Sayed is an Information Technology veteran with over 20 years of successful experience in national and global level technology operations, cloud technologies, product development, bringing innovative technologies for business, and business ideations through Digital transformations.

Companies form HR departments to handle hiring and compensation. Soon, HR leaders will 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 psychologists 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 Tensor-flow 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 organisation. While a Fortune 500 company will probably require some in-house data science activities, smaller companies can work with HR analytics solutions.

Despite these challenges, numerous companies are rolling out HR analytics programs and highlighting their successes such as the ones below:

Survey Analytics
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 analyse 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 Digitisation or RPA
Operational HR activities like compensation and benefits will be almost entirely automated thanks to digitisation. 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 digitisation, Robotic Process Automation (RPA) bots will take over repetitive human jobs and digitise 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 and HR digital transformation articles 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?

Candidate Outreach
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 personalise timing, medium and message of your candidate outreach.

CV Filtering
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, the 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.

Candidate Engagement
Engaging candidates is time consuming however without it, employees are left without any information at a stressful time. AI-powered recruiting chatbots can send customised, automated messages to ensure that employees are informed at the right times, minimising unnecessary anxiety and ensuring that qualified candidates remain engaged.

AI Can Help with Employee Training
According to Oracle’s Future Workplace report, 64 percent of employees reported they would trust a robot over their manager for advice. Deploying an AI virtual mentor can provide personalized assistance throughout training by having access to all enterprise files and policies which can provide quick answers to employee queries.

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 implement at their own discretion.