
It’s hard to talk about any business today without artificial intelligence entering into the conversation. It is starting to spread everywhere, and pace of adoption is accelerating. Product development, customer experience, sales and marketing, distribution, supply chains and many other business functions are adopting AI in some shape or form. Hiring and recruiting industry is not far behind and we are starting to see some interesting applications of AI in this space.
In the recruitment and talent acquisition industry, AI is helping hiring managers and recruiters to identify candidates who match their specific requirements, it simplifies the recruiting process and hyper personalizes the user experience of both recruiters and candidates. Using AI frees up recruiters from spending time on mundane tasks and allows them to focus on more value adding tasks such as interviews, networking, compensation planning etc.
Recruiters and hiring managers are increasingly using AI to do initial screening, reading body language to predict your on job behavior, analyzing your interview answers to assess the depth of your knowledge and even coming up with interview questions specifically tailored to the interviewee. Imagine an AI program which is determining who on the internet to show the job opening. In 2020 more than 60 percent of hiring managers and recruiters on the Linkedin platform were found to be using AI to increase their efficiency and productivity.
AI is being used throughout the life cycle of a hiring process
Creating Job Descriptions: Many recruiters and hiring managers struggle with writing the perfect job description. Most of the time human written job descriptions fail to attract the right candidates and repel the wrong candidates. AI enabled tools such as Seattle based Textio are solving these problems using AI augmented writing. Textio tool gives hiring manager an instant access to the most extensive and up-to-date language performance data in the industry, in real time as they write the job descriptions. Textio claims that their tool helps stop the guessing game and write thoughtful, inclusive, on-brand content quickly and confidently.
Job Postings: All major jobs platforms such as LinkedIn, Ziprecruiter and Indeed are using AI extensively to maximize the effectiveness of hiring campaign. These platforms use sophisticated AI programs to match the right candidates with the given job description and only show the posting to those candidates. Some of these platforms are also scoring the candidates based on their fit and likelihood to respond to the posting. Pandologic.com provides an AI platform which automates the entire job advertising process and uses advanced algorithms to manage bids and budget allocations.
Initial Screening: Recruiters and hiring managers waste a lot of time sorting through the ocean of resumes they receive in response to the job postings. Keyword based filtering does not work any more as candidates have figured out ways to defeat the keyword bots. AI is now solving the problem using natural language processing which goes way beyond the keyword search but instead focus on the context in which those keywords are used. Some new age tools such as datascholar.io solve this problem by offering AI enabled testing to weed out the unwanted candidates. Datascholar.io platform however focusses exclusively on data science and data engineering postings, if you are hiring of other roles then there are many general testing platforms available online but most of them are not AI powered.
Candidate Management: Applying for a job can be a very bad experience for candidates which could result in tarnishing the image of the hiring company in the long run. In recent surveys it has been found that more than 55% of applicants form a negative opinion about the company if didn’t hear back from the company after submitting an application, whereas more than 65% of applicants form a positive opinion about the company if the hiring company engages with them throughout the recruitment process. Engaging with each and every applicant is not feasible for any hiring company, this is where AI enabled recruitment chatbots have started to shine.
These intelligent bots are capable of asking questions based on the job description, answering candidates’ questions and providing feedback and status updates. Xor.ai is one recruitment chatbot platform which provides candidate screening, scoring, and then schedule interviews right on your calendar.
Interviews: AI engines can structure a line of questioning based on the candidate’s resume and job description. Although not fully mature yet, this capability would eventually replace the need for a human being to carry most of the face to face interviews saving the hiring managers a ton of time and energy. Where the AI technology has matured for commercial usage is the facial analysis of the candidates during the interviews and when combined with real time speech analytics, its already showing very good results. Hirevue has one such product which the AI engine assess applicants against its database of thousands of facial and linguistic data points. These are compiled from historical interviews of successful hires. Many linguistic elements they look at include criteria such as candidate’s voice tone, use of passive or active words, sentence length and the talking speed. The thousands of facial features analyzed include eye brow movements, eyes movements, lip tightening, chin raising and smiling.
Final Decisioning: Deep learning algorithms today are capable of looking at hundreds of signals about the candidate collected during the life cycle of the recruitment process and then combining all the features to predict likelihood of future success at the job. AI algorithms then score and rank all the candidates and make their final recommendations. This is pretty amazing but implementing such decisioning tool can be very expensive and is suitable only for large sized companies deploying the solution at the enterprise scale. These AI algorithms can also track the actual performance of hired candidates over a period and then create feedback loops to make itself smarter overtime.
Conclusion: Its clear from the discussion above that AI is already here and its learning at a very fast pace. It learning about each phase of the recruitment cycle and making itself smarter with each posting, with each candidate and with each interview. Only time will tell which way it goes and how fast it gets there but I give it at the most 3 years when more than 99% of the recruitment will be done by an AI program. Pretty amazing right?