Companies form HR departments to handle hiring and compensation. Soon, HR leaders find themselves tackling, retention, performance management, culture and a myriad of other responsibilities. And now CEOs are asking them: What’s your AI strategy?
The short answer is: AI will transform HR creating a lean department that is less intrusive yet more impactful. But how?
HR analytics is a must for any large company
Software has eaten the world and now AI is eating software. The first application of AI is advanced analytics, enabling companies to have instant access to insights. HR analytics is also the first AI use case HR professionals need to explore.
However, HR analytics comes with its challenges. HR has long been a field dominated by psychologist and liberal art majors. HR departments mainly focused on managing wage and benefits costs on the quantitative side. As companies grew, HR started focusing on qualitative aspects of a company like culture and motivation. However, now we are asking these departments to improve their data quality, complete data science projects and understand their workforce. This is a major challenge. How can HR tackle this?
An alternative is to invest in off-the-shelf data science tools like Google Tensorflow and hire data scientists to look into patterns in HR data. The other alternative is to work with HR analytics vendors who can set up advanced analytics systems for your organization. While a Fortune 500 company will probably require some in-house data science activities, smaller companies can work with HR analytics solutions like the ones we list on our guide on HR analytics and our latest blog article on the topic.
Despite these challenges, numerous companies are rolling out HR analytics programs and highlighting their successes such as the ones below:
Free text surveys are the survey format that allows employees the most freedom of choice. However, they are also notoriously hard to evaluate as manual labor is necessary to analyze responses.
As WSJ reports; SPS Companies Inc., a steel processor with 600 employees and First Horizon National Corp. , a regional bank based in Memphis, used AI powered text analytics services to analyze input of their employees. At First Horizon National Corp. such analysis required 360 man-days of work to examine 3,500 surveys. Now it takes a few days and accuracy has been reported to be satisfactory.
Operational HR activities need to be automated with digitization or RPA
Operational HR activities like compensation and benefits will be almost entirely automated thanks to digitization. Modern cloud or on premise solutions provide paperless and automated solutions. However, especially for large companies, legacy systems can prevent such efforts as they are difficult to integrate with.
Where legacy systems prevent full digitization, Robotic Process Automation (RPA) bots will take over repetitive human jobs and digitize processes. RPA bots can be trained like employees and perform repetitive actions with ease while recording every single action they complete. Check out our comprehensive guide on RPA for more info.
Data driven hiring is possible thanks to big data
Hiring is essentially a search problem. Hiring managers try to answer the question “Which employee is the best fit for my company?”. It is an especially hard problem for humans as we have our own innate biases which impact our judgement which lead to injustice and inefficiencies like racial or gender pay gaps. So how can AI help?
First of all, AI is not a silver bullet especially when it comes to overcoming existing biases against race or gender. However, there are a number of areas where AI provides solutions increasing your HR team’s efficiency and effectiveness:
Like any advertising activity, it is important to reach your candidates at the right time, through the right medium with the right message. With the advance of digital marketing, so much data is available to personalize timing, medium and message of your candidate outreach.
CV filtering in most companies is time consuming and subjective. Fear of missing a good resume due to a careless misclassification haunts the best recruiters. AI systems use online data combined with data presented in the CV to create a holistic profile of the applicant. Based on best practices established in the company, system can filter CVs to minimize manual effort.
Innovative solutions are also rising for specific verticals. AI-scored programming challenges for engineers like Lytmus, automated video interviews for blue-collar positions pre-filter candidates and save time for your team to focus on more value-added challenges of HR.
Engaging candidates is time consuming however without it, employees are left without any information at a stressful time. AI systems can send customized, automated messages to ensure that employees are informed at the right times, minimizing unnecessary anxiety and ensuring that qualified candidates remain engaged.
If you are interested in applying these solutions and want to learn more about vendors offering these solutions, feel free to check out our extensive guide on hiring.
AI can identify employees who are likely to churn
Once candidates are hired and trained, they become a valuable resource and churn becomes a concern. Even without any big data, good managers could spot churn. Showing up late to work in a suit and an improved Linkedin profile are good predictors of churn. These days HR managers can rely on AI systems rather than such old-school techniques that managers implemented at their own discretion.
With all these tools at their disposal, the stakes are high for HR leaders to deliver renewed HR departments that are both more efficient and more effective. We are constantly identifying new AI use cases and vendors, take a look at the latest AI use cases in HR for more information.