AI adoption has become rampant in talent management, with reliable and ever-improving features that accelerate the recruitment process. Artificial intelligence’s accuracy and consistency simplify the steps to handle the mountain of repetitive tasks hiring teams face.
With AI tools constantly bringing in the right people who best fit their roles, your organization can maintain a robust workforce through the most volatile job markets. We at Ongig believe AI can do wonders for talent acquisition campaigns through accurate and reliable data.
To that end, we have rounded up the most notable AI-driven recruitment use cases and how they benefit modern companies. More importantly, we show how applying intelligent technology to your workflow can supercharge your search for the next big talent. But first, we look at AI’s core advantages and why it is all the hype for talent managers.
Advantages of AI in Recruitment
Artificial technology mimics the human thought process, but unlike human recruiters, it functions tirelessly. As such, you can depend on AI recruitment solutions for time-sensitive tasks around the clock. However, this does not mean that AI should replace humans – this is a common misunderstanding we will address later in the write-up.
AI technology comprises subfields, including machine learning and generative AI, which create quality content when human users submit prompts to the AI systems.
The reliability and cost-effectiveness of AI have led to a rise in support and growing use cases across recruitment to source the best candidates. Bloomberg reported that generative AI could expand to a $1.3 trillion market (from $40 billion in 2022) by 2032.
Essentially, generative AI solutions replace the tedium of traditional recruitment methods. The algorithm-driven system automates and structures candidate data for seamless management.
For example, you could leverage generative AI to create inclusive job descriptions with the Ongig Text Analyzer by simply keying in a job title (i.e., the prompt). Similarly, you could use generative AI to draft model interview questions and scoring matrices that eliminate recruitment bias.
The Biggest Concerns with AI in Recruitment
Despite AI’s impressive functions, a few lingering concerns remain with the technology. The two most common challenges involve cybersecurity risks that arise from candidate data management and inherent biases in AI training that could perpetuate existing discriminations.
Reliance on AI could also cause companies to overlook more nuanced candidate selection criteria, such as soft skill assessments. For those reasons (and as mentioned earlier in the article), it is critical to consider AI an enhancement rather than a replacement for traditional human-led recruitment methods.
Your team can mitigate the risks of AI in recruitment with the following measures:
- Maintaining the highest standards in candidate data management and collaborating with external IT auditors to comply with cybersecurity regulations, like the California Consumer Privacy Act (CCPA).
- Conducting regular reviews and updates of AI training systems to maintain the accuracy and fairness of algorithms. Alternatively, you could partner with a trusted AI vendor committed to continuously vetting databases and ensuring they fulfill ethical guidelines.
- Running AI functions under close supervision by human recruiters. For example, you could assign hiring managers to review AI-generated JDs before distributing them across job boards.
Modern Use Cases of AI in Recruitment
AI’s consistency has led to a growing number of use cases in hiring and talent management to accommodate rapidly shifting workforce demands.
According to Gartner, around 81% of HR leaders have explored AI in boosting their recruitment efficiencies. An estimated 76% of the respondents of the study also believed that they would lose out to competitors in one or two years if they cannot keep up with AI adoption.
The following are popular AI applications that have improved recruitment metrics like time-to-hire and quality of hire.
Guided Interviews
AI bots trained with machine learning and natural language processing (NLP) can provide a mostly touchless (running smoothly without human intervention) yet immersive candidate experience. For instance, an AI bot with significant data training can personalize first-stage interview processes based on a candidate’s profile and professional details.
Chatbots accelerate hiring and recruitment by interpreting a candidate’s response to preset/auto-generated interview questions. The AI solution’s algorithm uses predictive analytics to match the right candidates to the most suitable roles based on the gathered responses.
AI chatbots also optimize interviews with note-taking functions for smooth scheduling by aligning the availability of interviewees and employers. Leveraging an AI chatbot during the interview stage of recruitment improves coordination and prevents costly errors like double-booking, enhancing the candidate experience.
An AI-powered chatbot is advantageous, particularly for large-scale enterprise hiring campaigns involving hundreds and thousands of interviews with interested applicants.
For instance, an AI-powered chatbot could generate data-driven interview follow-up questions, reducing interview biases. According to Statista, North Americans ranked chatbots and intelligent messaging as the most popular AI recruitment solutions for 2023.
Unbiased Candidate Assessments
Human recruiters can use AI’s rich data including historical data and employee trends to oversee fair candidate assessments. Hiring managers and HR professionals can access AI tools to perform candidate evaluations based on their job experience and competencies for a skills-centric approach.
These AI solutions apply algorithms that track the best candidates based on technical factors that may include:
- Keyword recognition—Identifying keywords within a CV relevant to the industry and the roles and duties of the open position.
- Statistical assessment – Determining a candidate’s suitability based on numerical values rather than text content. These statistics could include the timeline of their job history and the frequency of keywords within the CV.
- Grammar structuring – Optimizing CVs according to grammar rules to best interpret a candidate’s suitability for a role. Doing so minimizes the risks of companies overlooking skilled hires simply due to poorly drafted resumes.
Companies can use AI data’s far-reaching capabilities to verify candidate references, including past accomplishments and employer testimonials.
AI also accelerates the process with automated emails and notifications immediately after an interview. Entrusting these tasks to AI enables human recruiters to shift their focus to higher-value talent acquisition strategies, such as developing their employer brand.
Automated Candidate Profile Creation
AI’s algorithm makes it easy for hiring teams to create quality candidate profiles from unstructured data, such as interview transcripts and resumes.
For instance, leading AI solution, Veolicity MSP can scan 3.5 million resumes at a fraction of the time managed by a human recruiter. Doing so enables quicker onboarding and a broadened outreach for talent acquisition.
