Sectors such as retail have felt it like a tsunami, with relatively new players such as eCommerce platforms Amazon and Alibaba growing rapidly, taking market share and forcing change at traditional brick-and-mortar retailers.
Others such as the automotive sector may have yet to feel the full brunt of change. Even as Tesla’s electric cars continue rolling off its production lines, they still constitute a minuscule proportion of the total number of cars on the road, which remains dominated by gas-guzzlers.
Meanwhile, the bigger prize is autonomous driving, with electrification just a stepping-stone towards the larger goal. Already companies such as Google have been testing self-driving technology on roads, demonstrating it is only a matter of when and not if, for drivers to literally take the back seat while being driven to their destinations by smart and connected cars.
What is curious is that automation is nothing new for the car industry. Production facilities at the largest car companies have for years employed the latest state-of-the-art robotic machinery working alongside workers.
Likewise in the manufacturing sector, production of integrated circuits, silicon wafers, TV screens, smartphones, refrigerators, washing machines and appliances is a symbiotic relationship, where machines or robots produce the parts, with human workers responsible for assembly, inspection, quality, supervision and design.
But winter may be coming to this mutually beneficial arrangement. The rise of machine learning and artificial intelligence (AI) has the potential to disrupt and completely change the way things are done. “Business as usual” will then no longer be possible.
Chinese manufacturer Changying Precision Technology Company used to need 650 workers at its mobile phone factory. Today it has 60 due to automation and it believes this number can be further reduced to 20.
The world’s industrial powerhouses have been leading the robotics bandwagon. South Korea has the highest robot-to-worker ratio at 470 robots for every 10,000 workers, while Germany has 292. In contrast, USA has 164 while China has only 36.
These numbers refer to physical robots, be they only arms or those that resemble humanoids. But if you count robotic process automation - the use of software with AI and machine learning capabilities to handle high-volume and repeatable tasks previously requiring a human to perform - the ratio may one day tilt to the side of robotic dominance.
The rise of AI
The first shot was fired by IBM’s Deep Blue, a chess computer which beat world champion Garry Kasparov in 1997. The tide has not stopped since. Just this year, Google’s Alpha Go defeated the world’s number one Go player, in the ancient game deemed even more complex than chess.
While detractors might play down the significance of these wins as just “games”, even the limited AI of today has already displaced jobs doing what was previously considered sophisticated human activities.
Blackrock, the world’s largest money manager has cut more than 40 jobs, replacing human portfolio managers with AI-driven computerised stock-trading algorithms.
Even tradition-bound industries like the legal profession have turned to AI to improve its performance. Global law firm, Linklaters, uses LinkRFI, a digital tool, to sift through 16 UK and European regulator registers to check client names for banks, processing thousands of names in hours. A lawyer would have taken about 12 minutes per name.
The biggest bank in the US, JP Morgan, is using a learning software called COIN, short for Contract Intelligence, to interpret commercial-loan agreements, doing in seconds what used to take 360,000 hours of work each year by lawyers and loan officers. Not only are there fewer errors, the program never needs a vacation. It is also using AI to help comply with financial regulations.
These are just a few early instances. According to a report from the Oxford Martin School’s Programme on the Impacts of Future Technology, 47% of all jobs in the US are likely to be replaced by AI systems in the near future.
Science and technology luminary Ray Kurzweil predicts that computers will exceed human intelligence by 2045. Elon Musk, CEO of Tesla, believes it is even sooner, by 2030. Meanwhile, Steven Hawking, Nobel-prize physicist, thinks the rise of AI could spell the end of mankind as we know it.
Our response, our responsibility
Whether these predictions will come to pass is yet to be seen. However, the era of technological disruption is certainly well underway, presenting both opportunities and threats for businesses and communities.
To be an effective business partner, human resource professionals need to understand the implications of digital disruption on their company and the lives of the individuals in it. They must guide their organisations in navigating the turbulent waters while meeting their organisational commitments for corporate social responsibility. Leaders need to demand it of them.
KellyOCG, in conjunction with McKinsey, conducted a research study this year to map the probability of automation for all job types across all of the industries we serve.
Based on an analysis of each job type – including the associated knowledge, skills and abilities - and its probability of automation, we are now able to assess the impact on a given organisation, addressing both the opportunity and the risk.
Some of the results of the study are obvious. Data entry, production and manufacturing are some examples of work with high automation potential.
But some outcomes are surprising. Scientists, physicians, bankers and public security workers may see some 30 to 40% of their work being automated.
Even educators are not exempt, with the work of middle school teachers having an over 20% potential of automation. Early-childhood educators may see some automation, but they remain among the jobs that have the least automation potential, alongside research analysts, community workers, nurses, and creative workers.
Our research further showed that jobs, where greater than 30% of the tasks are highly automatable, are most likely going to be automated. With the rise of the gig economy, even the remaining tasks might be parcelled out to freelancers, further disrupting the traditional assumptions behind full time permanent jobs.
A report by the World Economic Forum (WEF) last year surveyed chief human resource and strategy officers on the top 10 skills they expect will be needed in 2020 compared with skills needed today.
Complex problem solving is the top skill in both periods, but critical thinking and creativity moved much higher on the chart for 2020, rounding out the top 3 spots. Emotional intelligence and cognitive flexibility are new entrants for the top 10 in 2020.
Negotiation declined in importance, going from fifth to ninth position, reflecting the expectation that machines with the aid of big data may begin making decisions for us. A separate study by the WEF’s Global Agenda Council predicts that AI machines may even be part of a company’s board of directors by 2026!
Responsible corporate leaders need to consider the implications not only for their businesses but also to their employees and the communities they operate within.
If you know that specific roles are likely to be automated, what actions can you take to cross train those who may be affected? Have you developed a pathway for them to build the skills required to move into a new role less likely to be automated, either within your company or elsewhere?
An under-appreciated aspect of big data and machine learning is that we now have access to the information necessary to answer these questions. We can then bring value to our organisations and communities through
- Workforce Planning, by aiding the leadership to know what roles are most open to automation, identifying the alternative approaches to clustering the activity to drive organisational effectiveness and developing sourcing strategies to leverage the emerging market alternatives best suited to achieving company goals.
- Training and Development. While lifelong learning is an established standard for today’s workforce, through the use of a compatibility index, we are now able to define both the market opportunities as well as the specific training needed to maximise the opportunities and minimise the threats arising from automation.
- Economic development, by working with government leaders and educators to develop a balance between supply and demand of the manpower resources within the community, to ensure a progressive and sustainable environment.
At a time where there is so much changing around us, it is critical that we pause and assess the possible implications, and identify people and organisations with whom we share a set of common beliefs so that we can work together to achieve outcomes we can all be proud of.
At KellyOCG, we recognise the unique and sometimes conflicting opportunities that arise as a result of the digital revolution we are all experiencing. Our purpose is to connect people and work. Our values necessitate that we invest the time and resources to build these connections in a way that is respectful to both the individuals and the customers who have placed their trust in us.
We welcome your engagement if you share our passion for the subject.