AI Headhunters & Tech Trends in Global Talent Recruitment
There’s an old adage, “good help is hard to get,” that is making something of a comeback in today’s increasingly dynamic and competitive global human resource industry. In 2016, the HR industry’s total operating income reached €491 billion, while 2007–2016 CAGR was about 9 percent. Flexible labour accounts for about 71 percent of modern market share, 20 percent comes from management service providers, 8 percent from high-end talent search, and 1 percent from recruitment process outsourcing and specialized services.
Recruitment and staffing are challenging areas that have been getting the most market investments. There are numerous derived services and platforms catering to recruiting: headhunters for high-end talents, background investigation services, consulting firms, and of course the popular online recruitment platforms such as LinkedIn and Glassdoor.
According to 2019 Deloitte Global Human Capital Trends Survey, over 80 percent of corporate survey respondents expect to see an increased use of technology in recruiting sourcing/outreach, candidate screening, and applications, while most also see the tech being used in candidate assessment and compensation package generation. A separate Bersin HR study of recruiting processes meanwhile revealed that “only 12 percent of respondents reported [their own enterprises have] strong sourcing technology, and only 9 percent said they had strong screening technology.”
The pivot to AI technologies is imminent: they have the power to help enterprise HR departments solve challenges related to insufficient or inefficient resume-submission channels, recruitment and hiring, screening for fake resumes, reaching middle/senior-level talents, correcting subjectivity or bias of interviewers, etc.
More specifically, products and platforms powered by predictive analytics, deep learning, natural language understanding, and knowledge maps can help enterprises expedite their scouting and hiring procedures. AI and big data can realize multi-dimensional analysis of the job requirements, accurately match job portraits and determine matching candidates, and quickly determine the pertinence of a candidate’s resume.
Synced has gathered some AI in talent recruiting use cases:
Chatbot Assistant
- Task description: Headhunters or HR departments can use chatbot assistants for initial communication and docking with job seekers and companies
- AI application: Natural language understanding technology powered by knowledge graphs
- Related companies: Avrio AI, AllyO chatbot, Gloat, Paradox, XOR, Wade & Wendy
Resume screening
- Task description: HR departments often need to deal with resumes from a large number of candidates
- AI application: Through deep learning and natural language understanding technology, classify job seekers’ information, identify key information priorities, and match with relevant recruitment information
- Related companies: Ifchange, Paradox, Restless Bandit
Personalized applicant portrait
- Task description: Headhunters and recruiting platforms can provide users with clear user portraits to enable more efficient and personalized services and improve work quality
- AI application: Through deep learning and predictive analytics technologies, analyze job seeker information in the talent pool
- Related companies: Ifchange, Arya, Entelo, Mesoor
Job matching
- Task description: Job-matching is concerned with the actual fit of a job candidate, instead of the individual’s stated excellence
- AI application: match information using natural language processing technologies such as key information identification, entity recognition
- Related Companies: Ifchange, Paradox, Rampup, Woo
Position key element analysis
- Task description: Analysis based on the company’s job data to understand the industry’s current talent flow, salary base, and other information
- AI applications: Collect internal employee data and use deep learning algorithms for analysis and modeling
- Related companies: Ifchange, Paradox
Source: Synced China
Localization: Meghan Han | Editor: Michael Sarazen
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