higher cognitive
skills like critical thinking, creativity and
complex information processing will also
have rising demand (David 2015).
■ As a result of this increase of shift in skill
demand, there will be increased challenge
for the existing workforce skills and
challenge will also be in areas of new
system credentialization (Dubin 2017).
■ The data statistics mentioned here shows
the shift in skill requirement and workforce
needs (2016 vs 2030).
(Noble 2017)

CONTINUED…
■ As a result of this shift there will be major challenges in
areas of occupational changes, change in workplace
culture and workflows, training and development needs
of workforce, increased pressure on average wage
structure in advanced economies, dislocation effect on
workers and will also enhance the so called
phenomenon of ‘Engel’s Pause’ where wages remain
stagnant despite rising productivity (Noble 2017).
■ The race of survival of the fittest has already started
and a maximum part of future ready workforce is
already here as modern businesses have learnt well that
the age of automation has arrived and is here to stay
(Smith and Anderson 2014). So, instead of defending
one’s stand it is recommendable to adopt to the changes
resulted from automation in future of work.

RE-SKILL AND UP-SKILL OF WORKFORCE
■ Reskilling is training the existing employees and workforce to cope
up the future talent needs. It is at times called the ‘reversal of
fortune’ where workers are provided one more chance to prove
their caliber in this changed work environment (Smith and
Anderson 2014). Reskilling is most cost-effective to the
organization as it reduce uncertainties of new talent management.
■ By 2030 there will be a major shift from agricultural work
environment to manufacturing ones. Up-skilling will meet the
urgency of enterprise wide transformation in the most efficient
manner and potential skill gaps will be addressed at large
(Acemoglu and Restrepo 2018).
■ Most organizations keep workforce re-skilling and up-skilling as
one of their top 10 priorities in this age of advanced automation. In
this regard, a strong and robust HRM support is mandatory (Dubin
2017).

DISCUSSION WITH THE HELP OF EMERGING AND
DEVELOPING ECONOMIES
■ The advancement of technological automation has a strong multiplier effect in
increasing level of unemployment in both emerging and developing countries
(Dubin 2017).
■ Most emerging economies like India will be adversely affected by incorporation of
automation in core work structure. The impact will be prominent in the
transitional stages. In China, as well the wage and growth of employment have
been subdued (Chui, Manyika and Miremadi 2016).
■ The emerging economies of India and China, need to focus more on workforce
reskilling so that displacement cases can be handled tactfully.
■ Social unrest, retarded growth and unemployment has increased adversity in
growth of economies, mainly in areas of off-shoring and outsourcing resource
programs, in countries like India and China (Chui, Manyika and Miremadi 2016).
■ Importance on vocational training and development factors will improve the skill-
set of workforces to a considerable amount. Focus on FDI (Foreign Direct
investment) will increase scope of multi-nationalization (Acemoglu and Restrepo
2018).

CONTINUED…
■ In developing economies like Bangladesh and Philippines , the Government plays major role in
re-skilling and up-skilling the workforce to face the socio-economic impacts of automation to a
greater extent.
■ Robotics is used as an alternative of off-shoring in these developing countries that help in limited
operational cost involvement and enhance production of high quality goods and services in an
optimized time frame (Acemoglu and Restrepo 2018).
■ The wave of change in automation and AI has increased ‘home coming’ of a number of big
overseas corporations and there is a steady business environment change in those organizations
(David 2015).
■ Chances of uncoupling of human resources in organizations have increased as a result of
automation and there is high chances of destruction of current jobs and creation of new ones
(David 2015). In this regard, the nations with educated and skilled workforce will have
competitive advantage and lower labor cost will add to the advantages.
■ Reengineering and standardized software platform will increase aspects of offshoring from
developed countries like UK, USA and Australia. China and India have been benefitted from such
IT revolution effectively (Acemoglu and Restrepo 2018). Also, due to limited job opportunities in
native countries like Bangladesh increased labor force are taking active participation in
offshoring by developed countries and this is resulting in huge brain drain.
■ This ‘brain drain’ is limiting the level of socio-economic growth and development in those
emerging and developing nations to a great extent (Acemoglu and Restrepo 2018). This,
enhances the importance of re-skilling and up-skilling of labor force .

