Economic instability and the threat of recession place immense pressure on companies to cut expenses. At the same time, hiring and retention remain vital to business performance. This poses a dilemma for recruiters facing headcount freezes or budget reductions. Luckily, innovations in AI offer ways to automate parts of the recruiting workflow to curtail costs without sacrificing talent acquisition results.
This article explores key applications of artificial intelligence that enable recruiters to maximize productivity and efficiency, especially during downturns. While AI cannot entirely replace human judgment in hiring, purposefully deploying the right technologies can yield significant savings.
Screen Resumes and Profiles with AI
Manually reviewing hundreds of resumes and candidate profiles is an arduous task that bogs down recruiters. Applicant tracking systems like Greenhouse and Lever integrate intelligent algorithms to automate parts of the screening process, including:
- Semantic search – Parses resume content to match candidate skills and experience with open role requirements.
- Natural language processing – Extracts key details like past companies, titles, and duration in roles from unstructured resume text.
- Machine learning – Uses historical hiring data to identify patterns predicting candidate success in a given position.
- Automated ranking – Scores and ranks candidates based on closeness of fit to the job description.
- Email automation – Triggers automated emails to schedule interviews for promising applicants.
This enables recruiters to quickly filter potential matches for further evaluation, rather than exhaustively reading every resume. The huge time savings allow focusing on higher value interviewing and relationship-building activities.
Conduct Candidate Interviews via AI
Traditional phone or video interviews require massive coordination for scheduling. AI virtual interviewing assistants like Phenom AI, Mya, and Ideal provide 24/7 availability to accelerate this process. Key features include:
- Custom interview questions – Create interview scripts tailored to each open position.
- Flexible candidate scheduling – Candidates choose from available times through text or web chat.
- Automated interviewing – The AI assistant asks and records video answers to interview questions.
- Sentiment analysis – AI assesses verbal and non-verbal cues like facial expressions as candidates respond.
- Transcription and reporting – Interview videos, transcripts, and analysis get shared back to recruiters.
This round-the-clock automated interviewing leaves recruiters free to focus on more strategic hiring tasks. Candidates also appreciate the convenience of self-scheduling.
Automate Background Checks and Verifications
Vetting candidates’ backgrounds is a necessary step, but time-intensive when done manually. AI and API integrations available through services like Checkr, FirstAdvantage, and GoodHire allow automating various verification processes including:
- Identity check – Validates candidate name, date of birth, and SSN.
- Employment check – Confirms past employers, titles, and employment dates.
- Education check – Verifies academic credentials and degrees earned.
- Criminal check – Performs county, state, and federal criminal record searches.
- Motor vehicle records – Checks driving records for policy violations.
- Credit check – Retrieves credit reports when relevant for a role.
- Professional license validation – Confirms proper certifications and valid status.
Triggering these instantly via API reduces the weeks-long back and forth once common for verifications. Speeding up this step enhances candidate experience and prevents losing top prospects to competitors.
Guide Interview Decisions with Data
After preliminary resume screening and interviews, deciding who to advance to final round interviews involves careful consideration. A number of AI tools can support more data-driven selective decision making:
- Interview analytics – Platforms like HireVue and Montage analyze linguistic patterns, keywords, and interviewee engagement metrics to identify optimal candidates.
- Voice analysis – Solutions like Talview extract vocal tone, word choice, pacing, and emotional inflection to assess behaviors indicative of a good culture fit.
- Job simulation – Apps like Skeeled and Pymetrics measure cognitive abilities, attention, multitasking, and work styles through neuroscience games and tests.
- Predictive analytics – Based on attributes of past successful hires, AI identifies candidates statistically likelier to excel and stay with the company.
While not a replacement for human evaluation of talent, these AI insights help focus recruiting efforts on those with the highest probability of being a match.
Tap AI Chatbots for Candidate Communication
Communicating with applicants during recruiting is highly manual. AI chatbots offer efficient 24/7 support for common candidate questions and workflows like:
- Initial outreach – Automated bots can respond to applicants, provide role details, and schedule interviews via two-way chat.
- Follow-ups – AI can send timely reminder and follow-up messages at each stage.
- Updates – Chatbots inform applicants on application status, hiring timelines, and next steps.
- Offer letter delivery – Candidates can receive, review, sign, and submit offer acceptance paperwork digitally through bots.
Candidates appreciate getting speedy responses from AI assistants which builds goodwill and bolsters the employer brand.
Create an Intelligent Recruiting Data Hub
To maximize value from the above AI tools, their data and insights should feed into a centralized analytics platform accessible across the HR and recruiting team. Solutions like Oracle HCM, SAP SuccessFactors, and Workday HCM incorporate capabilities to:
- Aggregate recruiting metrics – Compile hiring volume, cost per hire, time to fill, and other key metrics in one dashboard.
- Slice by role, department, etc. – Allow filtering metrics based on various parameters for deeper analysis.
- Forecast hiring demand – Predict future hiring needs based on growth projections and historic rates.
- Model outcomes – Estimate potential improvements if changes are made to the recruiting process.
This holistic view of recruiting data empowers strategic decisions on where to target AI automation for optimizing results and reducing costs.
The Outlook for Intelligent Recruiting
AI and automation enable recruiters to work smarter and faster, particularly crucial in tight economic climates. While adopting these technologies involves some change management, the long-term payoff for efficiency and cost savings is substantial. AI should be viewed as a talent multiplier – not a replacement – that allows recruiters to advance their skills and impact. Companies who approach AI as a strategic capability poised to transform recruiting will gain advantage in securing top talent while controlling costs.