4IR? Artificial Intelligence and the Changing Landscape of Work as we know it

Following last month’s Fourth Industrial Revolution (4IR) mini-series posts, including an introductory Overview and associated Glossary,[1] this instalment explores some of the possible impacts and opportunities of the 4IR and Artificial Intelligence (AI) for various industries regarding skills and the future of ‘work’.

Various sites and social platforms – including but not limited to those of education and training institutions; news and publishing agents; financial and investment interests; labour, social and economic development organisations; IT and data advisory services; public sector bodies and policymakers – have devoted energy to considering what the future holds and which skills are most likely to be required within the next decade, and beyond. Given that this digital age is characterised by rapid, disruptive and pervasive technological change, most contributors acknowledge that future roles or job descriptions do not presently exist or are only just being created. There can be no certainty as to which industries and jobs will be most impacted since technological innovations and capabilities are advancing exponentially.

Another aspect on which most agree is that the continued growth of IT and of ‘human-machine partnerships’ presents tremendous opportunities for innovation, growth and quality of life, but also has ethical implications. These implications range from “the immediate (how are the algorithms behind Facebook and Google influencing everything from our emotions to our elections?) to the future (what will happen if self-driving vehicles mean there are no more jobs for truck drivers?)”[i], and introduces “unprecedented ethical, legal, social, security, privacy and safety challenges that need to be addressed before the true benefit of these opportunities can be realized.”[ii]

While the future remains changeable – at least more rapidly changeable than ever before – there is some consensus among thought-leaders in this arena, including:

  • There will be aggregate job losses due to AI and automation
  • There will be job growth for shifting skills’ requirements and for new or augmented occupations
  • Disruption will be felt across all industries and economies
  • There is a need to prepare and adapt, at the individual, organisational and global level

IT systems have progressed from basic and rule-based operations (automation systems) to those which mimic human behaviour and cognitive thought patterns (AI systems).
Traditionally, the most ‘at risk’ roles were lower-order, manual and repetitive or routine jobs, whereas advancements in AI are seeing a shift to higher order work, notably in healthcare but also in the accounting, legal, marketing, and even human resources sectors.

Manufacturing is an early adopter (and initiator) of AI technology, utilising automation and specifically designed industrial robots since the mid-20th century and developing capabilities, with advances in technology. Industrial robots today are still used for dangerous, manual and repetitive tasks but programming for dexterity and reasoning skills are enhancing higher-order (e.g. precision and design-related) applications enabling robots to increasingly undertake work previously performed by humans. Beyond manufacturing, particular industries are predicted to experience greater disruptions than others, based on current and developing trends.

Transportation systems and the broader transport, mobility and logistics industry is one of the most impacted by AI. A whole range of disruptive technologies are developing, including virtual and augmented realities, autonomous trucks, driver-less taxis and drones, self-organising fleets, smart containers and smart cities. Airport technology already enables people to book on their own and drones are being used for couriering and the delivery of goods, including medical supplies.
Other technologies, still largely at concept, include Uber Air (air taxis are already being piloted in various places); Franky Zapata’s jet-powered hovercar (hoverboard already piloted, reaching 160-170km per hour, which crossed the English Channel in around 20 minutes); and Elon Musk’s Hyperloop (US, potentially reaching speeds greater than 700 miles (1,127km) per hour).

AI brings efficiencies to logistics, supply chain, warehousing and transportation operations, reducing time and costs and increasing productivity, accuracy and responsiveness. Technologies include cognitive automation, focussing on IoT and myriad other data feeds, enabling information collection, storage and analysis and facilitating inventory processing, predictive demand and network planning. AI and machine learning (ML) are already used by companies to inform and fine-tune core strategies, such as warehouse locations, as well as to enhance real-time decision making like availability, costs, inventories, carriers, vehicles and personnel. Examples of AI applications in warehousing and retail include: Just Walk Out Technology / Checkout-free ‘Amazon Go’ stores (currently operating across four US cities) using computer vision, sensor fusion, and deep learning technologies; Automated fast food outlets, such as Domino’s Pizza ordering and delivery tracking, McDonalds self-ordering kiosks and kitchen AI automation (e.g. Flippy, the burger-flipping robot); Robots used for packing and unpacking shelves, scanning, collecting and delivering products, including driving a vehicle; and Smart glasses (e.g. Google Glass) for tracking, picking and packing inventory via a warehouse management system.

Correspondingly, e-Commerce is advancing with AI-powered personalisation, dynamic pricing and offer generation centred around the customer. Increasingly automated, and sometimes autonomous, fulfilment centres, with robots navigating the space to collect products and execute customer orders, which can be supported by driverless drones and vehicles for delivery. Since processes are centralised, typical sales processes, channels, and networks of physical stores are becoming less important.

