Your hiring process operates underneath ever-present pressure. You face greater volumes of requisitions, smaller teams, and applicants expecting consumer-grade experiences. Meanwhile, AI technology clogs your inbox with more applications than you are physically capable of filtering through.
“When comparing AI recruitment to more traditional recruiting, the question is not how one model is better in theory. It’s critical to understand where automation adds value and where the human remains the most important component and how to best blend those two without upsetting either compliance or candidate trust.”
In the following chapters, this framework is applied to describe the strengths and weaknesses of each process, as well as how you can apply the advantages of AI in recruitment processes while not compromising the human judgment of your hiring managers.
What Is Traditional Recruiting?
Traditional recruitment relies heavily on human decision-making throughout each step of the process. The recruiter manually finds, screens, and selects candidates based on the aid-to-process, but does not have control over decision-making variables.
In a traditional model, you would:
• Advertise jobs on boards and careers sites
• Manual resume sorting and analysis, or the use of a simple ATS
• Conduct preliminary screenings via telephone interviews
• Organize interviews through email and spreadsheet communication
• Use feedback from the hiring manager to progress candidates
The time to hire may extend. In the industry, the average time to fill is indexed at around 36 to 44 days. Most companies have experienced growing times to fill, year over year (44 days and up, without the aid of AI). Extended times to fill contribute to increased cost to fill.
The traditional recruiting model is effective when the volume of hires is not large, the talent pool is not broad, or when you need to assess for deeper and more intricate qualities, rather than speed. It can be stressful when you are recruiting high volumes of hourly and seasonal employees.
What Is AI Hiring?
AI recruitment involves the use of software that can learn from data to facilitate or automate aspects of the hiring process you undertake.
Artificial intelligence recruiting appears in:
• Screening and ranking resumes
• Programmatic sourcing and job ad targeting
• Chatbots that handle question-answering and pre-qualify candidates
• Automated Scheduling and Reminders
• Quality of Hire and Turnover Risk predictive scoring
Adoption is no longer niche. Recent statistics reveal a staggering 87 percent adoption rate of AI applications in hiring, with over 65 percent of hiring professionals actively making use of these applications in their day-to-day activity. This is largely a function of recruitment teams making use of recruitment automation software to save time on low-value tasks.
The AI recruiting vs recruiting discussion can often be put as human recruiting vs AI recruiting. But AI recruiting should basically be an aiding level. Volume work and pattern work are done by AI recruiting. Your team will retain responsibility for the judgments and decisions.
Also Read: How High-Volume Hiring Software Helps Employers Hire Faster Without Compromising Quality
Key Differences Between AI and Traditional Recruiting
When you evaluate AI recruitment versus the human recruitment process, you realize variations exist within five aspects.
I. Speed and scale
The more applications that come in, the more the old-fashioned process slows down. “The recruiters come to a point where they’re limited to how many resumes they’re going to screen within a day or how many interviews they’ll conduct.”
The bottleneck of manual hiring applications is removed by automated hiring software. These AI-driven applications tend to substantially reduce the time to hire. Some findings indicate AI-driven hiring applications can cut the time to hire by as much as 50 percent in many cases and in some instances by as much as 65 percent while maintaining the quality of hires (50 percent faster) (65 percent reduction in time to hire).
2. Consistency and bias risk
Traditional recruitment involves the manual application of criteria. Human error is inherent in the application of criteria. Bias, exhaustion, or rushed decision-making can compromise the application of criteria, despite training. Managers tend to deviate from the rules in a hurry.
The benefits of AI in recruitment include equality in the application of rules. It applies the same rules to all resumes. Around 43% of recruiters who make decisions regarding hiring point to the reduction of bias as a benefit of AI recruitment tools (43% bias reduction). Conversely, studies and regulators point to the fact that AI has the effect of increasing biases if the data is skewed.
It is not human or AI for the hiring process. You require and need both. Human ingenuity and accountability. AI for scale and replay, but only when you audit the inputs and outputs for safe AI usage.
3. Candidate experience
Traditional recruiting methods provide extensive social interaction, albeit with the potential for poor or confusing communication, resulting in the candidates awaiting feedback for days or perhaps not receiving it at all.
Employing Ai means there are chatbots and auto-messages used in the process, which increases the speed at which these are addressed. There is evidence that chatbots currently address up to 60 percent of the first questions posed by candidates (60 percent of first questions answered by chatbots). This is particularly good at being more responsive and clear, or very bad at making the candidate feel valued.
A good mix involves automated updates on status, reminders, and FAQs, together with human touch points around points of decision.
4. Data & Decision Support
Traditional recruiting can happen with very little data, looking backwards. Reports are received days or weeks late. Management acts with headquarters in mind, not the system as a whole.
