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ARTIFICIAL INTELLIGENCE AND ITS IMPACT ON FUTURE WORK AND JOBS
By Marion Kokel
Abstract
This essay is a first attempt at exploring Artificial Intelligence (A.I.) and its growing impact on our
modern societies. It voluntarily takes the form of an interdisciplinary opinion essay that is aimed
at investigating A.I., its impact on jobs and at developing its potential benefits on the economy.
This analysis also includes a country case study of the UAE in relation to our topic.
Introduction
Artificial intelligence “is the opportunity of our time, and skills are the issue of our time. 100
percent of jobs will be augmented by #AI.”1 - Ginni Rometty, IBM CEO for the NYTimes
For more than two centuries, technological innovations have been the drivers of our economies.
The First Industrial Revolution had its steam engine, the Second Industrial Revolution mobilised
electricity for mass production and the Third Digital Revolution, which started in the middle of
the last century, uses digital electronics to automate production2.
According to Professor Klaus Schwab, Founder and Executive Chairman of the World Economic
Forum, a 4th industrial revolution is on its way (see Annex 1): “the evidence of dramatic change is
all around us and it’s happening at exponential speed”3. The world is at the cutting edge of new
technologies that are expected to revolutionise people’s lives: robotics, computer algorithms and
A.I. are expected to alter the world as we know it and change the way we live. Our modern
societies – businesses, governments and the civil society alike – are experiencing the
unprecedented effects of the acceleration of innovation, as well as the velocity of disruption4.
A.I. has long stayed within the realm of science fiction, but has recently crept up the political
agenda. A.I. technologies seem to be a priority discussion these days; this was especially the case
at the 2018 World Economic Forum Annual Meeting in Davos earlier this month.5 In most studies
and discussions worldwide, attention is centred on the future of work and the job market.
Robots, automation, and A.I. are disrupting jobs and expected to increasingly replace people in
the workplace. For many world-experts (including Prof. Schwab), collaboration on a global scale
is and will remain key, in order to tackle the challenges and grasp the opportunities offered by
A.I. – ie.to avoid inequalities, insecurity, governmental, and organisational failure6.
Programmed devices performing human work arouse fear but also a lot of interest for its
promising potential. Both an ideological and a technological phenomenon, A.I. is expected to have
an important impact on our world economy. This paper aims to cast a new light on the future of
1
FRIEDMAN, Thomas L., “While You Were Sleeping”, NYTimes, Opinion, 16 January 2018,
https://www.nytimes.com/2018/01/16/opinion/while-you-were-sleeping.html?linkId=47079031
2
SCHWAB, Klaus, “The Fourth Industrial Revolution: What it Means, How to respond”, WEF, Global Agenda, 14 January
2016, https://www.weforum.org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-to-respond/
3
“The Fourth Industrial Revolution, by Klaus Schwab”, WEF, https://www.weforum.org/about/the-fourth-industrial-revolution-
by-klaus-schwab
4
SCHWAB, Klaus, “The Fourth Industrial Revolution: What it Means, How to respond”, op. cit.
5
See https://www.weforum.org for more information
6
“World Economic Forum 2018 to Call for Strengthening Cooperation in a Fractured World”, WEF, 20 September 2017,
https://www.weforum.org/press/2017/09/world-economic-forum-2018-to-call-for-strengthening-cooperation-in-a-fractured-
world/

