How AI Is Influencing Human Resource Decision-Making

By: Raghav Poojary

Artificial Intelligence is the most prevalent and revolutionary technology that exists in today’s time as it continues to change how industries and different businesses operate. With the help of AI, companies are transitioning the repetitive and tedious processes into automated functions that augment human capabilities and amplify actions. In Human Resource, AI is proving to be an essential tool that is empowering HR leaders with deep, analytical insights to make data-driven decisions, reduce human bias and become true strategic partners.

According to an Oracle-Future of Workplace report, 64% HR practitioners would trust a robot over their manager for advice. The future of HR is an integrated approach where the human mind and machine learning come together to optimize the processes. Integration of AI in the Human Resource department will ensure a flawless experience for the candidates and existing employees.

Here are some ways AI is transforming HR and how it is impacting HR decision making.

Talent Acquisition

AI is simplifying the talent acquisition process to a great extent. Recruiters spend about one-third of their productive time sourcing talent and identifying the best candidates for a given role. Integrating AI/ML into the Applicant Tracking System automates the candidate sourcing and screening process for repeat requirements. Here’s how it works:

• The ML component enables the system (ATS) to learn from the recruiters’ shortlisting pattern for specific requirements
• When sourcing for similar requirements in the future, the AI recommends the best matches from previously sourced profiles stored in the internal database, ranking them according to relevance to the job role

However, to improve the accuracy of AI in recommending matching profiles, the recruiters must ensure that they source/shortlist only the most relevant profiles for a particular requirement, so the AI doesn’t incorrectly learn from their mistakes. If implemented with care, the AI will not only save costs and reduce time to hire, but also help to remove human bias in the screening process and make data-backed decisions in talent acquisition.

Furthermore, AI can predict the future performance of a potential candidate by referring to past credentials and assessment/performance scores which will be the input data for the AI. With the help of simple artificial neural networks, recruiters will be able to make more informed decisions in talent acquisition.

Employee Engagement

Nurturing a warm relationship with an employee is crucial throughout the HR process, right from the first contact till the employee exits. AI-driven chatbots can serve as efficient employee care platforms that answer simple queries and offer the primary level of HR support, allowing the HR personnel to focus more on their core job role. This will save a lot of time and effort and boost employee experience by providing them with the immediate attention they seek. When employees have complex issues, the AI can initiate manual intervention by knowing when to involve HR reps and make appointments and organize meetings.

AI-driven chatbots can also handle early interactions with candidates, such as requesting their CVs, gathering information on their experience, skill sets, etc. and following up with shortlisted candidates for scheduling interviews. Integration of AI into chatbots has allowed for HR personnel and bots to work together to greatly improve the overall candidate/employee experience and promote retention.

Employee Training

The COVID-19 pandemic has pushed most organisations in realizing the pressing need for upskilling/reskilling and implementing L&D initiatives to promote continuous learning at the workplace, thus building a future-ready workforce.

By integrating AI into Learning Media Systems, we can create personalized learning paths for employees based on their existing skill-sets and the skill gap needed to be fulfilled. The AI can also recommend training programs to employees by analysing what courses other employees in similar job roles are taking, also considering the ratings they have provided for those courses.  It works around the same concept as in OTT media platforms like Netflix, i.e., by generating recommendations for users using ML.

Advanced People Analytics

Analytics has been around  for quite some time now, but the advent of big data and AI is helping organisations to interpret large data sets and create predictive models for improving decision making and driving results today and tomorrow. The blend of these technologies shall drive the recruitment process in future. HR leaders around the globe are using big data and AI to track and predict future trends w.r.t. hiring, performance, productivity, attrition and org pyramid in terms of age, gender, geography, workforce demographic, etc.

Most importantly, speed is the essence of recruitment in today’s employment scenario. The need to hire top talent before other competitors do is vital, and using analytics to optimize recruitment processes is the way forward. Many established companies, such as Unilever, are already using algorithms and analytics to draw conclusions from people’s data and identify top talent before contacting them. Furthermore, AI is facilitating the management with deep insights into employee satisfaction levels, predicting attrition and correcting systemic or departmental inefficiencies before they become problematic and prove expensive.

Emotion AI and Its Future in HR

Emotion AI is still in its nascent phase.  When fully evolved, it can measure, understand and simulate human emotions. Emotionally intelligent bots can analyse micro-expressions that are too subtle for us to pick up. Though it is too early to comment on potential use cases in HR, some applications of Emotion AI in recruitment may include:

• Conducting interviews and formulating reports to determine the candidate’s cultural fitment for a given job role
• Capturing the emotions of individuals when asked to detail out real-life experiences
• Gauging ingenuousness and transparency in responses by analysing voice and text notes
• Understanding the emotional stability of an individual when exposed to various scenarios
• Analysing various data points to gauge the credibility of the candidates
• Eliminating biases over time by interpreting thousands of scenarios, identifying matching patterns and formulating accurate reports

Conclusion

AI systems are only as good – or as bad, as the data they are fed and trained on. Incorrect use cases will lead to inaccurate machine learning and erroneous automation, which may gravely impact the hiring process and even bring direct losses to the business. If HR leaders can be precise in identifying what problems can be solved by AI and accurately inputting the required data into the algorithm, AI can help reimagine the way HR works and enhance the role of the HR function to be the strategic partner in the organisation.

(The author is Vice President Business Operations & Process Automation at First Meridian Business Services and the views expressed in this articles are his own)