AI Recruitment relies on applicant, employee, and retention information to estimate the prospects and retention rates of job candidates. Authors note that with AI-driven talent analytics, recruitment accuracy can increase by as much as 50 percent, allowing executives to make informed decisions with higher certainty levels (accuracy increase of up to 50 percent). This way, you understand where your sources perform, where candidates fall off, and how process adjustments impact your funnel.
5. Compliance and Risk
In the case of traditional hiring, the risk involves human behavior, inconsistent documentation, and poor record-keeping practices.
AI recruitment introduces a unique risk profile. There are concerns about the potential for biased recruitment interviews powered by AI, particularly for candidates with accents or speech impediments, and the world’s regulators target AI bias and transparency (exposing risks of discrimination in AI-powered recruitment interviews). You must have AI vendor transparency, model process documentation, and human oversight for each automatic decision made against candidates.
Also Read: AI vs Human Screening: Finding the Right Balance in Hiring
Benefits of AI Hiring
If you implement your AI solutions well, the results of recruiting with AI will be reflected positively at all stages of your funnel.
1. Time to Hire: Reduced
It takes minutes, not days, for automated hiring software to process a huge set of candidates. It dispenses candidates who match your requirements and sends them to an interview.
Research indicates that the time to hire has been reduced by 30 to 50 percent by the usage of AI systems in various sectors, while another study noted that 87 percent of hiring professionals utilize AI solely to reduce the current average 44 days in hiring a candidate to even shorter hiring cycles (30 to 50 percent faster) (87 percent using AI to cut time to hire).
2. Cost per hire reduced
There are steps in the traditional hiring process that consume the recruiter’s time. Each email thread, calendar invite exchange that leads nowhere, or unqualified interview increases your overall recruitment expense.
Recruitment automation technology cuts down on redundant administrative tasks. Research illustrates that AI-powered recruiting can bring about a 30 to 35 percent reduction in the cost of hiring through automation of screening, scheduling, and communication with potential candidates while maintaining or even improving the quality of recruitment (up to 30 percent cost reduction) (up to 35 percent cost per hire).
3. Increased recruiter productivity
Each hour your recruiters spend inputting interview times into calendars is an hour they could be spending on other things, like working with hiring managers and creating talent pools.
The future of hiring with AI involves many advantages. These advantages start with a huge increase in productivity. One set of results indicates a 60 percent increase in recruiter productivity with the takeover by AI of repetitive work in resume review and Q&A (60 percent productivity increase). This allows a thin staff to handle more hiring managers without exhausting them.
4. Better candidate matching
Conventional screening may employ keyword searches and intuitive assessment. The best, yet unconventional, candidates pass through.
The AI hiring solutions evaluate the data of the candidates against successful hires and their performance metrics. Research studies indicate that the adoption of AI hiring solutions has led to a 31 percent enhancement in the quality of hiring, with AI-matched candidates having a 14 percent better chance of passing the interviews and an 18 percent better chance of accepting offers than the selections made by human resources alone (31 percent enhancement in quality of hiring) (14 percent better chance of passing the interviews, 18 percent better chance of accepting offers).
5. Experience at Scale
Chat, screening, and reminders powered by AI enable you to handle applicants consistently, even during peak times. Automation can answer frequently asked questions, provide status updates, and notify people.
Surveys indicate that more than half of the recruitment industry believes AI improves candidate experience. Candidates are increasingly expecting fast and digital processes when applying (52 percent believe that AI improves candidate experience) (a significant proportion of candidates expect AI-enabled processes). You experience improved speed without lowering the level of communication.
When Traditional Recruiting Works Better
AI recruitment is not the solution to all problems. There are certain areas in recruitment where traditional recruitment methods should take precedence, and the role of AI should be minimal.
High-level and very complex roles
More senior or highly specialized positions need extensive context understanding about culture, strategy, and politics. You are assessing how the leader impacts teams, politics, and strategic direction. AI may assist with sourcing or initial screening; however, the process needs to be fully owned by human recruitment and hiring managers.
Smaller talent pools
When your candidate field is small, going manually may work better than screen rules. You receive the benefits of referrals and premium attention. AI should assist with research or scheduling, but not drive who is viewed.
Early-stage data and/or unstructured data
The hiring process relies heavily on clear and consistent information. When your team is not currently tracking structured outcomes or does not have consistent job descriptions, your AI will discover unclear patterns and bring forth unfit candidates. Instead, improve your hiring process before adding AI.
High-trust or sensitive hiring situations
When it involves sensitive community, union, or regulator matters, the selection process needs to be transparent with human involvement. You may still leverage recruitment automation technology, perhaps for scheduling or communication, although you need to ensure that the selection process remains at the discretion of humans.