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jobs and skills through the lens of A.I.. We will research and analyse how this technological
megatrend could potentially shape the job market and our economies. Is it possible to predict
how A.I. will redefine work and the labour market 15-years from now? The thesis we would
like to defend in this article is that the development of A.I. systems and applications will result in
faster growth and rising employment.
Methodology
There are many interesting variables and sources of information that can be used to produce
forecasts on the potential future of A.I.. These variables and sources include, but are not limited
to expert surveys, prediction markets, extrapolation of historic models, analogy with other
developments, group forecasting methods (e.g. Delphi method) and building complex models,
etc.7
For this study, we collected and combined various data sets, literature reviews and methods for
better accuracy. The added value of this paper lies in the aggregation of a set of indicators and
metrics comprising notably expert reviews, extrapolation, forecasting and prediction markets.
To structure this article we will proceed in four steps. First, in order to understand the way in
which way A.I. is shaping our economy, we must develop a comprehensive view of what this
technology is about. The second chapter will elaborate how this phenomenon is affecting our
economies and job market and why we believe it does so in a favourable way. The third chapter
focuses on proposed milestones and solutions to prepare for the future of the labour market. The
fourth chapter reflects back on the previous findings with a focus on the United Arab Emirates
(UAE), the first government to appoint a State Minister for A.I.. Finally, a summary of conclusions
highlights the main takeaways for each point.
I. The Case for A.I.
The neologism “Artificial intelligence” (A.I.) was invented by John McCarthy in 1955. Since then,
many authors and researchers have been using these words to describe a very promising field of
study. Yet, there are several definitions of A.I. and what it consists of, for experts and the man in
the street are using the term interchangeably. For the purpose of this essay, we will use a
generalist definition focusing on A.I. as « the field that studies the synthesis and analysis of
computational agents that act intelligently »8. In other words, this means we are moving into an
era of robotisation and automation, where machines work intelligently and are sharing some
qualities of the human mind.
We choose not to focus on the potential pitfalls of A.I. given the time-constraint. This essay
strongly defends the idea that A.I. will shape our modern societies in an unprecedented way.
While we do believe this technology to be in its hype cycle, we are convinced of its long-term
impact on the market, alongside other related technologies such as machine learning, virtual
reality, blockchain or quantum computing9.
“The technology hype cycle for a paradigm shift – railroads, A.I., Internet, telecommunications,
possibly now nanotechnology – typically starts with a period of unrealistic expectations based on a
7
“A Survey of Research Questions for Robust and Beneficial A.I.”, Future of Life Institute, 34p., p. 23,
https://futureoflife.org/data/documents/research_survey.pdf
8
POOLE, David L., MACKWORTH, Alan, K., Artificial Intelligence. Foundations of Computational Agents, Cambridge
University Press, Second ed., 820 p., p.5.
9
SCHMIDT, Adrien, “How Does A.I. Measure Up to Other Tech Trends on The Gartner Hype Cycle?”, Forbes, YEC, 30
October 2017, https://www.forbes.com/sites/theyec/2017/10/30/how-does-ai-measure-up-to-other-tech-trends-on-the-gartner-
hype-cycle/#613aca603a5c

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lack of understanding of all the enabling factors required”10. As a rule of thumb, new technologies
follow a parabolic type of pattern, a visual representation of an innovation’s market perception.
In the early stage, it will form an upward trend linked to the market’s high expectations; this will
in turn trigger a peak of interest – or inflated expectations – before engaging in a period of
disillusionment to eventually reach a plateau of productivity that drives future innovations (see
Annex 2)11.
At the moment, it seems this curve applies well to the A.I. phenomenon at the moment. Although
many companies heavily invest in this promising sector to develop A.I. products and tangible
applications, many documents currently showcase A.I. buzzwords with little specific content.
Based on this recurring human reaction to emerging technologies, we might therefore experience
a period of disillusionment in the coming years, where A.I. should still be a field to focus on for
many research studies and businesses, but will have lost centre stage to the profit of other
innovations.
We can draw an analogy with what already happened back in the early 80s, when the field
pivoted and transitioned to the commercial realm before sinking into oblivion in the late 90’s12.
There was an initial period of excitement linked to new A.I.-expert systems and applications,
which later cooled down once companies realised they were lacking skills and resources to
succeed. This decade paved the way to an “A.I. winter”, where the technology was set aside and
forgotten until recently13.
Hype cycles tend to repeat themselves, but some innovations will stand the test of time. We
believe this the case of A.I.. There is a clear difference between innovative systems with genuine
substance experiencing early setbacks and “weak”, or worse, failed technologies that were
discarded for good. Rodney Brooks, A.I. Intelligence Lab Director for the MIT already stated in
2002 that the idea that A.I. failed, is a myth, since we are surrounded by A.I. on a daily basis:
“People just don’t notice it.”14.
It is precisely because A.I. is a mega-trend that future widespread adoption of the technology is
more than a probability today. Computational advances and making machines smarter does not
belong to science fiction anymore, but is rather a matter of labelling. Ray Kurzweil, a famous
computer scientist and one of the world’s leading inventors, wrote: “an underlying problem with
artificial intelligence that I have personally experienced in my forty years in this area is that as soon
as an A.I. technique works, it’s no longer considered A.I. and is spun off as its own field (for example,
character recognition, speech recognition, machine vision, robotics, data mining, medical
informatics, automated investing).”15
The renewed interest for the sector and exceptional progress made in the last several years in
terms of computational power, data origination activities and advances in deep neural networks
show a promising future for A.I., and therefore our economies16. Google’s CEO, Sundar Pichai
came up with a bold statement at this year’s Davos summit, stated that “A.I. will be bigger than
10
KURZWEIL, Ray, When Humans Transcend Biology. The Singularity is Near, London, Duckworth Publishers, 2008, 368 p.,
p. 263.
11
PANETTA, Kasey, “Top trends in the Gartner Hype Cycle for Emerging Technologies, 2017”, Gartner, Trends, 15 August
2017, https://www.gartner.com/smarterwithgartner/top-trends-in-the-gartner-hype-cycle-for-emerging-technologies-2017/
12
FENN, Jackie, MARK, Raskino, Mastering the Hype Cycle: How to Choose the Right Innovation at the Right Time, Gartner
Inc., Boston, Harvard Press, 2008, 272 p., p. xii.
13
ibid., p. xii.
14
MIT Technology Review, “Lord of Robots”, Technology Review, 1 April 2002,
https://www.technologyreview.com/s/401409/lord-of-the-robots/
15
KURZWEIL, Ray, When Humans Transcend Biology. The Singularity is Near, London, Duckworth Publishers, 2008, 368 p.,
p. 286
16
BRENDEN, M. Lake, TOMER, D. Ullman, TENENBAUM, Joshua B., GERSHMAN, Samuel J., “Building Machines That
Learn and Think Linke People”, in Behavioural and Brain Sciences, vol. 40, CBMM, NYU, 58p., p. 2-5.

