Note to readers: Zoom Out: The Future of Work is a series that chronicles macro changes, trends and real-life experiences that affect the workforce as we tread uncertain times. It is aimed to dig deeper and build a point-of-view around popular and contrarian topics around work.
In a few years, recruiting and hiring will look very different from the way they do today. AI has been rapidly reshaping every function, including HR and talent acquisition, and the tectonic shifts will be visible soon.
You may have already observed the following shifts in the hiring process:
- Sharpening of the job posting process with better, more thoughtful and keyword-enabled JDs written by bots (example: Textio)
- Sorting/matching and pre-screening of relevant resumes with the help of technology (example: Greenhouse, Lever)
- Increase in video interviews that read potential candidate behaviour (example: Talview)
- Technology-led assessments; psychometric tests for hard and soft skills (example: IBM Watson Talent)
Thought Leaders such as Rajeev Menon, consultant with AI-powered recruitment platform Talview, who has 20 years’ experience in Talent Acquisition and Evaluation, hold the view that hiring must become ‘insta’. Here’s a look at how AI can make that happen.
Imagine this: A potential job opening comes up in an organisation. AI parses through the internet and seeks potential ‘ideal’ candidates. The recruiter does not approach a candidate directly, however; AI sends them interesting content about the job opening and the company (as with digital marketing).
Once the prospect has clicked on the content/call to action, a human gets in touch with the candidate and takes the conversation forward (mostly through an interview). In this case, AI has already suggested the kind of offer that would interest shortlisted candidates and how the interviewer should negotiate. This is called insta-hiring*.
Why should the recruitment process take months when AI can help ensure a job offer is rolled out in 24-48 hours?
What will it take for AI to get ‘predictive’?
Data and more data (of course, topped with elegant machine learning and AI). However, data is ever evolving and has to be constantly updated. In its raw form, this data can be generated from résumés and social profiles. However, the problem is that data is not standardised and can open a can of biases*.
Professor Nimmi Rangaswamy, from IIIT Hyderabad, who brings an anthropological lens in understanding the impact of AI, says: “AI is entering a domain that is already fraught with allegations of existing bias. One (optimistic) way to look at it is: AI will remove the human bias involved in hiring.”
Hence, multiple advanced tools like Textio exist that standardise the JD and also eliminate bias as much as possible. But that cannot happen overnight. Professor Rangaswamy says there is ambiguity in how AI will measure or define ‘merit’, ‘hierarchy’, ‘educational qualifications’ ‘pedigree’ or ‘soft skills’ and this is just the beginning. It has to be finetuned further to industries, teams and a particular role, especially when 85 percent of jobs that will exist in 2030 haven’t yet been invented.
Here are some examples of how bias is eliminated:
1 Masking candidate photos and gender
2 Masking location
3 Masking recruiter feedback
4 Masking university/college attended (in some cases)
5 Highlighting skills and certain keywords based on the job description
Many have made a start.
“Our clients are predominantly in the BFSI and IT/ITeS space and so far our product, the Edge Graph, has parsed through 10 percent of the existing data (there are about 34 million profiles and 10 million JDs in IT/ ITeS and BFSI alone),” says Aparna Devi Moola, part of the Leadership Team at Bangalore-based Edge Networks, an eight-year-old AI-based startup in the Talent Management space. She states that while AI is currently far from perfect, it is not an ‘either-or’ choice anymore. The HR function cannot be restricted to being a ‘people-function’ only and has to evolve into a data-driven function that keeps people at heart.
According to Fortune Business Insights, the talent management software market’s size is projected to reach $11.09 billion by 2026. Digitisation helps improve recruitment quality at scale, with economies of cost and time, and is inevitable.
TurboHire, a three-year-old AI-based hiring platform based in Hyderabad has parsed about a million résumés. Aman Gour, Co-founder, Head of Product & Partnerships, believes that “we are currently in a phase of ‘augmented intelligence’ where the tech product is like Google Maps and the recruiter is in the driving seat”. It gives you the desired data; the choice on how to use it is yours. “AI cannot replace humans, but can be a recruiter’s best friend,” says Gour.
What enterprises want?
Many large organisations are either sitting with legacy systems or just beginning to test the waters with a few tools. It takes an extremely forward thinking CHRO to see the bigger picture and start exploring the benefits of technology.
Vikas Dua, an HR Tech Evangelist who has worked extensively in the ITeS space with companies like Wipro and Concentrix said: “I would prefer a seamless platform with a uniform look and feel that can automate the entire recruitment process. It starts with identifying the candidate, assessments, managing the interview process (where the human intervenes), offers negotiation options and then also goes out to roll out the offer.”
Trends that will further define this space:
1. Technology backed personalised job marketing (ensuring that an organisation can attract passive candidates as well). This means that organisations have to work hard on employer branding and marketing.
2. Rise in gig working and specialisation and hence the need for a tighter job fit as there is no leeway to spend time on training.
3. JDs will also change as they will focus on the immediate job at hand rather than potential jobs. A lot is changing and companies will hire only for a particular role with a laser sharp focus.
4. Deep Job platforms. Job platforms have gone from light to layered; from simply matching potential candidates with open roles to adding additional value for employers or job seekers, or in some cases both. Can there be a Netflix-like deep job platform that can help employers shortlist their ‘ideal’ candidate and employees land their ‘dream’ jobs with a matching algorithm?
To conclude, “in hiring, you have to understand that there are people on the other side. You cannot treat people as a résumé and hiring as a robotic process. Including AI or any technology to hiring will be an art and science,” says Nikunj Verma, Cofounder and CEO of CutShort.io, an AI based hiring platform.
(Nisha Ramchandani is Manager Outreach, Axilor Ventures and a writer focussed on Future of Work)