Hybrid Approach: Combining AI and Human Intelligence
“The future of AI recruitment vs. traditional recruitment is not an ‘either or’ question. The winning approach combines automated processes with human insight in a thoughtful way.”
Define where AI adds value
Begin with your process map. Look for high-volume, rule-based tasks that are time-consuming for the recruiter. These might include:
Just-In-Time and Resume Screening Against Fixed Criteria
• Scheduling and coordinating of interviews
• Application status updates and reminders
• Qualification screening for hourly or seasonal employment
Use AI-based recruiting software. Instead, involve the human element in Competency Interviews, Assessment of the Company Culture fit, and Final Offers.
Provide clear ‘guardrails.’
Use AI as an advisor, not as an unreviewable gatekeeper. Plan policies to:
· Manual evaluation for any decision based on AI output must be required.
• Avoid video and voice analytics due to increased bias risks
• Record data sources, behavior of the model, and fairness tests
• Communication with candidates regarding the usage of automation
Research reveals that only “a quarter of applicants believe the AI will judge them well,” so it appears that the reputation of your company will need to be safeguarded because “only 26 percent of applicants trust the evaluation by the AI system.
Measure the right outcomes
Speed without quality creates a ripple effect. Track:
• Time to hire and cost per hire
• Quality of Hire & First Year Turnover
• Diverse candidate slates and hiring
• Candidate satisfaction and Hiring Manager NPS
Use these metrics to tweak screens, improve AI models, and optimize where humans should be spending more of their time.
Align tools with your technology stack
You will get the most mileage from AI recruiting when it integrates smoothly with your ATS and HRIS systems and data. Point solutions operating in a silo create more busywork and more risks.
Recruitment automation solutions must be able to give you a unified view of a recruitment process based on jobs, candidates, hiring managers, and new hire performance data. At this point, solutions like Cadient excel, particularly in high-volume hiring of hourly workers.
Conclusion
Machine hiring vs. traditional hiring is not old vs. new. Machine hiring vs. traditional hiring is how you want to design your hiring engine.
Traditional approaches provide a level of complexity, relationship building, and direct engagement. AI recruitment benefits include speed, cost-savings, and reinforcement. Combine the two, and you empower recruiters with the ability to be strategic while the automation aspect does the drudgery.
Those who win do not go after glitzy technology. They select an automated solution that values the dignity of the candidate, complies with their standards, and integrates with what they already have. It is integrated with their technology. They also keep humans involved where judgment is most valued.
Cadient assists large volume and distributed employers in doing this very thing. You leverage recruitment automation technology to evaluate, coordinate, and advance qualified candidates more quickly, while your recruiting team is able to coach hiring managers and make informed decisions. Ready to construct a recruitment engine that will scale effectively without compromising fairness and control in the process? Speak with a member of theCadient team today about optimizing your recruiting technology solution.
FAQ
Is AI hiring better than traditional recruiting?
AI recruiting is better suited for speed, scalability, and automating repetitive tasks. Traditional recruiting is better suited for nuances, difficult positions, and relationship-building recruiting. The best of both worlds is obtained in a hybrid Recruiting model where AI is utilized for screening, scheduling, and analysis, and human recruiters make hiring decisions and conduct two-way conversations with applicants.
How does AI reduce bias in hiring?
AI bias may occur through various mechanisms
AI can mitigate bias by using consistent standards and blocking sensitive data, such as name and address, from being evaluated early on. There are tools to identify areas where specific groups of people are being rejected at higher rates. However, AI can perpetuate biases if trained on biased data and will require constant monitoring and reviews to correct biases.
What jobs are most well-suited for AI-powered hiring processes?
AI is most effective in rule-based, high-volume recruiting. Hourly, retail, customer service, logistics, and franchises are among the types of recruiting that AI can help the most with. There are just too many similar types of applications in these industries, and the AI recruiting software is effective at screening candidates for qualifications and location.
What do I want to see in recruitment automation software?
Emphasize integration with your ATS system, transparency in decision-making, and effective reporting. Look for software that removes the most work from your process that requires human intervention, such as auto-screening, auto-scheduling, mobile-friendly apply solutions, and workflow automation. Investigate what each software provider does regarding data privacy, bias analyses, and compliance, even before the initial software launch.
What is the impact of AI recruiting on building trust with applicants?
Be upfront in job ads and in the process about where you are using automation and where human beings are in control. Provide candidates with ways to contact a human if they have a query or need a reasonable accommodation. Do not make candidates go through an opaque AI-only interview process and make major decisions, such as selecting or rejecting candidates, accessible to human review.