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electricity or fire”, acknowledging that the benefits for humanity would far outweigh the extreme
risks17.
Extending Moore’s law on exponential growth and the curve of new technologies to A.I.,
mainstream adaptation seems to be the next logical stage of its development: “ubiquity becomes
the next step”18. Pinpointing where A.I. will be in 15 years from now seems a lot more
complicated. Experts and researchers agree this technology will create a new market space
requiring a redefinition of jobs and skills. “The technology (…) has the potential to create a multi-
billion dollar human augmentation market”19.
II. A.I. as a Source Of Job Creation
This chapter focuses on the composition of work in the economy with regard to the on-going
mechanisation and automation of jobs. Current findings and future prospects are discussed on
the premise that A.I. is not an ephemeral trend, but a credible source of economic growth and job
creation.
Indeed, we refute predictions about long-term technological unemployment. Academic literature
on the topic is very abundant and unequivocal. The phenomenon is vastly overrated: except for
temporary unemployment and labour displacement caused by the sudden introduction of
machinery or external factors, there is no proven causal link between long-term unemployment
and technology. “… technological advance will continue to improve the standard of living in many
dramatic and unforeseeable ways. (…) The law of comparative advantage strongly suggests that
most workers will still have useful tasks to perform even in an economy where the capacities of
robots and automation have increased considerably”.20
Innovation, the introduction of machinery and pioneering techniques are usually introduced on
the market to improve productivity and efficiency, at lesser costs. The market can thereby
experience positive externalities such as the creation of job opportunities in newer or different
sectors of the economy. Permanent job destruction should therefore not be of concern, as history
shows there is empirical evidence supporting this assumption.
In effect, unemployment concerns were already present in 1412. The city of Cologne prohibited
the construction of a spinning wheel by a local merchant because it feared this would affect the
activities of local spinners. In the 16th century, ribbon-weaving machines were banned in large
parts of Europe in the same attempt to save jobs. Not only did the “imposition of technology bans
(…) proved counterproductive in the long run.”21, but technological progress in the textile industry
also never induced employment loss in the long-term. It is therefore safe to argue that industrial
revolutions, globalisation and trade affected the composition of employment along the way, but
not to the extent that it would sustain long-term unemployment.
There are nevertheless doomsday scenarios à la Professor Stephen Hawking, where A.I. would
soon be so powerful that it could not only take our jobs, but wipe out mankind22. In this regard, it
is worth noting that we have a negativity bias. The human brain pays ten times more attention to
17
PARKER, Ceri, “Google CEO – AI will be bigger than electricity or fire”, WEF, Global Agenda, 24 January 2018,
https://www.weforum.org/agenda/2018/01/google-ceo-ai-will-be-bigger-than-electricity-or-fire/
18
SCHMIDT, Adrien, “How Does AI Measure Up to Other Tech Trends on The Gartner Hype Cycle?”, op. cit.
19
PANETTA, Kasey, “Top trends in the Gartner Hype Cycle for Emerging Technologies, 2017”, op. cit.
20
MOKYR, Joel, VICKERS, Chris, ZIEBARTH, Nicolas L., "The History of Technological Anxiety and the Future of
Economic Growth: Is This Time Different?", in Journal of Economic Perspectives, 29(3), 2015, pp. 31-50., p. 47.
21
DORN, David, “The Rise of the Machines. How Computers Have Changed Work”, Zurich, UBS International Center of
Economics in Society, n°4, December 2015, 31p., p.8.
22
CELLAN-JONES, Rory, “Stephen Hawking Warns Artificial Intelligence Could End Mankind”, BBC, Technology, 2
December 2014, http://www.bbc.com/news/technology-30290540

