Digital-first for better work: How is AI impacting the world of HR?
We at Weekly10 were recently fortunate enough to be able to take part in Wales Tech Week, where our CEO Andy and I gave a talk on the ways in which AI is shaping the future of HR. This includes how we ourselves use machine-learning to provide richer employee engagement and predictive people analytics to clients from the data we collect via our employee check-in.
There are numerous applications for AI in HR that can be leveraged right now to help HR professionals improve workplace efficiency, experiences and impact the bottom line.
Will artificial intelligence make everyone redundant?
When we think about artificial intelligence, the idea of machines coming along and taking all our jobs is a common one. But how likely is it, really?
It's true that AI in HR and other areas can perform a lot of repetitive tasks and functions quite quickly, that might otherwise take human employees hours to complete. According to the Future of Jobs report 2018 by the World Economic Forum, predicts that as many as 75 million current jobs will be displaced and potentially made redundant as artificial intelligence takes over more and more tasks in the workplace.
But don't worry too much, because the report also found that this should be more than offset by the creation of approximately 133 million new roles as a result of incorporating machine learning technologies. It's also worth mentioning that rather than being made redundant, many roles could be up-skilled so that employees can incorporate AI to streamline tasks and make jobs less stressful.
The benefits of using AI in HR
We've previously highlighted how AI can benefit law firms, but the legal sector is far from the only one with something to gain from machine-learning. There are plenty of ways organisations stand to benefit from using AI in HR.
Artificial intelligence can streamline various tasks, allowing HR professionals to focus on aspects of the job that require a human touch. Some of the ways AI in HR can benefit an organisation and improve employee experience include:
- AI in HR will automate time-consuming or less important tasks: Machine-learning algorithms can be trained to perform all sorts of functions. They're particularly good at taking tasks that employees find mind-numbing and time-consuming, and doing them incredibly quickly with little margin for error. By using AI to automate certain processes, HR professionals can streamline their work and free up time for the important stuff.
- AI can improve data collection and analysis: One of the most useful applications of artificial intelligence is its ability to enhance research. Language-based machine learning algorithms can be used to refine things like survey questions based on sentiment analysis and other data. AI can even spot connections that humans might miss. In a purely scientific example, a machine learning algorithm analysed research papers from 2009 and was successfully able to "œpredict" an incredibly effective thermoelectric material that was only discovered in 2012.
So imagine the level of insight such an algorithm could have for workplace analysis. With enough data, HR professionals may be able to predict how different circumstances affect employee behaviour.
- AI will help to provide a more personalised employee experience: With artificial intelligence streamlining more menial tasks, as well as improving the level of insight that HR and business leaders have about their employees, it can better enable organisations to treat their employees as individuals. Different people have different ambitions, needs and systemic barriers to consider, and machine learning can ensure you take an informed approach to supporting your employees.
The applications of AI in HR technology
- Human capital management: AI tools can streamline various aspects of workplace coordination using simple algorithms to manage a lot of the admin that goes into organising people. A good example would be Zenefits or SAP. These services provide a range of HR tools for things like talent management, workforce planning and payroll.
- Employee benefits: This is another service offered by platforms such as SAP or Zenefits. You might be tempted to just fall back on some financial incentives, but those aren't always as effective as you might think. There are a wide range of potential benefits for organisations to offer that employees tend to find a lot more useful.
But when you're offering everything from monetary rewards and flexible work options to finance management services and flashy company cars, it can get quite difficult to keep all those plates spinning. This is another area where AI in HR can really boost efficiency by automating your organisation's employee benefit systems, as well as increasing room for personalisation to suit the needs of individuals.
- Recruitment: Artificial intelligence can help refine both your recruitment and interview processes. For example, job listings can be improved with Textio. It's a service that uses machine learning to improve the language in your job listings by removing unconscious biases and making selecting the best wording to appeal to prospective applicants. Services like Bullhorn offer fully-fledged recruitment software that uses "œpredictive intelligence" to provide actionable recruitment insight.
- Learning and development: Implementing AI in workplace learning and development can significantly improve the way an organisation provides training to its employees. Machine learning can adapt resources to different learning styles, transcribing videos for more textual learners, or extrapolating text into a display for visual learners. AI-driven training courses can also break away from the rigid format of identical Q&As, instead making adjustments to provide appropriate challenge to each individual.
- Employee engagement: AI can assist in monitoring employee engagement, as well as developing strategies for improving it. Machine learning algorithms for tracking engagement typically take the form of people analytics as part of an on-going feedback process. When it comes to specific examples, look no further, because that's where we come in.
How Weekly10 uses artificial intelligence
Here at Weekly10, the core of our platform is the weekly employee check-in. It was created based on the idea that traditional employee surveys are ultimately only a snapshot in time, which has little beneficial insight for long-term behaviour change.
So our check-in system takes the idea of more frequent feedback, condenses an "˜employee survey' down to a few questions, and makes it as lightweight as possible and as regular as you want. Like our name suggests, we'd recommend checking in every week to provide a flow of on-going, real-time data - research has found with employees wanting more frequent feedback in work, weekly is the optimal, realistic cadence.
The first place you'll notice our AI is during question setup for an employee's check-in. Our question-based machine-learning algorithm will recommend questions (or edits to questions) based on the data from past check-ins, as well as what's been found to be effective for other similar businesses.
This is just one way we use people analytics at Weekly10, with the largest area being in the analysis we are able to run on check-in data.
In particular, our platform gets a lot of use out of sentiment analysis. This form of analysis looks at the language that employees use in their updates, as well as the context around it, to provide "˜true meaning' and actionable insight.
Our 10Pulse employee engagement score is derived from the sentiment analysis output, meaning HR and business leaders have access to a qualitatively driven, robust engagement metric that can be tracked over time and across groups (e.g. occasions, different teams/departments) allowing for great benchmarking ability. For more information on HR best practice and the latest employee engagement strategies, visit the Weekly10 blog.