Data analysis is an essential part of current trends in business. And Artificial Intelligence (AI) is at the root of that data analysis and its application to management and strategy. Integrating AI software into the recruiting and talent management process has the potential to increase both effectiveness and efficiency, in addition to many other benefits. Early adopters of such software have already seen impressive returns from AI integration.
But human resource (HR) management has traditionally lacked data fluency. Far too often, HR departments are slow to incorporate data analysis and AI software. And many who have embraced a certain degree of data analysis-based recruitment through applicant tracking systems (ATS) or human resource information systems (HRIS) still seem skeptical of AI for recruiting.
The need for data fluency and AI integration in HR processes is a popular thread for today’s HR leaders. Advanced academic programs such the University of Northern Colorado’s online Master of Business Administration (MBA) with a Concentration in Human Resource Management are including the study of data analytics and data-driven decision-making in their coursework. Through such programs, HR professionals can gain the knowledge and fluency they need to effectively use AI for recruiting.
What Is the Importance of Data Fluency for HR?
HR already deals with vast amounts of data, including information from resumes, applicant data, job descriptions, job performance and quality of hire, retention and turnover, etc. Much of this is currently digitized and electronically organized (using an ATS or HRIS), making it more accessible and usable.
But the bulk of HR data is still gathered and processed in an analog fashion, gleaned from hours and hours of screening, interviews, shortlisting, and rereading files and interview transcripts. Obviously, this burns time. Ideal.com reports that recruiters spend an estimated 23 hours on screening alone to fill a single position.
How Can AI for Recruiting Positively Impact This Process?
Data analysis can significantly expedite this process. AI software has the potential to free up a great deal of time recruiters generally spend on repetitive, high-volume tasks. This time could be better spent focusing on the person-to-person aspect of recruiting, hiring and training, not to mention HR functions after hiring and throughout employment.
Quality of hire, retention and turnover are essential focuses of HR as well. Effective AI analysis of data on past hires, applicant data, employee performance and turnover can help quantify the quality of hiring outcomes demonstrated through key performance indicators (KPIs). The predictive potential of this level of data fluency and application can be useful in the recruitment process as well as for creation of HR strategies that effectively promote employee retention.
AI also has the potential to minimize or eliminate bias in recruiting. This can promote the development of a diverse, talented workforce — an essential component of ethical business practices and success in the ever-diversifying global culture and economy.
How Does AI for Recruiting Accomplish This?
AI for recruiting intelligently automates aspects of the recruitment process. AI software can be applied to various stages of this process, from sourcing and engaging potential applicants through initial screening and applicant assessment. AI technology can be used to collect data from a multitude of sources — resumes and automated interviews as well as information gleaned from sources such as social media.
With such broad information on job skills, past performance and desired traits on and off the job, AI can help illustrate an applicant’s job matching potential far beyond their basic resume. AI for recruiting can effectively broaden the applicant pool at the same time as it narrows that pool to the most highly qualified individuals. Plus, AI can be programmed to selectively remove information from job descriptions, application questions and resumes such as age, gender, race or other such factors. Omitting this information through the screening process can help avoid unconscious or conscious bias from the recruiting process.
In addition, AI can augment existing recruiting workflows such as applicant tracking systems. This can result in streamlining the recruiting workflow.
Of course, AI for recruiting is not without potential pitfalls. Being based on machine learning, AI software has the potential to learn biases from programmers and the corporate mission, culture and past hiring practices. HR and AI vendors alike must stay vigilant in eliminating any potential learned biases that may arise.
Yet, with the vast potential of AI and the demand for HR personnel to accomplish more with fewer resources, AI for recruiting is becoming a must. By advancing data fluency and integrating AI, HR leadership can improve the performance and efficiency of their own department as well as the productivity of their company as a whole.
Learn more about UNC’s online MBA program with a Concentration in Human Resource Management.
Sources:
Ideal.com: AI for Recruiting: A Definitive Guide for HR Professionals
Forbes: The Rise of AI in HR: Nine Notable Developments That Will Impact Recruiting and Hiring
Workforce: AI Is Coming — and HR Is Not Prepared
AIHR: Human Resources KPIs: An In-depth Explanation With Metrics & Examples
