Let’s say you see a job advertisement. You click through and read the job description. The role seems interesting and you email your CV. A couple of days later, you are notified that you are shortlisted, and an interview is scheduled. You also take an assessment test. Then, you get interviewed. The following week you learn that alas, you are not selected. But you get a nice and polite email wishing you all the best.
Seems like a pretty normal thing, right? But would it surprise you if as a job seeker you did not interact directly with any real humans during this entire process? That algorithms and automated tools orchestrated everything? You may think that this scenario will play out in a distant future. But in reality, there’s technology that already can automate all of the above steps — displaying targeted ads, writing job descriptions, screening CVs, scheduling interviews, dissecting video interviews, conducting psychometric evaluations and more. And such AI is being used by many companies around the world.
What I’ve described is just one hiring scenario, but there is a lot of interest in leveraging AI across different HR domains. A lot of start-ups are funded, acquired and existing HR Technology vendors introduce AI-features in their system. So, a practical way to make sense of AI in HR is to first get an overview of the HR Tech stack.
The HR tech landscape is quite large with thousands of vendors across hundreds of categories, but you can think of them as three broad groups of applications — talent acquisition, talent development and talent management. Of course, each of these high-level categories has further sub-categories and so on. The framework roughly follows the employee life cycle with an organisation, from identifying potential candidates till their separation/retirement.
The use of AI depends to a large extent on the HR tech category and let us see how and why AI is being used in each of these categories.
Talent management
In this category, AI is used to make HR operations more efficient. Even in the largest of organisations, HR teams are usually lean, and more of their time than they intend to is spent on routine and repetitive tasks. Automation of repetitive tasks and manual paperwork steps using Robotic Process Automation (we’ll explore what RPA is in a future column, but for now, just think of them as tools to automate standardised, rules-based tasks) is an example. Freed up of such grunt work, HR teams have time to focus on more complex issues.
Talent development
AI is used to enhance employee experience in talent development. For example, employees have a lot of questions about company policies and procedures. They get in touch with HR looking for answers or try to find information on the company intranet. A well-designed chat bot can simplify this experience. Digital assistants can make new employee on-boarding much more engaging. There are also many applications that make training more personalised, relevant, and fun.
Talent acquisition
AI is used for hiring talent. AI-enabled Applicant Tracking Systems can scan the resumes received, automatically rank them and create a shortlist. Video interviewing tools can analyse candidate responses, including their facial expressions and make hiring recommendations. The usage of these and other AI-assessment tools in the hiring process is a grey area. The AI software vendors claim that their systems lead to better outcomes because they are data-driven and help eliminate (conscious or unconscious) human biases.
On the other hand, AI-systems are only as good as the data they are trained on, and HR-AI systems have their own blind spots and can introduce a different set of biases or violate anti-discrimination rules. As a HR manager, you should be able to understand, assess and evaluate the workings of these AI tools before green-lighting them.
Beyond using AI for work, HR has to also play a strategic role for the rest of the organisation. As AI is more widely adopted, it impacts the working of different departments and HR needs to devise a ‘future-of-work’ strategy, plan for employee re-skilling, lead change management, and help employees with career planning. Thus, HR has to wear multiple hats when it comes to AI.
Key takeaways for you as a HR manager
The HR function has traditionally been a consumer of technology, but the future will require HR to be more tech-savvy and think strategically about AI. If you are a B-school student specialising in HR / Organisation Behaviour, consider doing a few elective courses on AI, digital transformation, and statistics.
Being a successful HR leader in the age of AI calls for embracing a data-driven mindset, understanding the essentials of AI, knowing when to use AI and when not to, and preparing the organisation for the age of AI. HR will be even more important than before, but practitioners have to become adept in leveraging AI.