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negative news than positive ones23. With this in mind, one understands why narratives about
technology and A.I. in general are rather enthusiastic. Stanford’s new Report Card for A.I.24 makes
an attempt at measuring different A.I.-indicators to include, but not limited to, course-enrolment,
GitHub Project Statistics and Academic literature25. The Report Card notably measures media
sentiment: positive articles outweigh gloomy predictions by three to one26. Given some rather
pessimistic forecasts linking the development of A.I. to mass unemployment, it is interesting to
note that – based on data collected from the UK, Canada and US job markets – the index also
points out the growth of the share of job openings requiring A.I. skills (see Annex 3). At the same
time, data also showcases an increase in international robot imports (see Annex 4) and number
of US startups developing A.I. Systems. Highlighting demand and offer for A.I. skills and jobs in
more economically advanced countries is a good indicator of current market needs. However, it
does not mean this trend will stay stable in the long-term.
Incidentally, there is broad consensus that there are many statistics on the future of work:
opinions vary a great deal. What our findings suggest is that technologies create more jobs than
they displace. As we move forward, A.I. research is progressing steadily, crossing the threshold
from “laboratory research to economically valuable technologies, a virtuous cycle takes hold”27.
Businesses are and will be seeking to retain a competitive advantage and adapt to the changing
economy. Since, some machines are now capable of performing some tasks better and faster than
most humans, and will increasingly become able to do so “labor is becoming automated for
reasons of cost, efficiency, and quality”28. Organisation and societies have now means to expand
and diversify their activities. Economic incentives are driving businesses to replace people with
machines, for robotisation and A.I. offer affordable and efficient alternatives to low-skilled
workers.
As jobs get displaced due to digitisation, new jobs are created. This is the case for fields such as
cyber security, 3D printing, cloud, machine learning, virtual reality, etc. Traditional sectors of our
economies are impacted as well, such as the energy industry (renewable energies), the transport
industry (smart cars), or the finance industry (blockchain applications). There are many more
examples showing how the nature of work continually evolves and will keep on changing (See
Annex 5). A global study led by Accenture PLC asserts that several new categories of jobs are
emerging “that look nothing like those that exist today”29. Certain specific profiles that cannot be
replaced by cognitive technology in the near future will be sought for: ‘explainers’ capable of
bridging the gap between technologists and business leaders, ‘trainers’ to teach performance to
A.I. systems and ‘sustainers’ to operate A.I. systems according to their intended purpose.
Possibilities are limitless and we predict there will be an ongoing creation of new employment
opportunities following market needs.
The prior statement highlights the possibilities offered by digitisation, notwithstanding the
implications for the labour force. McKinsey Global Institute’s 2017 study esteemed that robot
automation could displace 400 to 800 million jobs by 2030 in the case of a rapid adoption
23
DIAMANDIS, Peter H., KOTLER, Steven, Abundance: The Future is Better Than You Think, New York, Free Press, 2014,
400 p., p. 30.
24
The AI Index was developed in cooperation between Stanford University, the MIT, OpenAI and SRI International.
25
STONE, Peter, BROOKS, Rodney, BRYNJOLFSSON, Erik, et. al., "Artificial Intelligence and Life in 2030.", in One
Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA,
September 2016, http://ai100.stanford.edu/2016-report.
26
ibid.
27
RUSSEL, Stuart, DEWEY, Daniel, TEGMARK, Max “Research Priorities for Robust and Beneficial Artificial Intelligence”,
in AI Magazine, Winter 2015, Association for the Advancement of Artificial Intelligence, pp. 105-114, p. 106.
28
CALLAGHAN, Victor, MILLER, James, YAMPOLSKIY, ARMSTRONG, Stuart, The Technological Singularity: Managing
the Journey, Berlin, Springer, The Frontiers Collection, 261 p., p. 13
29
WILSON, James H., DAUGHERTY, Paul R., MORINI-BIANZINO, Nicola, “The Jobs that Artificial Intelligence Will
Create”, MIT Sloan Management Review, Vol. 58, n°4, Summer 2017, pp. 13-17, p. 14.

