The Real Impact of Machine Learning and Automation on Employees
There is much discussion about the impact of machine learning and automation on employees. It’s understandable that people and businesses are thinking, “What jobs and skills will be available in the next five or 10 years?” Here Christian Foerg, General Manager EMEA Region, Saba, talks to CEO today about the impact machine learning and automation will have on employees in 2018 and beyond.
According to a PWC survey, based on interviews of 10,000 individuals1, 37% [of organisations] are ‘worried about automation putting jobs at risk’ and 74% of employees are ‘ready to learn new skills or re-train to remain employable in the future’. Yet many CEOs accept that businesses that are agile and able to adapt are more likely to succeed. With much talk of AI (artificial intelligence) and the impact on employees and jobs, businesses should prepare to meet the changing needs of employees, enhancing the skills and abilities of people with the use of technology.
Most of the respondents to the survey (73%) believe technology can never replace the human mind. Many employees can see the benefits of automation – the majority of respondents reckon technology will improve their job prospects (65%), but even more (86%) think human skills will always be in demand. Indeed, businesses are likely to get the most benefit from a hybrid approach, combining the skills of its workforce with machine learning and automation. But where should organisations start when it comes to adapting their strategy to capitalise on technology that can help improve and develop the skills of its workforce?
In a recent report, ‘2018 HR Technology Disruptions’2 Josh Bersin identifies productivity, design and intelligence as the three key issues for workforce strategy. Businesses need to make intelligent technology work for them – creating and supporting a modern learning experience for employees, with mechanisms for feedback such as pulse surveys that supply the data for intelligent analytics that support talent management and drive productivity.
Design is at the heart of all this. ‘Design thinking’ is crucial because it helps drive HR technology adoption among employees by making them feel and understand how technology can fit into their regular flow of work and help improve their skills and knowledge so they can perform better at their job. Technology that delivers a data driven, personalised learning and performance management experience plays a key role in achieving this result.
Businesses can use intelligent software to realise the best possible performance and productivity, while giving individuals the tools to develop and specialise their skills, in three main areas:
- Improved performance and engagement. Technology, from pulse surveys to sentiment analysis, can provide business leaders with an improved understanding of employee sentiment and arm them with the data they need to make better business decisions relating to talent programmes. At the same time, employees need real-time feedback and coaching all year long, not just an annual appraisal. If the business is in a good position to respond quickly to real-time data, employees will feel that management is paying attention to them. In addition, collaboration systems can help unearth and suggest useful new connections that an individual employee might make within the organisation based on how individuals interact within the system, with the aim of making workers more productive.
- Enhanced learning and development. Employees want the freedom to learn on their own time and they want to be recognised for formal and informal learning activity. Modern learning systems can provide this. Bersin at Deloitte predicts ‘big things’ for artificial intelligence in learning. For example, he points out that as learners share and access all sorts of learning content to help them in their job, intelligent software can help automatically tag content and create taxonomies to help combine corporate learning content with external learning, such as YouTube videos and TED talks, sensibly and accessibly. Software can deliver relevant content to learners based on their prior experiences, colleague recommendations or corporate productivity targets.
- Intelligent hiring and talent retention. Many HR departments collect basic data such as headcount, promotions, compensation packages, time and attendance to support recruitment and talent retention activities. However, most businesses are simply not using the data available to extract a useful analysis of performance, learning and engagement that will help improve hiring and retention. Effective use of data not only helps current employees work, learn, and grow together, but also creates a responsive learning culture that is attractive to potential new hires as well as engaging and retaining current staff.
The impact of machine learning and automation brings us that much closer to offering employees with personalised recommendations to support their ongoing performance and development. The key in all of this is helping employees understand how technology helps them. Think of all of the ways people interact with technology in their personal lives. Self-service HR systems and conversational voice interfaces will become widely available in the near future. But, the fact remains that these systems are all meant to enhance human performance because the most effective and productive workforce of the future will most likely be a hybrid of human and machine intelligence.
In an article for Wired, ‘Welcome to the Era of the AI Co-worker’, Miranda Katz argues, “We’re not living in the golden age of AI, but we are living in the golden age of AI-enhanced productivity. Call it the First Pass Era. AI is now powerful enough to make a solid first attempt at countless complex tasks, but it’s not so powerful that it seems threatening. For more thought-intensive, subjective work, we still need humans.” 3
In this scenario, enterprises must be brave and bold and maximise human assets. Rather than waste human resources on repetitive tasks, it is crucial to take a strategic view of apply intelligent technology to talent management programmes to help people develop the skills they need to help drive breakthrough business performance.
