Summary: This article explains step-by-step what happens during an interview with AI, the different formats of AI job interviews available in the market, and the hiring stage they’re best suited for. It also outlines the major pros & cons of hiring with AI, and underlines the importance of human judgement for recruiters considering hiring automation platforms.
‘‘We’re thinking of integrating AI into our hiring process’’
— you, your manager, and every other hiring team in 2025.
The pressure is real. As per LinkedIn’s Global Talent Trends, recruiters today spend 30–40% of their time just screening candidates! The average time-to-hire? A whopping 36-42 days. [1] Now imagine being able to cut this time by half. Implementing AI for interviews helps you do just that!
But what really happens in AI job interviews? Does a chatbot start making hiring decisions autonomously or can a recruiter make adjustments to the AI’s review?
Let’s break it down step by step, without laying down any hype or spreading further fear-mongering.
What Does ‘‘AI Job Interview’’ Really Mean?
Summary: This section defines what interviewing with AI typically means. It also lists the major pros and cons of using AI for job interviews in recruitment and discusses the key differences between AI-powered hiring & traditional hiring.
If you know, you know but if you don’t here’s a quick breakdown below. Go ahead and skip this section if you’d rather jump straight to business.
Heard someone talk about AI for job interviews recently? Either of the following is what they were likely referring to. At present, AI interview tools can be neatly divided into two distinct categories:
- AI-Assisted (Live): Where a human conducts the interview with an AI tool running in the background. The AI transcribes the conversation, suggests real-time follow-up questions based on the candidate's answers, and highlights key skills demonstrated during the interview.
AI acts as back-end support here, pitching in to enable deeper assessment of a candidate by the interviewer. However, these AI interview tools do little besides improve overall interview quality.
- AI-Led (Asynchronous): Where the candidate directly interacts with an AI interface (chat-based or video-based) without a human present. The AI plays a leading role here, autonomously asking intelligent questions, capturing responses and micro-cues, and finally evaluating the captured data against a scoring guide.
These AI interview tools not only allow for a seamless candidate experience by eliminating scheduling woes but also help make recruiting at scale hassle-free for recruiters by splitting their workload. Unlike the first kind, these actually help make recruitment processes more efficient and show clear business impact for teams who deploy them.
Curious to see how this works? Try it out here.
The "AI" component here, as anywhere else, utilizes Large Language Models (LLMs) to understand, interpret, and respond in human language. Basically, anything the candidate speaks or writes during the interview is converted into structured data for recruiters to analyze and enhance their decision-making.
It’s important to note that even for autonomous AI-led interview tools, the intent is always to help augment a recruiter’s capabilities and never to replace them in the recruitment process.
Key Benefits and Concerns for HR Teams and Recruiters
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Benefits:
- Increased efficiency and faster candidate screening
- Consistent evaluation criteria, reducing unconscious bias
- Scaled asessment of soft skills, cultural fit, and technical competence
- Enhanced candidate experience through seamless scheduling and communication
Concerns:
- Potential bias if AI models are not properly trained
- Transparency around how AI evaluates responses
- Can miss nuance in assessing soft skills
- Maintaining candidate trust and ethical standards
AI Interviews vs Traditional Interview Methods
Traditional interviews rely heavily on human intuition and subjective judgment, often influenced by unconscious biases. In contrast, AI interviews utilize data-driven algorithms to analyze verbal responses, facial expressions, and body language, providing a standardized assessment.
While traditional methods focus on personal rapport, AI-led interviews emphasize objective signals and behavioral cues, making the process more scalable and consistent.
The Step-by-Step Process of AI in Job Interviews
Summary: This section provides a detailed step-wise walkthrough of how AI for interviewing commonly comes into play in the hire-tech solutions now available.
1. Candidate Application and Pre-Screening
The AI job interview process begins with the candidate submitting their application or resume. AI systems automatically parse these documents, extracting relevant information such as skills, experience, and qualifications, scanning for keywords and patterns aligned with the role’s requirements.
Once the initial assessment is complete, the AI ranks and shortlists candidates based on how well their profiles match the job criteria. This automated screening ensures that only the most suitable candidates proceed to the next stage, saving time for recruiters and reducing manual effort.
