AI for Better UX in Computer-Aided Engineering: Is Academia Catching Up with Industry Demands? A Multivocal Literature Review

Choro Ulan Uulu; Mikhail Kulyabin; Layan Etaiwi; Nuno Miguel Martins Pacheco; Jan Joosten; Kerstin Röse; Filippos Petridis; Jan Bosch; Helena Holmström Olsson

doi:10.1007/978-3-032-04200-2_20

AI for Better UX in Computer-Aided Engineering: Is Academia Catching Up with Industry Demands? A Multivocal Literature Review

Choro Ulan Uulu (Corresponding author)
, Mikhail Kulyabin
, Layan Etaiwi
, Nuno Miguel Martins Pacheco
, Jan Joosten
, Kerstin Röse
, Filippos Petridis
, Jan Bosch
, Helena Holmström Olsson

Software Engineering and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Computer-Aided Engineering (CAE) enables simulation experts to optimize complex models, but faces challenges in user experience (UX) that limit efficiency and accessibility. While artificial intelligence (AI) has demonstrated potential to enhance CAE processes, research integrating these fields with a focus on UX remains fragmented. This paper presents a multivocal literature review (MLR) examining how AI enhances UX in CAE software across both academic research and industry implementations. Our analysis reveals significant gaps between academic explorations and industry applications, with companies actively implementing LLMs, adaptive UIs, and recommender systems while academic research focuses primarily on technical capabilities without UX validation. Key findings demonstrate opportunities in AI-powered guidance, adaptive interfaces, and workflow automation that remain underexplored in current research. By mapping the intersection of these domains, this study provides a foundation for future work to address the identified research gaps and advance the integration of AI to improve CAE user experience.

Original language	English
Title of host publication	Software Engineering and Advanced Applications - 51st Euromicro Conference, SEAA 2025, Proceedings
Editors	Davide Taibi, Darja Smite
Publisher	Springer
Pages	298-312
Number of pages	15
ISBN (Electronic)	9783032042002
ISBN (Print)	9783032041999
DOIs	https://doi.org/10.1007/978-3-032-04200-2_20
Publication status	Published - 2026
Event	51st Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2025 - Salerno, Italy Duration: 10 Sept 2025 → 12 Sept 2025

Publication series

Name	Lecture Notes in Computer Science
Volume	16082 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	51st Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2025
Abbreviated title	SEAA 2025
Country/Territory	Italy
City	Salerno
Period	10/09/25 → 12/09/25

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Keywords

artificial intelligence
Computer-aided engineering
grey literature review
multi vocal literature review
systematic literature review
user experience

Access to Document

10.1007/978-3-032-04200-2_20

Cite this

Ulan Uulu, C., Kulyabin, M., Etaiwi, L., Martins Pacheco, N. M., Joosten, J., Röse, K., Petridis, F., Bosch, J., & Olsson, H. H. (2026). AI for Better UX in Computer-Aided Engineering: Is Academia Catching Up with Industry Demands? A Multivocal Literature Review. In D. Taibi, & D. Smite (Eds.), Software Engineering and Advanced Applications - 51st Euromicro Conference, SEAA 2025, Proceedings (pp. 298-312). (Lecture Notes in Computer Science; Vol. 16082 LNCS). Springer. https://doi.org/10.1007/978-3-032-04200-2_20

Ulan Uulu, Choro ; Kulyabin, Mikhail ; Etaiwi, Layan et al. / AI for Better UX in Computer-Aided Engineering : Is Academia Catching Up with Industry Demands? A Multivocal Literature Review. Software Engineering and Advanced Applications - 51st Euromicro Conference, SEAA 2025, Proceedings. editor / Davide Taibi ; Darja Smite. Springer, 2026. pp. 298-312 (Lecture Notes in Computer Science).

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abstract = "Computer-Aided Engineering (CAE) enables simulation experts to optimize complex models, but faces challenges in user experience (UX) that limit efficiency and accessibility. While artificial intelligence (AI) has demonstrated potential to enhance CAE processes, research integrating these fields with a focus on UX remains fragmented. This paper presents a multivocal literature review (MLR) examining how AI enhances UX in CAE software across both academic research and industry implementations. Our analysis reveals significant gaps between academic explorations and industry applications, with companies actively implementing LLMs, adaptive UIs, and recommender systems while academic research focuses primarily on technical capabilities without UX validation. Key findings demonstrate opportunities in AI-powered guidance, adaptive interfaces, and workflow automation that remain underexplored in current research. By mapping the intersection of these domains, this study provides a foundation for future work to address the identified research gaps and advance the integration of AI to improve CAE user experience.",