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scenario30. This phenomenon conveys a healthy transition ensuring long-term economic growth.
Countries are expected to operate a shift from a market of mass-production to a market of
information processing and A.I.. This will require people “to switch occupation and learn new
skills”31, with a higher incidence for advanced economies. The report forecasts that innovation,
investment and economic growth should suffice to create jobs32.
According to data from the US Bureau of Labor Statistics, employment by sector changed
dramatically in the last century, shifting from an agricultural-based labour market to the profit of
other sectors such as trade, telecommunications or education (see Annex 6). If history repeats
itself, an estimated 10% of the population should shift sectors in the next 15 years. However,
“humans have consistently demonstrated an ability to find new things to do that are of greater
value when jobs have been outsourced or automated. The industrial revolution, outsourced IT work,
China’s low-cost labor force, all ultimately created more interesting new jobs than they displaced”
33. While automation and computerisation puts certain categories of jobs at risk, these changes
are inevitable since technologies develop at an exponential pace. The challenge will be to adapt to
upcoming evolutions. According to Matt Hancock, UK Minister of State for Digital and Culture, the
current pace of changes brought about by new tech and A.I. is the slowest we will see for the rest
of our lifetime34.
Following Kotler and Diamandis, we are witnessing the development of a new paradigm. Thanks
to information and technology we live in an age of abundance, or a generation with the ability to
raise the living standards of humanity. Studies suggest that the future of technologies will be
more inclusive and not solely limited to more economically developed countries. They argued
back in 2012 that “a Masai warrior with a cell phone has better mobile phone capabilities than the
president of the United States did twenty-five years ago (…), we are now living in a world of
information and communication abundance”35.
Even if some countries are already experiencing the challenges of emerging technologies, A.I. is
still a tabula rasa right now, which carries limitless possibilities and opportunities. The future of
work will depend on what we will feed it, ie. our ability to catch up with technological change,
adapt and accept the novelty. A.I. in itself is a neutral technology. It is neither negative nor
positive. In such a scenario, technology-induced employment should be a definite driver for
growth. Humans might merge with machines or live on mars one day, but in the end, this all
comes down to what we want to make out of new technologies. Will policy-makers and global
markets be willing to militarise A.I., or make something beautiful out of it and cooperate on a
global scale? Historical extrapolation tells us that the future is rarely black or white.
30
MANYIKA, James, LUND, Susan, CHUI, Michael, BUGHIN, Jacques, WOETZEL, Jonathan, BATRA, Parul, KO, Ryan,
SANGHVI, Saurabh, “Jobs Lost, Jobs Gained”, McKinsey Global Institute, December 2017,
https://www.mckinsey.com/~/media/McKinsey/Global%20Themes/Future%20of%20Organizations/What%20the%20future%20
of%20work%20will%20mean%20for%20jobs%20skills%20and%20wages/MGI-Jobs-Lost-Jobs-Gained-Report-December-6-
2017.ashx
31
MANYIKA, James, LUND, Susan, CHUI, Michael, BUGHIN, Jacques, WOETZEL, Jonathan, BATRA, Parul, KO, Ryan,
SANGHVI, Saurabh, “What the Future of Work Will Mean for Jobs, Skills, and Wages”, McKinsey Global Institute, November
2017, https://www.mckinsey.com/global-themes/future-of-organizations-and-work/what-the-future-of-work-will-mean-for-jobs-
skills-and-wages
32
ibid.
33
DIAMANDIS, Peter H., KOTLER, Steven, Abundance: The Future is Better Than You Think, op. cit., p.p. 300-301.
34
HANCOCK, Matt, “Addressing the Global Cyber Challenge”, gov.uk, Government, Speeches, 19 September 2017,
https://www.gov.uk/government/speeches/addressing-the-global-cyber-challenge
35
ibid., p. 9.