The Marketing industry is already using automation and AI-powered tools to inform things like consumer behaviour predictions, ad placement and personalised messages to consumers, and improved content creation. The next generation of marketing tools are expected to use AI and ML to make communications ever more personalised and relevant through such means as tailored marketing (e.g. tracking interests and curating a website by individual or marketing content by targeted segment of consumers), segmentation in the sales funnel or buyer journey (e.g. tracking and separating consumers by interest/demand/motive) and improved customer interactions through virtual assistants (e.g. chatbots for customer service and sales support). Gartner predicts that chatbots will power 85% of all customer service interactions by the year 2020.[iii]

AI arguably benefits any sector that requires a significant amount of data processing and content handling, such as Financial Services and Insurance, as well as Trading and Investment. Financial institutions already use AI technology for anti-money laundering (AML) and to validate transactions and combat fraud. More sophisticated applications are expected with automation of such processes as stock trading, recommendation, and advisory services (e.g. through AI assistants or chatbots and robo-advisors). Retail and investment banking have already been significantly impacted by increased automation and AI, with investment shifts away from physical (staffed) to digital banking largely in response to consumer behaviour and demand for online and mobile banking. This has resulted in branch closures and retrenchments (predicted at millions of jobs in the next decade[iv]) globally. In South Africa this year, branch closures and retrenchments of thousands of workers – 3,500 employees from three major banks – were announced and initiated. Acknowledging the need for new and more competitive skills in the digital age, skills funds and training programmes for reskilling and entrepreneurial development have been established by some institutions.

AI and ML can be used in the finance industry to make data-based decisions about investments and when to buy and sell stocks. An example of the latter is the emerging field of bionic advisory which combines machine calculations and human insight to provide options that are much more efficient than what either provides alone. Insurance companies are expected to leverage the vast amounts of data available and, together with predictive and ML technologies, arrive at better risk estimations and products to match consumer needs. Another disruption in the financial sector is the emergence of cryptocurrencies (e.g. Bitcoin), with New Zealand being the first country to officially recognise cryptocurrency as legal tender.

Healthcare is another industry where AI has a high current, and potential, impact promising to will significantly improve the overall effectiveness, access and level of service to patients. Improvements to health systems are possible through more accurate medical diagnoses, automation of mundane and repetitive tasks (e.g. swab analysis with recommended prescription), personalised care and medicine, and shorter drug development cycles by aiding in drug research. AI is seen as augmenting the role of healthcare practitioners through automation, mobile and wearable technology (e.g. wellness wearables to monitor biometric data; Smart glasses to assist during surgery and consultation, including remote consults) and improved diagnostic procedures.

What can we Expect and Plan for?

As AI is increasingly adopted across industries, globally, there will be shifts in the work environment, the job market and demand for skills. The Institute for the Future (IFTF) identified six key drivers – working together to produce true disruptions – of future work skills for 2020 which remain relevant today.[v]

Significantly, this year’s IFTF Ten-Year Forecast Summit – “The Age of Distributed Superpowers: 2019-2029” – highlights climate change as a key factor and major disruption, with other considerations and risk factors including automation, market volatility and disruptions to global institutional order. [vi]

There can be no certainty on what new roles will be created in the future, in response to economic and social needs. Changing business models and new categories of jobs are emerging, such as commercial space and Uber Air pilots, personal data brokering and alternative energy consulting. We need to remain informed of changing requirements and new technological advances as well as the global climate crisis.

It is clear that disruptions will be felt across all fields and that learning new skills – as well as unlearning and relearning, as noted by Alvin Toffler – will be crucial and lifelong. One of the key benefits of our information and digital ages is the enhanced access to learning opportunities online, including free courses. The next instalment of this 4IR mini-series will look more closely at skills and available learning sites and courses.

Afro Ant would like to thank Prof. Noel Pearse[vii] of the Rhodes Business School for his guidance and insights, and Joseph Appiah-Yeboah[viii] for his presentation, “AI and the Future of Work – Will I still be relevant?”, at the Afro Ant Saturday Sessions in April 2019, which informs this post.

Additional Links and References

Krasadakis, G. (7 June 2018) “Artificial Intelligence: What’s Next” [Online: https://medium.com/ideachain/ai-beyond-the-hype-3fd6b4b16c3c]
















[1] Please note that the Acronyms and Definitions (Glossary) post will be updated throughout the 4IR mini-series and in response to your contributions and suggestions.

[i] Dalmia, V. and Sharma, K. (13 February 2017) “The moral dilemmas of the Fourth Industrial Revolution” [Online: https://www.weforum.org/agenda/2017/02/ethics-2-0-how-the-brave-new-world-needs-a-moral-compass/]

[ii] Center for Research and Development Strategy: Japan Science and Technology Agency (2017) cited in Ferreira, C.M. and Serpa, S. (2018) “Society 5.0 and Social Development” [accessed online: https://www.preprints.org/manuscript/201811.0108/v1; For peer-reviewed version: http://www.sciedupress.com/journal/index.php/mos/article/download/14206/8970]

[iii] Hinds, R. (2 April 2018) “By 2020, You’re More Likely to Have a Conversation With This Than With Your Spouse” [Online: https://www.inc.com/rebecca-hinds/by-2020-youre-more-likely-to-have-a-conversation-with-this-than-with-your-spouse.html?cid=search]

[iv] UXDA, Alex and Linda (undated) “Banks Will Cut Millions of Jobs in The Next Decade” [Online: https://www.uxdesignagency.com/blog/Banks_will_cut_millions_of_jobs_in_the_next_decade]

[v] Institute for the Future (IFTF) for the University of Phoenix Research Institute (2011) “Future Work Skills: 2020” [accessed online: http://www.iftf.org/uploads/media/SR-1382A_UPRI_future_work_skills_sm.pdf]

[vi] http://www.iftf.org/techfutureslab/

[vii] Pearse, N. (August 2019) Personal Communication

[viii] Appiah-Yeboah, J. (April 2019) “AI and the Future of Work – Will I still be relevant?”, Presentation at Afro Ant Saturday Sessions