2. Scheduling and Candidate Preparation
After pre-screening, AI-powered scheduling tools send out invitations, allowing candidates greater flexibility in choosing a date and time to interview as per their convenience. It sends them timely reminders to keep the upcoming interview top-of-mind for the candidate. If the candidate is unable to attend the scheduled interview for any reason, it can also handle rescheduling automatically.
After shortlisting profiles, AI interview tools generally send clear instructions to the candidate notifying them about the interview format, technical requirements, and other expectations. These help minimize confusion for them and ensure that the candidate is well prepared for a positive AI-led interview experience.
3. The AI-Led Interview Session
AI-led interviews are commonly found in formats such as:
- One-way asynch video interviews
- Text-based asynch chat interviews
- Voice-based telephonic interviews
- Real-time coding and technical interviews
With Fabric, however, recruiters can access several more formats, like:
- Live coffee-table chat discussing candidate qualifications
- Video pair programming and coding assessments for tech hiring
- Real-time technical screening interview with on-spot skill mapping
- Case-study & scenario-based review for non-tech roles.
In fact, Fabric AI allows recruitment teams to build their own interview agents based on their specific hiring needs. Want an AI for job interviews that can do all of the above at the same time? You can just go ahead and build one.
Interested to learn how? Schedule your demo here.
4. Data Analysis and Candidate Evaluation
Here’s a rundown of everything typically analysed in an AI interview:
- Verbal & text responses for technical competency
- Facial expressions and micro-expressions for emotions
- Body language cues such as posture and gestures for confidence
- Speech patterns, tone, and pace for communication
For candidate evaluation, AI algorithms score or rank interview responses based on a predefined criteria. It then highlights the candidate’s strengths and areas for improvement in a comprehensive report. Besides assessing technical competence, AI job interviews also help identify soft skills like communication, adaptability, and cultural fit for recruiters.
To promote fairness, many AI interview tools incorporate bias mitigation techniques, ensuring that evaluations are non-discriminatory & just.
Human Involvement and Final Decision-Making
Summary: This section outlines how AI augments human decision-making in HR, rather than eliminating it.
Where does the automation end and the need for human judgement begin? Good question!
While AI provides valuable insights, human discretion continues to be essential. Recruiters and hiring managers review AI-generated reports and candidate scores to make better informed hiring decisions.
Also, these insights are generally used to shortlist candidates for further interviews or assessments, rather than making final hiring decisions.
Combining AI generated insights with recruiter wisdom ensures a fair, nuanced evaluation for all applicants balancing objective signals and interpersonal dynamics.
Final Words
Summary: This section offers a conclusive note to the article by underlining how integrating AI into modern hiring workflows can help recruiters remove bottlenecks and improve efficiency. It also suggests the likely path forward for hiring automation.
AI interviews are designed to complement traditional hiring methods, making the process more efficient and data-driven. When integrated thoughtfully, AI job interviews can -
- Enable deeper candidate assessment
- Reduce hiring bias
- Drastically improve hiring outcomes
In other words, it can significantly reduce your cost-per-hire (by up to 40%!) and help you directly leave an impact on business growth. Read how here.
With AI for job interviews gaining popularity by the day, here’s what we recommend recruiters do once they integrate an AI interview tool into their hiring process:
- Ensure AI models are trained on diverse data sets to minimize bias
- Clearly communicate AI use to candidates upfront for building trust
- Combine AI insights with human judgment for balanced decisions
- Continuously monitor and refine their AI evaluation criteria
What’s next for AI in interviews? Think improved emotion recognition and contextual understanding that further enhances the accuracy and fairness of AI-led interviews. Also, it will be interesting to watch how developing AI governance guidelines globally influence the next gen of AI interviewers.
Here at Fabric AI, we believe all AI interviews should be ethical, compliant and unbiased. Data privacy and transparency are non-negotiables for us, as they are for you.
We hope this article helped you understand how AI for interviewing works —- at least for now. With AI interview tools like Fabric AI, scaling hiring affordably, improving candidate experience & making unbiased hiring choices without compromising the human element becomes a walk in the park.
Interested in finding out how Fabric helps recruiters evaluate candidates with greater accuracy? Read this next.
Want to see how Fabric can start scaling hiring efficiency for your organization in <2 mins? Book your demo today!