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Documents authored by Nitychoruk, Dominik

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Software Engineering in Practice Track Paper
DOI: 10.4230/LIPIcs.ESEM.2026.92
AI-Enabling Requirements: An Industrial Experience Report from a Data-Driven Recruitment System

Authors: Sylwia Kopczyńska, Mirosław Ochodek, Eryk Kosmala, Jędrzej Musiał, Rafał Mroziewski, and Dominik Nitychoruk

Published in: LIPIcs, Volume 394, 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026)

Abstract
Requirements Engineering commonly distinguishes between functional and non-functional requirements. In AI-based systems, an orthogonal perspective might also be worth considering: whether requirements concern AI components or not. This paper reports on a 2.5-year R&D project building MONEKTO, a holistic data-driven recruitment system for a Polish temporary employment agency. The system integrates three data streams: recruitment process events, candidate and job order profiles, and employment histories - to support both candidate-order matching and employee retention prediction. Drawing on project logs covering June 2023 to January 2026, we identified three categories of requirements in AI-based systems: Non-AI-based requirements, AI-based requirements, and AI-enabling requirements. We show how these categories differ in their lifecycle: while traditional requirements stabilize after implementation, AI-enabling requirements emerge incrementally and require continuous investment throughout the system lifetime. We report five observations on the emergent nature of AI-enabling requirements and derive seven practitioner lessons for RE in AI-based system projects.
Cite as

Sylwia Kopczyńska, Mirosław Ochodek, Eryk Kosmala, Jędrzej Musiał, Rafał Mroziewski, and Dominik Nitychoruk. AI-Enabling Requirements: An Industrial Experience Report from a Data-Driven Recruitment System. In 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 394, pp. 92:1-92:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{kopczynska_et_al:LIPIcs.ESEM.2026.92,
  author =	{Kopczy\'{n}ska, Sylwia and Ochodek, Miros{\l}aw and Kosmala, Eryk and Musia{\l}, J\k{e}drzej and Mroziewski, Rafa{\l} and Nitychoruk, Dominik},
  title =	{{AI-Enabling Requirements: An Industrial Experience Report from a Data-Driven Recruitment System}},
  booktitle =	{20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026)},
  pages =	{92:1--92:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-450-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{394},
  editor =	{Feldt, Robert and Paasivaara, Maria and Mendez, Daniel and Wagner, Stefan and Bar\'{o}n, Marvin Mu\~{n}oz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESEM.2026.92},
  URN =		{urn:nbn:de:0030-drops-280604},
  doi =		{10.4230/LIPIcs.ESEM.2026.92},
  annote =	{Keywords: requirements engineering, AI-based systems, AI-enabling requirements, industry case study, data-driven recruitment}
}

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