5 Areas That AI Continues to Make an Impact on HR
10 February 2020
One of the most talked-about and controversial trends in the future of HR is Artificial Intelligence. AI and automation have influenced almost every aspect of our lives (and not just Spotify playlists), and HR isn’t an exception. Sometimes we don’t even realize how an AI-powered software plays a massive role in shaping our decisions.
As a founder of a human resource software company, I have worked with a long list of companies with different levels of involvement in AI and automation in their human resources department. Here are some key areas where AI is currently impacting HR and will make a massive revamp in the near future.
Recruiting and candidate matching
One of the areas in HR where AI has significantly revamped the process is candidate matching for a job. With AI, appropriate candidates are being identified for open roles. The process works vice versa as well, with related jobs being recommended to job hunters according to their search history and pattern.
AI-powered solutions help companies in the shortlisting process, screen profiles, and interact with prospects before competitors. Application trackers from the employer’s database can use many keywords, text analysis, and other data points that use AI to search and sort with ease. Because of this, time is saved on manual tasks, and organizations can devote time and resources in providing superior candidate experience. In the end, AI also helps to create a positive brand image for an organization as most prospects get appropriate replies and not left stranded, unnotified, and frustrated.
Every new employee brings with themselves a fresh new perspective and something unique to the table. Similarly, they also bring with themselves different learning preferences. Onboarding and orientation software doesn’t always support these preferences. AI can be a savior here by providing personalized onboarding according to the existing skillsets and preferences. It’s the same as hiring a unique coach for every new employee. It can make onboarding and orientation productivity rates go through the roof. And the best part is that the more data collected, the more efficient the whole process becomes.
According to Shelton Blease, the director of HR operations for Lucas Group, many administrative tasks involving oodles of paperwork have been put away from everyday hassles. The most important part of an AI is its ability to adjust its setting according to the data presented. An intelligent system can schedule a meeting and grant proper permissions to understand a role better. That translates into a 24×7 onboarding process as well as faster and more efficient integration.
Bridging the skills gap
Identifying gaps in the current workforce and appropriately starting an efficient recruitment or talent development campaign was and is a headache for human resources. Not only that, organizations have to identify whether the gaps are practical or not due to unrealistic expectations.
AI handles the difference between the skills expected and skills possessed by the applicant or employee. Predictive analysis has enabled to identify the link between business goals and job description. Being able to predict which new employee is going to be a great fit according to past cultural fit and background experiences, which have been a great success, goes a long way in the efficient development of the organization.
Similarly, AI can play a massive role in the training of employees too. AI can suggest the optimal learning routes and techniques for the development of employees and the organization as a whole. An interesting example can be of Iris. Iris was developed by a technical training provider company called PluralSight, and it conducts quizzes and asks difficult questions. According to the feedback collected, it uses natural language processing and machine learning to recommend content based on your skills. It can help suggest ways to train current employees to the missing skillset rather than going for a new employee.
We have seen in the past few decades how employee engagement has been evolving. It all started with top-down annual employee engagement surveys. The 80s was an era of yearly surveys, benchmarks, and comparison of annual engagement growth. It all started when the internet was still in its nascent stages, and all the surveys had to be paper-based. The result? They were interesting, but taxing, slow, and not very actionable.
Then came the era of pulse surveys. It was the ability to conduct frequent surveys whenever the organization desired. Organizations are known to conduct surveys as frequently as weekly. Pulse surveys are an essential step in employee engagement because it can be more actionable and real-time.
What AI can do next is interesting. AI can use the data proactively and feed the results and recommendations directly to employees. First surveys are done for every employee, just like pulse surveys. Then the results are compared according to research done by psychologists and previous trends of what worked and what didn’t for the organization. And finally, the review or feedback is given directly to employees. Every feedback received would be unique suggestions to change their behavior in the workplace, keeping in mind the overall increase in employee engagement.
This leads us to an example of Humu, a company focussed on individual changes for the improvement of an organization. Humu’s product is based on something they call a nudge engine. It uses a set of rules, hints, tips, and suggestions to provide real-time solutions to behavioral adjustment.
Predicting turnover is one of the most time-consuming aspects of the human resources department of any company. Manual prediction of turnover is not only time consuming but ineffective too. Using advanced AI conversational analytics like sentimental analysis, the system can identify whether the communication between managers and their employees are engaged or disengaged. A disengaged employee is likely to be an addition to the company’s attrition statistics.
A recent CNBC article stated that an inhouse IBM AI program could predict with 95% accuracy which employees were about to quit their job. This kind of data is of the utmost importance for HR professionals to optimize the talent operations of their organization.
Managers can leverage this data and keep a check on employees for signs of burnout, which is often a significant cause for turnover. AI can enable managers to understand the amount of workload an employee is taking and efficiently delegate it to improve engagement in the workforce.
Instead of fearing the loss of jobs due to AI, HR leaders should embrace the evolution that is taking place. At least in HR, AI is set to boost engagement and help professionals to run an organization more efficiently.