| Title |
Artificial intelligence implementation in organizations: barriers and enablers for transition from pilot to production |
| Translation of Title |
Dirbtinio intelekto diegimas organizacijose: kliūtys ir veiksniai, padedantys pereiti nuo bandomojo projekto prie praktinio taikymo. |
| Authors |
Aleksynas, Vilius |
| Full Text |
|
| Pages |
90 |
| Keywords [eng] |
Dirbtinio intelekto plėtojimas versle, pilotiniai projektai, barjerai stabdantys plėtra, veiksniai lemiantys sėkmę. |
| Abstract [eng] |
This is the final master’s thesis examining why artificial intelligence (AI) projects tend to be perpetually stuck in the pilot phase and why these projects are rarely scaled from a pilot to a production environment. The research object is the process of implementing artificial intelligence in an organization. This study will provide an overview of the main factors that both hinder and help in the scaling of artificial intelligence from a pilot to a production phase. A qualitative approach is the foundation of this research. Semi-structured expert interviews have been conducted with nine experts actively involved in the implementation of Artificial Intelligence strategy and change. The results of the expert interviews have been analyzed via thematic coding, incorporating deductive and inductive themes, starting from the literature and including findings starting from practical experience. The main hard result for the thesis is an integrated story line for the pilot-to-production divide as a decision process at multiple gates and not purely technical for when to deploy. Empirical evidence indicates that scaling usually involves sequential ‘go/no-go’ gates for case legitimacy, value, acceptance and compliance, technical readiness and reliability, adoption and routinization, and finally sustainability through monitoring and ownership. |
| Dissertation Institution |
Vilniaus universitetas. |
| Type |
Master thesis |
| Language |
English |
| Publication date |
2026 |
