AN AI-DRIVEN PREDICTIVE MODEL FOR SCREENING LEGAL PROFESSIONALS IN INTERNATIONALLY ORIENTED UKRAINIAN IT COMPANIES

Simple item page
dc.contributor.authorDzoban, Volodymyr
dc.date.accessioned2026-03-19T13:28:47Z
dc.date.available2026-03-19T13:28:47Z
dc.date.issued2026
dc.description.abstractThis applied research remedies a pressing talents issue for legal departments in Ukrainian IT companies because typical credentials are poor predictors for success in a fast-moving technology sector. The author created and tested a screening tool based on large language model and statistical modelling techniques to better evaluate candidates in an initial assessment stage. Using a dataset of 269 legal professionals who were 178 candidates for a major Ukrainian IT company and 91 professionals in the LinkedIn networking group, this study applied logistic regression analysis and narrative coding to explore predictors for success measured as acceptance of a job offer, retention for 24 months, and delivery of satisfactory performance. Results demonstrated that a background in the information technology industry, English language skills, foreign transaction experience, interest in technology, and a business focus were strong predictors for success, while traditional credentials such as university name, prior employment with a law firm, and membership in a bar association lacked predictive power. The model has 78.4% classification accuracy with 81.2% sensitivity and 75.6% specificity in cross-validation with AUC=0.78. It was used for creating a screening tool based on GPT for candidate screening where output classifies candidate data into organized assessments with scoring points for strong traits, areas of concern, and interview recommendations. Pilot testing showed a 60% reduction in screening time while maintaining quality. This study addresses a repeatable approach for statistical model development in the context of a particular legal staff environment and a usable screening tool for the technology sector legal recruitment. The results of this research challenge traditional forms of credentialism associated with legal recruitment and establish that culture fit factors potentially outperform legal credentials.
dc.identifier.citationDzoban, V. (2026). AN AI-DRIVEN PREDICTIVE MODEL FOR SCREENING LEGAL PROFESSIONALS IN INTERNATIONALLY ORIENTED UKRAINIAN IT COMPANIES. Kyiv: American University Kyiv. URI:
dc.identifier.urihttps://er.auk.edu.ua/handle/234907866/177
dc.language.isoen_US
dc.publisherManuscript
dc.subjectlegal recruitment
dc.subjectartificial intelligence
dc.subjectpredictive modeling
dc.subjectin-house counsel
dc.subjecttalent screening
dc.subjectUkrainian IT sector
dc.subjecthuman resources analytics
dc.subjectmachine learning
dc.titleAN AI-DRIVEN PREDICTIVE MODEL FOR SCREENING LEGAL PROFESSIONALS IN INTERNATIONALLY ORIENTED UKRAINIAN IT COMPANIES
dc.title.alternativeПРОГНОСТИЧНА МОДЕЛЬ НА ОСНОВІ ШТУЧНОГО ІНТЕЛЕКТУ ДЛЯ ВІДБОРУ ПРАВНИКІВ ДО МІЖНАРОДНО ОРІЄНТОВАНИХ УКРАЇНСЬКИХ ІТ-КОМПАНІЙ
dc.typeThesis

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Dzoban_AI-DRIVEN PREDICTIVE MODEL.pdf
Size:
399.12 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed to upon submission
Description:
Download

Collections

School of Management (capstones)