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III. Future Employability: Next Steps and Long-Term Solutions?
“We cannot teach our kids to compete with machines – they are smarter. Teachers must stop
teaching knowledge. We have to teach something unique so that a machine can never catch up
with us. These are soft skills we need to be teaching our kids: values, believing, independent
thinking, teamwork, care for others. (…) This is why I think we should teach our kids: sports,
music, art – to make sure humans are different. Everything we teach should be different from
machines. If the machine can do better, you need to think about it”36, Alibaba Group – Jack Ma,
24 January 2018, WEF Forum.
This section focuses on proposed solutions and suggests adaptations to foster a virtuous circle of
economic employment and sustainable growth. Caveats and risk studies will not be at the centre
of this analysis.
The future of market capitalism, work, and skills since the dawn of technology is uncertain. In
this regard, Pew Research Center and Elon University’s imagining the Internet Center led a large-
scale canvassing of technologists, scholars, practitioners, academia and strategic thinkers
requesting their predictions regarding the future of jobs by 202637. This 2017 study shortlisted
five major recurring themes about the future of jobs and training in the tech age (see Annex 7).
The topics of interest focused on training and education capabilities, but also policy and market-
based solutions for greater employability. This research aims to dive further into such themes
and, mainly, the discussions on potential policy adjustments and governance, on training and
learning and best practices.
Many stakeholders are concerned about the concrete implications of A.I. and automation-driven
worlds in terms of policy and regulation. “One of today’s unanswered questions is how will
governments potentially respond (bans, nationalise, collaborate, policies to be implemented)?”38.
What levels of implementation should we focus on (global, national, organisational)? Does this
field call for stricter regulation, or will soft law suffice in the long run? Education, training, and
income distribution are particularly central to the political debate at the moment. Brynjolfsson
and McAfee explore different government policies and other interventions aimed at promoting
economic growth and at incentivising development39. They argue that the march of technology
should not be halted and that excessive regulation would be counter-productive. A.I.-induced
wealth will allow for resources to flow to more affected sectors of the economy. One of the
interesting suggestions is their call for new metrics and indicators to measure the impact of such
technologies on our societies. GDP per capita, for instance, has been a controversial
measurement of economic wealth for many years now. Making an attempt at predicting the
future and preparing for its challenges calls for precise metrics. Our findings suggest that, in
order to do so, decision-makers need to avoid linear-thinking in the case of A.I. and related
technologies. The advancement of A.I. calls for strategic thinking (planning, forecasting and
prioritising) to deliver on best practices and effective policies40.
36
FLASHMAN, Gay, “Jack Ma on the IQ of Love – and other top quotes from his Davos Interview”, WEF, Global Agenda,
China, 24 January 2018, https://www.weforum.org/agenda/2018/01/jack-ma-davos-top-quotes/
37
RAINIE, Lee, ANDERSON, JANNA, “The Future of Jobs and Jobs Training”, PewResearchCenter, 3 May 2017,
http://www.elon.edu/docs/e-
web/imagining/surveys/2016_survey/Future%20of%20Jobs%20Skills%20Education%205_3_17%20Elon%20Pew.pdf
38
“A Survey of Research Questions for Robust and Beneficial AI”, op. cit., p. 25.
39
BRYNJOLFSSON, Erik, MCAFEE, Andrew, The second machine age: work, progress, and prosperity in a time of brilliant
technologies, W.W. Norton & Company, 2014, 304 p., p. 12.
40
SCHWAB, Klaus, “The Fourth Industrial Revolution: what is means, how to respond”, op. cit.

8. 8
This is particularly essential, for “changes in educational and learning environments are necessary
to help people stay employable in the labor force of the future”41. By 2020, employers are expected
to seek skills such as complex problem solving, critical thinking, adaptability, creativity, people
management, and cognitive flexibility amongst others. There are many forces shaping the nature
of work and driving the employment demand and supply: training people and making them fit for
the job market, is one. Tony Wagner and a research group from Harvard University identified
seven key competencies and skills for greater employability in the future.42 These “survival skills”
are not about memorising content, but creating knowledge and solving complex problems (see
Annex 8). Repetitive tasks and administrative work should disappear for the most part.
Preparing the labour force for the future job market is essential to avoid any skill gap and
therefore, unemployment.
According to a working paper on education research from UNESCO, learning in our century
should be focused on learning to know, learning to do, learning to be, and learning to live
together. The study compiles data from various research papers to map out the essential
competencies and skills nations will have to focus on to equip their students and workers. “Real-
world challenges are highly complex, often ill-defined and interdisciplinary in nature, spanning
multiple domains (social, economic, political, environmental, legal and ethical). Learners must have
opportunities to reflect on their ideas, hone their analytical skills, strengthen their critical and
creative thinking capacities, and demonstrate initiative. In particular, the ability to evaluate new
inputs and perspectives, build new capacities and strengthen autonomy will be crucial”43.
As discussed earlier, greater employability is not only an objective, but also a suitable prospect if
nations and organisations adopt tailored policies and education. According to Professor Mateja
Jamnick of Cambridge University, “The jobs that will persist are the jobs that are inherently
human... that require love, compassion, understanding”44. Developing a comprehensive and
globally shared view of how superintelligent systems affect our lives and shape our environment
will be of great support our journey to the future45. “In a world of cheap goods, inequality in terms
of wealth or income may rise, inequality in the form of access to “primary” resources (…) would be
greatly diminished. The long-term trend toward greater leisure will continue, and one can even
imagine an economy that reaches the stage in which only those who want to work actually will do
so.”46
41
RAINIE, Lee, ANDERSON, Janna, “The Future of Jobs and Jobs Training”, Pew Research Center, Internet & Technology, 3
May 2017, http://www.pewinternet.org/2017/05/03/the-future-of-jobs-and-jobs-training/
42
WAGNER, Tony, The Global Achievement Gap, New York, Basic Books, 2014, 360 p., pp. 14-32.
43
LUNA SCOTT, Cynthia, “The Futures of Learning 2: What Kind of Learning for the 21st
Century?”, UNESCO, Education
Research and Foresight, 14 November 2015, 14 p., p. 8.
44
GARVEY, Jane, DALZIEL, Karen, “Women shaping the Future in AI”, BBC Radio 4, Womens Hour, 16 January 2018,
http://www.bbc.co.uk/programmes/b09lw33j
45
SCHWAB, Klaus, “The Fourth Industrial Revolution: What it Means, How to respond”, op. cit.
46
MOKYR, Joel, VICKERS, Chris, ZIEBARTH, Nicolas L., "The History of Technological Anxiety and the Future of
Economic Growth: Is This Time Different?", op. cit.