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author = "\{Ulan Uulu\}, Choro and Mikhail Kulyabin and Layan Etaiwi and \{Martins Pacheco\}, \{Nuno Miguel\} and Jan Joosten and Kerstin R{\"o}se and Filippos Petridis and Jan Bosch and Olsson, \{Helena Holmstr{\"o}m\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.; 51st Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2025, SEAA 2025 ; Conference date: 10-09-2025 Through 12-09-2025",

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doi = "10.1007/978-3-032-04200-2\_20",

language = "English",

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series = "Lecture Notes in Computer Science",

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Ulan Uulu, C, Kulyabin, M, Etaiwi, L, Martins Pacheco, NM, Joosten, J, Röse, K, Petridis, F, Bosch, J & Olsson, HH 2026, AI for Better UX in Computer-Aided Engineering: Is Academia Catching Up with Industry Demands? A Multivocal Literature Review. in D Taibi & D Smite (eds), Software Engineering and Advanced Applications - 51st Euromicro Conference, SEAA 2025, Proceedings. Lecture Notes in Computer Science, vol. 16082 LNCS, Springer, pp. 298-312, 51st Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2025, Salerno, Italy, 10/09/25. https://doi.org/10.1007/978-3-032-04200-2_20

AI for Better UX in Computer-Aided Engineering: Is Academia Catching Up with Industry Demands? A Multivocal Literature Review. / Ulan Uulu, Choro (Corresponding author); Kulyabin, Mikhail; Etaiwi, Layan et al.
Software Engineering and Advanced Applications - 51st Euromicro Conference, SEAA 2025, Proceedings. ed. / Davide Taibi; Darja Smite. Springer, 2026. p. 298-312 (Lecture Notes in Computer Science; Vol. 16082 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T2 - 51st Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2025

AU - Ulan Uulu, Choro

AU - Kulyabin, Mikhail

AU - Etaiwi, Layan

AU - Martins Pacheco, Nuno Miguel

AU - Joosten, Jan

AU - Röse, Kerstin

AU - Petridis, Filippos

AU - Bosch, Jan

AU - Olsson, Helena Holmström

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

PY - 2026

Y1 - 2026

N2 - Computer-Aided Engineering (CAE) enables simulation experts to optimize complex models, but faces challenges in user experience (UX) that limit efficiency and accessibility. While artificial intelligence (AI) has demonstrated potential to enhance CAE processes, research integrating these fields with a focus on UX remains fragmented. This paper presents a multivocal literature review (MLR) examining how AI enhances UX in CAE software across both academic research and industry implementations. Our analysis reveals significant gaps between academic explorations and industry applications, with companies actively implementing LLMs, adaptive UIs, and recommender systems while academic research focuses primarily on technical capabilities without UX validation. Key findings demonstrate opportunities in AI-powered guidance, adaptive interfaces, and workflow automation that remain underexplored in current research. By mapping the intersection of these domains, this study provides a foundation for future work to address the identified research gaps and advance the integration of AI to improve CAE user experience.

AB - Computer-Aided Engineering (CAE) enables simulation experts to optimize complex models, but faces challenges in user experience (UX) that limit efficiency and accessibility. While artificial intelligence (AI) has demonstrated potential to enhance CAE processes, research integrating these fields with a focus on UX remains fragmented. This paper presents a multivocal literature review (MLR) examining how AI enhances UX in CAE software across both academic research and industry implementations. Our analysis reveals significant gaps between academic explorations and industry applications, with companies actively implementing LLMs, adaptive UIs, and recommender systems while academic research focuses primarily on technical capabilities without UX validation. Key findings demonstrate opportunities in AI-powered guidance, adaptive interfaces, and workflow automation that remain underexplored in current research. By mapping the intersection of these domains, this study provides a foundation for future work to address the identified research gaps and advance the integration of AI to improve CAE user experience.

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KW - Computer-aided engineering

KW - grey literature review

KW - multi vocal literature review

KW - systematic literature review

KW - user experience

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SN - 9783032041999

T3 - Lecture Notes in Computer Science

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BT - Software Engineering and Advanced Applications - 51st Euromicro Conference, SEAA 2025, Proceedings

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PB - Springer

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Ulan Uulu C, Kulyabin M, Etaiwi L, Martins Pacheco NM, Joosten J, Röse K et al. AI for Better UX in Computer-Aided Engineering: Is Academia Catching Up with Industry Demands? A Multivocal Literature Review. In Taibi D, Smite D, editors, Software Engineering and Advanced Applications - 51st Euromicro Conference, SEAA 2025, Proceedings. Springer. 2026. p. 298-312. (Lecture Notes in Computer Science). doi: 10.1007/978-3-032-04200-2_20