How to fill hard-to-fill positions fast without increasing the hiring budgets? Business leaders mind that, especially, in the well-payed tech sector. Recruitment agencies know the answer, as they need to provide competitive service fees and high-quality hires.
If you look at a recruitment agency fee structure, you will see how many processes shape the recruitment cost. By integrating AI in recruitment process, whether it’s candidate sourcing, checking test assignments, or talent market analysis, recruitment companies save time and money. Want to learn how they distribute responsibilities between people and algorithms to get the most out of AI? Then, this article is for you.
They Automate the Recruitment Routine
Before we start, we’d like to note that it is important to integrate all the AI tools into a holistic ecosystem. If this is not done, the tools will operate on scattered and contradictory data. If a company does not specialize in recruiting, it may lack resources and experience to develop and support an entire recruiting ecosystem with AI on board. Then, an AI assistant can easily become a hindrance to team growth.
Candidate Sourcing and Screening
To filter candidates, recruitment agencies use independent AI tools like Hiretual and SeekOut, or in-built parsing tools provided by their HRIS (Human Resource Information System) or ATS (applicant tracking system). Those tools use advanced algorithms to analyze skills, experience, and cultural fit. Thus, recruiters shortlist candidates and devote more time to the most promising ones.
The most experienced recruiting firms, especially niche firms, develop their own sourcing and screening software. For instance, the tech talent market differs from the agriculture market. If you are looking for IT specialists, you need to set very specific search criteria.
Interview Scheduling and Coordination
AI-powered chatbots and scheduling tools can coordinate interviews, freeing up recruiters to focus on interviewing itself. These tools can automatically suggest available time slots, send reminders, and even reschedule interviews as needed, streamlining the process for both recruiters and candidates.
It’s also possible to program a chatbot to conduct interviews by sending candidates questions and gathering answers. Yet, such automated interviews have serious limitations. Without establishing personal contacts, it’s much harder to spot the cultural fit and address all the candidates’ concerns properly.
Candidate Assessments
AI can be used to test hard and soft skills to gain deeper insights into a candidate’s abilities and fit for the role. AI-driven test assessments can be tailored to specific job requirements. You can find some examples below.
- Codility tests coding skills using automated code reviews and performance checks.
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- Pymetrics uses games based on brain science and AI to look at how potential think and feel in different situations.
- HireVue studies how candidates answer questions, their facial expressions, and how they speak in video interviews.
They Use AI to Attract and Retain Top Performers
Targeted Job Descriptions
AI with NLP (natural language processing) at its core is brilliant at crafting job descriptions based on successful candidate profiles and optimizing those texts for SEO. While a robotic mind can help with making your job opening more visible across the talent market, it also can ruin your brand reputation, if a template suggested by AI is not approved by a human.
To safely delegate any writing to AI, tech recruiters:
- Give pinpoint prompts, for instance regarding tone of voice and target countries.
- Double-check any output received from AI to delete funny typos and fake facts.
Personalized Candidate Experience
With the 24/7 updates and personalized job recommendations provided by chatbots and virtual assistants, candidates feel a business takes care of them and become more loyal to that business. A loyalty is priceless in times of talent shortages.
AI for Recruitment of Diverse Teams
AI algorithms can be taught to only consider job-related factors, avoiding biases related to gender, race, or other protected characteristics. This helps businesses build inclusive teams and, as a result, get diverse tech skills and innovate faster.
Predictive Analytics and Talent Insights
AI for recruitment analyses past hires, team performance, and retention rates to predict the likelihood of a candidate’s success in a particular role.
They Overcome Challenges and Ethical Considerations Associated With AI
Successful recruiters are keen on addressing the challenges and ethical considerations of AI in recruitment.
Data Privacy and Security
Staffing and recruitment agencies implement robust data protection measures and adhere to well-known security regulations like GDPR and ISO 27001. They also don’t “feed” sensitive data to AI. Thus, candidate information remains confidential.
Transparency and Explainability
As AI-powered recruitment tools become more sophisticated, professional recruitment teams provide clear explanations about how exactly they use such tools. This helps build trust with candidates and keeps the hiring process fair and accountable.
Algorithmic Bias
AI in recruitment is only as unbiased as the data it is trained on. Good recruiters are vigilant in monitoring their AI tools for potential biases.
They Follow All the Trends in HRTech
Ethical and Responsible AI Implementation
Professional recruiters will adopt increasingly complex and multipage policies limiting the use of AI in recruitment to make sure it is ethical and responsible.
Advancements in Natural Language Processing
Advances in NLP, talked about in tech HR forums, will help AI chatbots and virtual assistants have more natural and meaningful chats with job applicants. This means it will be possible to engage AI for more HR ops.
Predictive Hiring and Talent Management
AI’s ability to analyze vast amounts of data and identify patterns will continue to drive advancements in predictive hiring and talent management. Recruiting agencies will be the first daredevils testing new AI features for forecasting talent needs, identifying high-potential candidates, and developing targeted retention strategies.
Will the next generation of HRTech be a breakthrough or just a slightly improved modification? We’ll see. In the meantime, hiring parties and hires get more chances to find each other with the help of AI for recruitment. It would be interesting to know how many people did not get their dream job because the recruiters did not have time to get to their resumes. In the history of recruitment, a huge number of interviews were cancelled because of time overlaps, which could be prevented with the help of the automated planning.