CONTINUED…
■ One of the major negative impacts of automation in emerging
countries is unemployment and China and India will surely feel the
heat of it (David 2015). Automation will improve productivity in the
most sustainable manner.
■ Reskilling and upskilling of the labor force will improve their
adaptability and help them survive in a complex environmental
scenario (David 2015). Academic skill upgradation is the founding
factor of improved workforce support.
■ It is also to be noted here that an increased number of current
employees and graduates have skills that do not match the job market
requirement. As a measure to reduce the wastage of their skills they
need to be reskilled and upskilled through training so that they can
make them equipped with the most required and demanding skills of
the present job market (Smith and Anderson 2014).
■ Third world economies need to focus more on capital support in their
decision- making, so that automation can only be beneficial to such
emerging and developing economies.

IS THE WORKFORCE READY?
■ The future workforce is already ready, now it’s the turn of the nations to support them
holistically. Today’s business have already adopted AI, machine learning and IoT in their daily
operations and people analytics is firmly embedded in their roots.
■ The next 10 years will show exponential growth and turnover in use of IT and process
automation (Smith and Anderson 2014). Every aspect of lives will be part of the change and the
most important of all the way and approach of work will be the most affected one.
■ Current workforce is much tech savvy than they were a year ago and are trying their level best to
cope up with the digital environment. The advent of ultra digital work force is here to both
succeed and compete (Smith and Anderson 2014).
■ One area that remained under scrutiny is that ‘will robots eventually take the job of the
workforce in near future?’ well, the obvious answer is not yes but still to a great extent it could
be said that yes it might replace humans to a considerable extent in future.
■ In this regard it could be mentioned that from horse to horse power, from radio to TV, from type
writer to computer all revolutions were purposeful which gave rise to new jobs and new ways of
earning a living (Smith and Anderson 2014). What is important here is that, humans being adopt
to the chances in the most effective and efficient manner.
■ So, in this next wave of innovation the humans will definitely succeed and so are the future
workforce of e-businesses. Jobs where more empathetic skills are required (teaching and
learning) are less likely to be replaced by automation and robots (Dubin 2017).
■ Thus, it could be said that, automation is a double edged sword where, elimination of one task
will give rise to a more productive task and workers will be able to do more meaningful task in
future.

CONCLUSION
■ Thus to conclude, it could be said that in order to tackle the impacts
of automation the businesses need to ensure robust economic
growth, foster increased business dynamism, evolve system of
education and learning to support workplace changes, invest more in
human capital, improve labor-market dynamism, redesign work-
rethink income, develop workplace safety and security, increased
drives for work demands and last but not the least should embrace
automation and AI in a safe and optimum manner.
■ There is work for everyone today and there will be tomorrow even in
this automation future world. It is true that the work will be different
and skill requirement will vary. Need for increased workforce
adaptability will be required where integrated and collaborative
human capital investment scope will widen up (Dubin 2017).
■ Therefore, the automation future will be challenging for the
workforce but will be much richer if technology is harnessed with
aplomb in mitigating negative outcomes significantly.

REFERENCES
■ Acemoglu, D. and Restrepo, P., 2018. Artificial intelligence, automation and work (No. w24196). National Bureau
of Economic Research.
■ Chui, M., Manyika, J. and Miremadi, M., 2015. Four fundamentals of workplace automation. McKinsey
Quarterly, 29(3), pp.1-9.
■ Chui, M., Manyika, J. and Miremadi, M., 2016. Where machines could replace humans—and where they can’t
(yet). McKinsey Quarterly, 30(2), pp.1-9.
■ David, H., 2015. Why are there still so many jobs? The history and future of workplace automation. Journal of
economic perspectives, 29(3), pp.3-30.
■ Dubin, R., 2017. The world of work: Industrial society and human relations. 1st ed. Routledge: London.
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Chalif, P., 2016. Technology at work v2. 0: The future is not what it used to be. CityGroup and University of Oxford.
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digitally enabled workforce: Megatrends and scenarios for jobs and employment in Australia over the coming
twenty years. Australian Policy Online.
■ Noble, D., 2017. Forces of production: A social history of industrial automation. 1st ed. Routledge: London.
■ Rübmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P. and Harnisch, M., 2015. Industry 4.0: The
future of productivity and growth in manufacturing industries. Boston Consulting Group, 9(1), pp.54-89.
■ Smith, A. and Anderson, J., 2014. AI, Robotics, and the Future of Jobs. Pew Research Center, 6.