A survey by Pew Research Internet finds 72% of Americans are worried about the future when robots,  artificial intelligence (AI) are capable of doing many jobs that are currently done by humans. So people are worried about future job risks due to the explosion of AI.

A recent PwC research finding shows that by the mid-2030s, up to 30% of jobs worldwide could be automatable. It is predicted that up to 30% of jobs (~10.5M) in the UK are considered at high risks due to transformation of artificial intelligence and automation. Majority of the professionals will be affected not possessing the skills to accommodate the AI revolution. By 2020, it is expected that roughly 75M jobs would have been dissolved across the globe as a result of the emergence of AI.

In a study by the consultancy firm Oxford Economics, the rapidly growing use of robots is expected to have a profound impact on jobs across the world, resulting in up to 20m manufacturing job losses by 2030.

Mid-skill workers are most at risk, with data illustrating that employment growth has been greatest at the extreme ends of the spectrum (top and bottom 20%) whilst in-between there has been a decline, resulting in a hollowing out of jobs for the middle-tier workforce. Within the industry, this displacement of mid-skill workers has become known as the ‘automation paradox’.

The findings come from a recent report published by global recruiter Robert Walters and market intelligence firm Vacancy Soft – Harnessing the Power of AI: The Demand for Future Skills.

Growth in data roles

However, it is not all bad news when we consider the impact of AI on the job market.

This uptake of AI has increased the demand for data professionals. Within large or global entities, IT professionals dedicated to data management are the fastest-growing areas. Data roles across the board have also increased since 2015, with engineers and data scientists being key areas of growth within the sector.

As businesses become ever more reliant on AI, there is an increasing amount of pressure on the processes of data capture and integration. As a result, we have seen an unprecedented number of ‘next generation’ roles being created with data skill-set at their core. In fact, data-related roles across the board have increased by 80% since 2015.

 

What has been the most interesting to see is the emergence of data scientist as a mainstream profession – with job vacancies increasing by a staggering 110% year-on-year. The same trend can be seen with data engineers, averaging 86% year-on-year job growth.

Ollie Sexton, Principal – Business Development & Go-to-Market Execution at Robert Walters

What are the most affected industries by AI & ML?

Retail: whilst driving the e-commerce powerhouse, AI is being utilised to drive consumers back to the ‘bricks and mortar 2.0.’ From self-checkout, and monitoring customer patterns and preferences, to using data to enhance the customer journey and in-store experience, and seamlessly linking online and offline channels.

Business Support: the application of AI within the professional services field is extraordinary, but when considering just the business support aspect alone AI has been implemented at every level – from spam filters and smart emails to smart personal assistants (Siri, Cortana, Google Now), automated customer support, and sales and business forecasting.

Healthcare: experimental AI is making huge breakthroughs in the healthcare industry from Google’s DeepMind being taught to read retinal scans, healthcare apps saving hours of GP time, to patient safety, training and education, as well as drastic improvements in bias, inequality and unfairness within the profession.

Who are mostly affected due to automation?

The Office of National Statistics analysis showed that 70.2% of the roles at high risk of automation are currently held by women. Also, people aged 20 to 24 years are most likely to be at risk of having their job automated, when compared with other age groups. Younger people are more likely to be in roles affected by job automation. Of those aged 20 to 24 years who are employed, 15.7% were in jobs at high risk of automation. The risk of job automation decreases for older workers and is lowest for workers aged between 35 and 39 years. Just 1.3% of people in this age bracket are in roles at high risk of automation. The risk then increases from the age group 40 to 44 upwards.

UK’s skill shortages

The concern should not be about jobs being displaced, but whether our workforce is ready and prepared to accommodate a job boom within data and digitalisation.

 

According to hiring managers within the tech field, 56% of professionals lack sufficient experience for the role, whilst a further 51% also lack the right technical skills.

Tom Chambers, Manager – Data Science, Analytics & Engineering at Robert Walters

Another recent survey of tech professionals by Robert Walters found that just 10% of cybersecurity professionals, 31% of data management professionals, and 27% of software developers rated their skills as ‘advanced.’

Worryingly 40% of UK professionals employed within the AI-sphere stated that their job-specific skills were only at the ‘beginner’ level.

Historically the UK has been able to attract skilled IT and data professionals from across the EU – a quarter of tech professionals in the UK are from overseas – yet with the current political climate this may prove to become more of a challenge.

 

The UK – in particular, London – has an opportunity to be at the centre of the tech & AI revolution but growth and demand can only be met with the upskilling or retraining of mid-tier talent so that they don’t become redundant.

Tom Chambers, Manager – Data Science, Analytics & Engineering at Robert Walters

Conclusion

AI is having a significant impact on the global as well as the UK labour market. As a result of early-stage automation and digitisation through AI, job markets are already polarising and changing drastically. So both employers, employees and potential job seekers need to be aware of this and let them prepare for the upcoming AI tsunami. Instead of worrying about job losses, employees and employers should be helping to reduce jobs or boring tasks in which AI and machine learning can take over, while employees can spend more time with higher-level strategic tasks.

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