9. 9
IV. Case study: UAE’s job market ripe for A.I.?
“We want the UAE to become the world’s most prepared country for artificial intelligence”47
- H.H. Sheikh Mohammed bin Rashid Al Maktoum
H.H. Sheikh Mohammed bin Rashid Al Maktoum, Vice-President and Prime Minister of the UAE
and Ruler of Dubai launched the UAE Strategy for Artificial Intelligence (A.I.) in October 2017. In
order to bring this project to life, H.E. Omar Bin Sultan Al Olama, was appointed the world’s first
Minister of State for A.I., following the cabinet reshuffle of October 2017. He is now in charge of
developing a strategic roadmap for A.I.48.
This important initiative is part of and a direct follow-up to the UAE Centennial 2071 objectives
and the UAE 4th Industrial Revolution Strategy. The strategy document states its aim is to invest
“in A.I. and its applications across multiple domains. The strategy is premised to ensure best
utilisation of all resources and invest in all available potential in creative manners that accelerate
the execution of developmental projects”49. The official release conveys the great potential of this
technology: to be embedded in the country’s modern governance and applied to all sectors of
society. Naturally, A.I.’s potential is also essentially envisioned as a “new vital market with high
economic value”50.
The UAE’s ambition depicts its visionary leadership and their desire to be at the forefront of A.I..
Many companies like Amazon, Google, Skype and Salesforce.com are heavily investing in A.I.51,
the country, and its local market. Therefore the nation seems ready to undertake the necessary
transformations to kick-start the UAE’s A.I. Strategy. “Findings from Accenture's 2017 Digital
Consumer Survey reveal that those in the UAE are ready to embrace A.I. technologies, with 76 per
cent of users comfortable with an A.I. application responding to their query, while 68 per cent have
interacted with computer-based apps in the past 12 months.”52. The potential adoption rate of A.I.
in the UAE is significantly higher than global averages.
Like any other countries, the UAE will have to prepare its younger generation for the challenges
ahead, especially for the sectors and industries described in Chapter II. According to World Bank
and Oxford Economics data sets, about 24% of work activities in the UAE could be displaced as a
result of automation (the highest number being 26% for Japan). This estimate follows a mid-
point adoption scenario where robotisation and A.I. would be gradually introduced to transform
the workplace (see Annex 9). On a world scale this implies that the UAE - an economically
advanced country53 - is one of the nations where the development of new skills and sector shift
are the highest. For the UAE and A.I. Minister Omar Bin Sultan Al Olama this represents a great
challenge but also an opportunity to compete with global elites.
47
SALAMA, Samir, “Mohammad Bin Rashid Reveals Reshuffled UAE Cabinet”’, Gulf News, Government, 19 October 2017,
http://m.gulfnews.com/news/uae/government/mohammad-bin-rashid-reveals-reshuffled-uae-cabinet-1.2108934
48
UAE The Cabinet, “H.E. Omar Bin Sultan Al Olama”, Cabinet Members, 2018, https://uaecabinet.ae/en/details/cabinet-
members/his-excellency-omar-bin-sultan-al-olama
49
WAM, “UAE Strategy for Artificial Intelligence to Drive Growth in the Country”, Dubai, Khaleej Times, Nation, 16 Octobre
2017, https://www.khaleejtimes.com/nation/dubai/artificial-intelligence-to-drive-uae-growth
50
UAE Government, “UAE Strategy for Artificial Intelligence”, Government.ae, Federal governments’ strategies and plans, 28
November 2017, https://government.ae/en/about-the-uae/strategies-initiatives-and-awards/federal-governments-strategies-and-
plans/uae-strategy-for-artificial-intelligence
51
KRAUTH, Olivia, “The 10 Tech Companies that Have Invested the Most Money in AI”, Tech Republic, Innovation, 12
January 2018, https://www.techrepublic.com/article/the-10-tech-companies-that-have-invested-the-most-money-in-ai/
52
CABRAL, Alvin R., “UAE Ready to Be Powered by AI”, Dubai, Khaleej Times, Technology, 2 August 2017,
https://www.khaleejtimes.com/technology/uae-ready-to-be-powered-by-ai
53
MANYIKA, James, LUND, Susan, CHUI, Michael, BUGHIN, Jacques, WOETZEL, Jonathan, BATRA, Parul, KO, Ryan,
SANGHVI, Saurabh, “Jobs Lost, Jobs Gained”, op. cit.

