International Journal of Drug Delivery Technology
Volume 15, Issue 2

Revolutionizing Quality Assurance with Artificial Intelligence Technology 

Hiralben Mehta*, Ratna Purvang Musale, Patel Ayushi Shaileshbhai 

Parul Institute of Pharmacy and Research, Parul University Limda, Vadodara 391760, Gujarat, India 

Received: 1st Jan, 2025; Revised: 29th Mar, 2025; Accepted: 17th Apr, 2025 ; Available Online: 25th Jun, 2025

ABSTRACT

Today, Artificial Intelligence within the space of only more than a couple of decades, is transforming rapidly a whole array of industries-quality assurance cannot be one exception. Through changing the very terrain of Quality assurance by way of mechanization and adding newer dimensions to the old approach of testing, Artificial Intelligence indeed is a much significant influence factor on this review. We will discuss the applied Artificial Intelligence applications in Quality assurance that are used for test case generation, test automation, and defect prediction, among other uses. The use of Artificial Intelligence algorithms helps Quality assurance teams optimize their workflow, predict issues at an earlier development cycle, and deliver more reliable software. However, applying Artificial Intelligence in Quality assurance faces several challenges, such as low data quality, model interpretation, and the need for high-level Artificial Intelligence professionals. This Article aims to provide insightful ideas for both professionals and researchers in exploiting the potential of Artificial Intelligence for optimizing Quality assurance strategies to achieve the best results for the software product developed.

Keywords: Advantage, Artificial Intelligence Application in Quality Assurance, Artificial Intelligence (AI), challenges, quality assurance (QA), software

How to cite this article: Hiralben Mehta, Ratna Purvang Musale, Patel Ayushi Shaileshbhai. Revolutionizing Quality Assurance with Artificial Intelligence Technology. International Journal of Drug Delivery Technology. 2025;15(2):889-95. doi: 10.25258/ijddt.15.2.66

REFERENCES

  1. Hoffmann R, Reich C. A systematic literature review on artificial intelligence and explainable artificial intelligence for visual quality assurance in manufacturing. Electronics. 2023 Nov 8;12(22):4572:1-33.
  2. Arora A, Gupta R. A comparative study on application of artificial intelligence for quality assurance in manufacturing. In2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA). 2022 Sep 21;1200-1206, IEEE.
  3. Ahmed I, Jeon G, Piccialli F. From artificial intelligence to explainable artificial intelligence in industry 4.0: A survey on what, how, and where. IEEE Transactions on Industrial Informatics. 2022 Jan 27;18(8):5031-5042.
  4. Ramchand S, Shaikh S, Alam I. Role of artificial intelligence in software quality assurance. In Intelligent Systems and Applications. Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 2. (edited by: K Arai). 2022;125-136, Springer International Publishing.
  5. Wang C, Yang Z, Li ZS, Damian D, Lo D. Quality Assurance for Artificial Intelligence: A Study of Industrial Concerns, Challenges and Best Practices. arXiv Preprint ArXiv:2402.16391. 2024 Feb;1-5.
  6. Fujii G, Hamada K, Ishikawa F, Masuda S, Matsuya M, Myojin T, Nishi Y, Ogawa H, Toku T, Tokumoto S, Tsuchiya K, Ujita Y. Guidelines for quality assurance of machine learning-based artificial intelligence. International Journal of Software Engineering and Knowledge Engineering. 2020 Dec;30(11n12):1589-1606.
  7. Chen Y, Li X, Zhang J. Applications of computer vision in quality assurance for manufacturing industries. Journal of Manufacturing Systems. 2021;61:437-448.
  8. Sharma P, Tyagi S. Leveraging AI for software quality assurance in agile environments. International Journal of Software Engineering. 2020;45(3):56-72.
  9. Katalon AI. Quality assurance: From manual to autonomous testing [Internet]. katalon.com. Katalon. 2023. Available from: https://katalon.com/resources-center/blog/ai-in-quality-assurance.
  10. AI in quality assurance: The next stage of automation disruption [Internet]. Appinventiv. 2020. Available from: https://appinventiv.com/blog/ai-in-quality-assurance/.
  11. Radhakrishnan J, Gupta S, Prashar S. Understanding organizations’ artificial intelligence journey: A qualitative approach. Pacific Asia Journal of the Association for Information Systems. 2022;14(6):43-77.
  12. Rindfleisch A, Kim MH, Kim S. Artificial intelligence and qualitative research. In Handbook of Qualitative Research Methods in Marketing 2024 Sep 17. (edited by: RW Belk & C Otnes). 2024;374-386, Edward Elgar Publishing.
  13. Wang JF. The impact of artificial intelligence (AI) on customer relationship management: A qualitative study. Int. J. Manag. Account. 2023;5(5):74-88.
  14. Role of AI in quality assurance – Advantage & tools [Internet]. 2024. Available from: https://techifysolutions.com/blog/role-of-ai-in-quality-assurance/.
  15. ‌Christou PA. The use of artificial intelligence (AI) in qualitative research for theory development. 2023 Sep 17;28(9):1-6.
  16. Borges A, Hwang H-J, Xu Y. Artificial intelligence in qualitative research: A review. Journal of the Association for Information Science and Technology. 2021;72(1):1-2.
  17. kaizo-wp-admin. 5 AI tools for quality assurance to upgrade your workflows – Kaizo [Internet]. Kaizo. 2023. Available from: https://kaizo.com/blog/ai-tools-for-quality-assurance/.
  18. Felderer M, Ramler R. Quality assurance for AI-based systems: Overview and challenges (introduction to interactive session). In Software Quality: Future Perspectives on Software Engineering Quality. Proceedings Volume 13: 13th International Conference, SWQD 2021, Vienna, Austria, Jan 19-21, 2021. 2021;33-42, Springer International Publishing.
  19. Khankhoje R. Quality challenges and imperatives in smart AI software. Computer Science and Information Technology (CS & IT). 2023 Dec 27:143-154.
  20. Khinvasara T, Ness S, Shankar A. Leveraging AI for enhanced quality assurance in medical device manufacturing. Asian Journal of Research in Computer Science. 2024 Apr 8;17(6):13-35.
  21. Wang C, Yang Z, Li ZS, Damian D, Lo D. Quality Assurance for Artificial Intelligence: A Study of Industrial Concerns, Challenges and Best Practices. arXiv Preprint ArXiv:2402.16391. 2024 Feb;1-10.
  22. Haller K, Haller K. Quality Assurance in and for AI. Managing AI in the Enterprise: Succeeding with AI Projects and MLOPS to Build Sustainable AI Organizations. 2022;61-83.
  23. Khan HL, Khan S, Bhatti S, Abbas S. Role of artificial intelligence in quality assurance in ART: A review. Fertility & Reproduction. 2023 Mar 4;5(1):1-7.
  24. Deming C, Khair MA, Mallipeddi SR, Varghese A. Software testing in the era of AI: Leveraging machine learning and automation for efficient quality assurance. Asian Journal of Applied Science and Engineering. 2021;10(1):66-76.
  25. Chisty NM, Adusumalli HP. Applications of artificial intelligence in quality assurance and assurance of productivity. ABC Journal of Advanced Research. 2022 Jun 30;11(1):23-32.
  26. Goericke S. The Future of Software Quality Assurance, Springer Nature. 2020;1-5.