How to automation-proof your workforce

How can the human and AI workforce co-exist? It’s all about the soft skills, says Jonathan Fitchew. 

Reading time: 4m 30s.

Artificial intelligence has done incredible things in its lifetime. It’s beaten the world’s best chess players, composed classical music and built cars. As more companies see its potential to change their ways of working, AI continues to make significant strides towards being a consistent contributor to the workforce.

But this progress comes with a cost – the potential of wholesale human replacement. We’ve already seen it on the high street, as more than a quarter of supermarket checkout positions were lost between 2011 and 2017.

As well as dealing with the heavy lifting in supermarkets and factory floors, AI is becoming more adept at handling cerebral tasks, like financial processing and data entry. So as artificial intelligence makes its way into the office, can humans expect to be made redundant by advances in software?

Decisions with data

AI may be reducing the necessary headcount in some areas, but in others entirely new avenues of employment are opening up. The Internet of Things is sending and receiving unprecedented amounts of data from everyday objects – everything from the driverless car to the central heating at home.

Employers need to know the difference between value added by automation, and value added by humans

All this data can be used to define and refine the user experience, gifting their creators with increasing knowledge of customers’ habits. That’s why interest in data scientist roles has been steadily on the increase since 2013.

While recruiters search for the best way to enhance the potential of new technology, there are also steps they can take to make sure new hires aren’t left in its wake.

Recruiting for skills that are still part of AI’s blind spot – and may always be – can be a challenge when there are less familiar metrics for success such as qualifications and career history. But knowing how to find those best suited for the post-AI workplace is a challenge to be relished.

The automated workforce

A study by the McKinsey Global Institute shows that AI is predicted to cause a seismic shift in the way certain skill areas are deployed in the workplace.

By 2030 there will be a large difference in terms of hours spent on skills in areas including physical and manual, basic cognitive and technological. It’s led to concerns that existing talent pools are exhibiting shortcomings in their digital abilities that employers need to address.

This short-sightedness arguably runs all the way up the ladder; a study by Alvarez and Marsal shows that decisions on digital at board level could be hampered by an analogue approach taken by older members of staff. The analysis recommends board restructuring to bring in younger, tech-savvy representation.

But the effect on the coming-of-age proportion of the workforce is thought to be the strongest. An ONS report says that 20-24 year olds are the most at risk, with nearly 16% of the age group feeling the effects of automation in the workplace. So what can be done to ensure that graduates and young workers are best equipped for these changes?


Focus on soft skills

Analysis of 20,000 keywords across entry-level job postings in 15 industries indicates that the most requested attributes of job applicants fall firmly into various categories of soft skills, with only ‘data and analysis’ (3%) representing a more technical requirement. 

Relationship building (19%) and having a positive and professional attitude (17%) were the most desired skills from the listings, illustrating that employers have begun to grasp the need for skilled communicators and relationship managers over experience with hardware and software. Despite this, there’s strong evidence that technology has a role to play.

According to the McKinsey report, the biggest shift will happen as skills in the technological category go from being the least in demand in 2016 to the most in demand by 2030. The study of businesses in the United States and several European countries including the United Kingdom showed an average of 11% of hours worked in this category, expected to reach 17%.

Physical and manual skills will experience the steepest drop but still remain the most worked category in 2030, while basic cognitive skills including data input and basic processing will drop from 18% to 14%.

Social and emotional skills will rise by almost a quarter of the estimated 119bn hours worked in 2016. This focus on the more abstract or ‘soft’ skills is indicative that human workers will not only survive, but thrive in an increasingly automated environment – provided they receive the support needed to increase their skillset.

The McKinsey study breaks down the social and emotional category into the following skills:

  • Advanced communication and negotiation skills
  • Interpersonal skills and empathy
  • Leadership and managing others
  • Entrepreneurship and initiative-taking
  • Adaptability and continuous learning
  • Teaching and training others

While artificial intelligence drives efficiencies in data processing and manual work, graduates and those entering the workforce should ensure they can demonstrate interpersonal skills. As advanced as AI may be, it can’t emulate the kind of skills displayed by leading managers and communicators.

A successful workplace needs to incorporate both AI advances and human interactions. Robots can do the heavy lifting and basic data collection, but right now it takes the human touch to ensure the work is being done as effectively as possible. Sometimes there’s no substitute for gut instinct despite what the data tells you.

Traditional ‘hard’ skills may be important, but as automation continues to impact the availability and types of work on the market, a focus on developing employees’ soft skills will arm them with the ability to adapt and cope with the ever-shifting goalposts of AI-inspired working.

Employers need to know the difference between value added by automation, and value added by humans, and make sure they can derive the best results from both.


About the author

Jonathan Fitchew is CEO of Pareto Law.


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