10. 10
Technology is and will be an enabler for jobs if the people are ready to move with the
government and the industry in this transformation. Seizing the opportunity offered by A.I. could
pave the way for the UAE to become one of the leading hubs for digitisation. Coherent and agile
strategies with smart goals are helpful to track progress and potential pitfalls in this regard. How
could the UAE then manage to achieve economic wealth and seamlessly integrate technology in
people’s life? By developing technological awareness, fostering education and training programs,
elaborating consistent economic policies, and attracting the right people.
The UAE has the potential to develop its first Arab Silicon Valley, becoming an incubator for
futuristic and ambitious startups. Providing business-friendly regulation for A.I.-entrepreneurs
and aficionados will prove to be an asset in this regard. Economic growth and job creation seem
therefore very likely if policies remain in tune with the business concerns. However, successful
countries will eventually be the ones who are also able to focus on nurturing unique human skills
that machines seem unable to replicate54.
CONCLUSION
Computational power has transformed the way organisations work. As A.I. and robotisation
starts to substitute humans in the workplace, this study wished to research the potential
continuity and long-term impact of the digitisation trend.
We learned that it is impossible to predict the future A.I. and its impact on the job market with
accuracy. Errors in forecasting the future of technology tend to be extreme. Darryl Zanuck,
Hollywood mogul, predicted television would fail back in 1946. Later on, in 1977, Ken Olson,
president and founder of Digital Equipment Corp., thought there was no reason anyone would
want a home computer55. It is difficult for the human mind to foresee innovations yet to be made.
However, certain indicators demonstrate that automation and A.I. – our 4th Industrial Revolution
– are a promising sector, which will probably be explored for at least a few more decades.
We saw that determining the future of A.I. is hardly realistic, but it is however possible to predict
its disruptive effect on the job market. Current statistics and sentiment towards digitisation and
automation are rather varied but denote an overarching positive economic trend. Putting history
into perspective, research and extrapolation have demonstrated high potency in forecasting
long-term job creation.
We attempted to focus on the central themes of future employability in our third chapter. We
noted that the most common concerns and areas of focus revolve around policy, decision-making,
education, and skills.
Finally, we assessed the UAE’s recent development in light of our analysis. We provided the
reader with an overview of the country’s strategies and milestones on A.I.. We explained how this
field is susceptible to result in faster growth and employment for the country.
This study focused on evaluating the future of work in relation to A.I.. We are now convinced that
the development of technology and superintelligent systems will result in a different job market
with a potential for greater employability and economic growth. We can however only gauge, not
reasonably predict, where A.I. will stand in a few decades from now. “Overall, past experience
54
RAINIE, Lee, ANDERSON, JANNA, “The Future of Jobs and Jobs Training”, PewResearchCenter, 3 May 2017,
http://www.elon.edu/docs/e-
web/imagining/surveys/2016_survey/Future%20of%20Jobs%20Skills%20Education%205_3_17%20Elon%20Pew.pdf
55
GOBLE, Gordon, “Top 10 bad tech predictions”, Digital Trends, 4 November 2012,
https://www.digitaltrends.com/features/top-10-bad-tech-predictions/

11. 11
suggests that predictions of immanent dramatic technology development should be assessed with a
healthy dose of skepticism. Yet it is still reasonable to expect that the boundaries between
automatable and non-automatable tasks will continue to shift as computers and robots become
more powerful and versatile”56.
56
DORN, David, “The Rise of the Machines. How Computers Have Changed Work”, op. cit., pp. 26-27.

12. 12
Annexes
Annex 1: From industry 1.0 to industry 4.0 – Source: Accenture.
Annex 1
Annex 2: Gartner Hype Cycle for Emerging Technologies, 2017 – Source : Gartner blogs.
Annex 2

13. 13
Annex 3: Share of Jobs Requiring A.I. Skills – Source: Stanford A.I. Index.
Annex 3
Annex 4: Robot imports – Source: Stanford A.I. Index.
Annex 4

14. 14
Annex 5: A.I. is transforming industries – Source: Intel A.I. Academy.
Annex 5
Annex 6: Sector shifts and job creation as a result of technological changes – Source: McKinsey &
Company.
Annex 6

15. 15
Annex 7: Major themes about the future of jobs and training in the tech age – Source: Pew
Research Center.
Annex 7
Annex 8: Wagner’s 21st century learning skills – Source: Core Task Project
Annex 8

16. 16
Annex 9: Work displacement per country as a result of automation, 2030 projection - Source:
McKinsey Global Institute.
Annex 9