Proceedings of theInternational Conference on Innovation and Practices in Artificial Intelligence (ICIPAI 2026)

International Conference on Innovation and Practices in Artificial Intelligence (ICIPAI 2026)

📍Roorkee, India🗓️ 15-16 May 2026

AI – Powered Mock Interview

Authors
Janvi Tayal1, *, Shikha Mishra1, Khatiba Zehra Zaidi1, Divya Saini1, Md. Shahid1
1Meerut Institute of Engineering and Technology, Meerut, India
*Corresponding author. Email: tayaljanvi3@gmail.com
Corresponding Author
Janvi Tayal
Available Online 8 October 2026.
DOI
10.2991/978-94-6239-789-7_47How to use a DOI?
Keywords
Mock interview; traditional interview practice; human feedback; multimodal; interview preparation; job interview skills
Abstract

What shapes an interview isn’t just the question bur the way each moment unfolds. With a mock interview system, a job seeker gets to experience a realistic environment where they can practice and enhance their interviewing abilities. Traditional mock interviews are usually conducted by human interviewer scum-career coaches, mentors, or people who, based on their experience and knowledge of the industry, will ask questions and provide feedback. The fact that candidates get to interact with a person themselves allows them to work on communication skills and develop more confidence to respond naturally to how others act. These can be tailored according to the job role and specific industry, hence giving an avenue for tailormade practice. The opportunity to interact with a real person creates pressure like what the candidate may feel during an actual interview, hence helping them manage stress and perform better. In a mock interview, the candidate responds to questions about past experiences, technical knowledge, or how they would handle a certain situation. The interviewer then observes and assesses different aspects, such as clarity in speaking, the level of confidence, body language, and substance in the answers given. They then provide immediate or in-depth feedback right after the session, highlighting strengths and possible areas for improvement. Personalized feedback is helpful because it is based on real professional experience and pragmatic comprehension. Traditional mock interviews are efficient at capturing emotional aspects and adapting to the different ways one could ask a question; however, they are time-consuming and depend on the availability of an interviewer. They are generally appreciated for being interactive in nature and realistically simulating real life job interviews. Conclusion A no-AI mock interview platform is the one that relies on experts in order to create an interactive environment that nurtures the preparation of job seekers in terms of real-life interviews. This approach becomes specifically efficient for those who need extensive and customized coaching, while laying great emphasis on soft skills, natural communication, and field-related situations.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

Volume Title
Proceedings of theInternational Conference on Innovation and Practices in Artificial Intelligence (ICIPAI 2026)
Series
Advances in Intelligent Systems Research
Publication Date
8 October 2026
ISBN
978-94-6239-789-7
ISSN
1951-6851
DOI
10.2991/978-94-6239-789-7_47How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Janvi Tayal
AU  - Shikha Mishra
AU  - Khatiba Zehra Zaidi
AU  - Divya Saini
AU  - Md. Shahid
PY  - 2026
DA  - 2026/10/08
TI  - AI – Powered Mock Interview
BT  - Proceedings of theInternational Conference on Innovation and Practices in Artificial Intelligence (ICIPAI 2026)
PB  - Atlantis Press
SP  - 705
EP  - 714
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-789-7_47
DO  - 10.2991/978-94-6239-789-7_47
ID  - Tayal2026
ER  -