Artificial Intelligence (AI) is a hot topic in 2018, with pundits from both the positive and negative camps predicting a paradigm shift in employment and productivity rivaled only by the industrial revolution. From robotic task execution to predictive algorithms, various strains of AI are already disrupting the workplace. Rapid advances in Machine Learning (ML), such as facial recognition, natural language understanding and computer vision, are increasingly in use in fraud detection, market analysis and medical diagnosis.
According to Forrester forecasts, automation will eliminate 17 percent of US jobs by 2027, offset by the growth of 10 percent new jobs from the automation economy. A McKinsey & Co report released recently projects that as many as one-third of American workers may need to find new lines of work by 2030.
The Organization for Economic Co-operation and Development (OECD), a Paris-based world research institution, has hosted symposiums and published research in an effort to analyze the impact of AI on labor markets. It predicts that there will be a further polarization of low-skilled and high-skilled jobs. Contributing researcher, Stuart Elliot of the US National Academies of Sciences, Engineering and Medicine, notes that only 11% of adults are currently above the skill level that AI is close to replicating.
For those in Human Resources, it’s difficult to assess the impact of AI/ML. Fifty-seven percent of respondents to a recent Capability Café survey said they know very little about AI/ ML and how these technologies could change the way they do business.
Predicting how ML will affect a particular job or profession can be especially difficult because Machine Learning tends to automate or semi-automate individual tasks, but jobs often involve multiple tasks, only some of which are amenable to ML approaches.
So how do you build a team equipped to thrive with AI emerging technologies?
The McKinsey report suggests a range of proactive measures to address worker transitions brought about by these technologies. The report’s suggestions include offering mid-career job training and enabling worker redeployment. These changes will challenge current education and workforce training models as well as business approaches to skill building, according to the report.
A side benefit to offering mid-career job training is that it will help proactive companies retain the talented workers who will be the most adept at working with AI. Employees who are highly adaptive, flexible problem-solvers will embrace change and a chance to learn new skills, and they will value employers who offer them the opportunity to do so.
Kay Durkin, founder of technical recruitment firm Phoenix Partners, says in addition to creating a corporate culture that is inviting to innovators, companies should also be screening new hires for adaptive attributes.
“In STEM recruitment, companies have become very focused on the “ready-to-work” hard skills candidates possess, and with good reason. But to future-proof our technical workforce over the long term, we must also evaluate candidates in terms of markers that indicate adaptability and creative problem solving. Many hard skills may become automated or obsolete. Adaptive and creative decision-making together with technical savvy will remain in the realm of human contribution,” she said.
In addition, employers will need to pay special attention to the transferrable skills sets of candidates, and dedicate more resources to employee training and development.
Do you need help finding adaptable employees who will thrive with AI? Talk to Phoenix Partners.