AI solutions could also directly organize and transfer the data to your ATS, reducing administrative burdens.
Advanced solutions can convert speech to text from an interview, parse resumes, and extract relevant candidate information. AI automation can also process the collected information from interview videos, analyzing behavioral subtleties like body language and tone to create accurate candidate profiles.
Optimized Job Searches
Aside from empowering hiring teams, AI recruitment tools can also smoothen a candidate’s job search journey based on their searched keywords, career profiles, and other job seeker preferences. AI programs can also interpret candidate data to recommend jobs based on their search history and past employer interactions.
Examples of AI-powered job search tools include the LinkedIn platform, which applies advanced AI to suggest industry networks and recommend suitable positions based on career profiles, employer testimonials, and accomplishments.
LinkedIn’s The Future of Recruiting 2024 Report highlights that skills-based hiring can diversify talent pools by ten times. Potential candidates could also entrust AI to draft compelling cover letters that leave a winning first impression on prospective employers.
Improved Pay Equity
Pay equity remains a lingering concern within the workforce despite positive trends in other employee demands (e.g., remote/hybrid arrangements and work-life balance). Pew Research Center findings show that wage parity issues persist among women aged 37 to 46. The study indicated that women only earn 84% of men’s earnings in the same age group.
Despite these observations, pay equity should be a priority. The lack of equity at work limits candidate outreach in talent acquisition and could lead to costly legal penalties and reputational damage due to non-compliance.
For instance, the New York State Equal Pay Act requires employers to verify pay gaps between similar roles based on job-related factors ( as opposed to gender, age, or other protected characteristics). Hiring managers can use AI to align organizational pay policies with the New York Equal Pay Act and similar state, federal, or non-discrimination regulations.
The sophistication of modern AI also enables hiring teams to assess pay equity among exact roles with different job titles. These may include marketing specialists versus marketing coordinators and project managers versus program managers.
An intelligent AI hiring tool generates fair salary ranges in job descriptions in response to industry standards without incurring biases based on a candidate’s background. Such an objective approach could eliminate biases commonly attributed to pay inequity.
AI solutions also provide candidates with wage analyses of posted jobs and how they compare with other companies for greater pay transparency. These could help candidates select the most fairly paid positions, improving career satisfaction, workplace engagement, and turnover.
Cost-effective and Inclusive JD Campaigns
Your job description is the precious gateway that connects prospective hires with your company culture. To achieve the best hiring outcomes, it is important to ensure inclusive and compelling JD content. Yet, it can be challenging to manually eliminate every instance of inherent bias when simultaneously managing hundreds of job postings.
That’s where AI’s reliability can provide the much-needed support to keep your campaigns DEIB-compliant and candidate-friendly. Ongig’s Text Analyzer program uses AI to review and revise your JD structure by analyzing readability (8th-grade readability is generally the gold standard for the best engagement) and bias scores.
The intuitive Text Analyzer interface lets you conveniently edit the generated content based on its readability and bias score. As such, your recruiting team can generate on-brand JDs at scale and enrich them according to your campaign needs without delay. For instance, Ongig’s enhanced JDs provided one client with a 22% increase in female applicants for critical roles.
Ongig’s solution also integrates with your current applicant tracking systems (ATS) or HRIS so you can start leveling up the candidate experience without disrupting your recruiting workflow. Text Analyzer’s data-powered JDs attract hires with impactful words that appeal even to passive job seekers.
Check out our webinar on automated smart templating to see the Text Analyzer in action.
The Bottomline – Boost Talent Acquisition Success With AI
Ultimately, AI offers recruiters and employers the power of data automation to attract and convert the most promising talent. Research from Korn Ferry reveals that 82% of CEOs and senior leaders expect AI to significantly affect their business.
According to John Vlastelica, CEO of management consulting firm Recruiting Toolbox,
“For the first time in years, there’s a fundamental shift coming to talent acquisition, and it’s driven by AI and automation.”
To sum it up, AI solutions present a long and still-growing list of benefits to raise the efficiency of your hiring team by:
- Eliminating unconscious biases that deter talented people from underrepresented groups from joining your company.
- Cost-effectively managing administrative duties like scheduling job interviews, parsing resumes, and following up with past applicants.
- Tracking and optimizing the candidate experience across every stage of their job application journey.
- Maintaining an organized and data-informed JD library to enhance the overall hiring process of your recruitment campaigns.
AI technology’s consistency and precision prevent hiring teams from being overwhelmed by the repetitive administrative tasks that pervade the candidate pipeline. As such, your company can focus on engaging the next top hire on a deeper and more empathetic level by catering to their unique career needs – every time.
Why I Wrote This?
Ongig’s Text Analyzer software aims to revolutionize how enterprises manage AI in recruitment. Our platform applies the latest algorithmic practices to replace biased and boring JDs with attractive descriptions that convert.
Request a demo with Ongig to discover how to ramp up your application rates with quality new hires using the Text Analyzer method.
Shout-Outs:
- Bloomberg – Generative AI to Become a $1.3 Trillion Market by 2032, Research Finds
- By Kimberli Lowe-MacAuley, Flexjobs – AI Interviews: What They Are and How They Work
- Gartner – AI in HR: The Ultimate Guide to Implementing AI in Your HR Organization
- Statista – Top usages of artificial intelligence (AI) in the recruiting process in North America in 2023
- Pew Research Center – The Enduring Grip of the Gender Pay Gap
- Velocity MSP – Leveraging Artificial Intelligence for Enhanced Candidate Sourcing
- Reuters – AI and pay equity: Positives and pitfalls for employers to consider
- Korn Ferry – Talent Acquisition Trends 2024
- LinkedIn – The Future of Recruiting 2024