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RESEARCH CENTER FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS of Ukraine (KHARKIV, UKRAINE)

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Liburkina L. M.

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The Methodology for Comparative Assessment of AI Projects at Customer-Centric Enterprises
Pohorelova K. A., Klimenko Y. I.

Pohorelova, Kateryna A., and Klimenko, Yaroslav I. (2026) “The Methodology for Comparative Assessment of AI Projects at Customer-Centric Enterprises.” Business Inform 6:126–137.
https://doi.org/10.32983/2222-4459-2026-6-126-137

Section: Information Technologies in the Economy

Article is written in Ukrainian
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UDC 658.012:004.8(477)

Abstract:
Modern digitalization processes of enterprises in Ukraine unfold under unprecedented wartime shocks, infrastructural exhaustion, and operational chaos, rendering classical Western technology planning tools irrelevant. There is an acute methodological gap in objective comparative assessment tools that would allow domestic companies to rationally select high-priority investment projects for artificial intelligence implementation without the risk of financial ruin and workforce collapse. The study aims to overcome the «cold start paradox» and develop a transparent, mathematically weighted comparative assessment model for alternative artificial intelligence projects at customer-centric enterprises in Ukraine, factoring in military and operational risks. The article applies a comprehensive methodological framework, including systemic and structural-functional analysis for business process auditing, comparative and portfolio analysis for ranking digital initiatives, as well as the Multi-Criteria Decision Analysis (MCDA) method and expert scoring technique for establishing evaluation criteria. The research findings substantiate the limitations of mechanically transferring classical foreign models into the extreme operational realities of Ukraine and prove the necessity of aligning automation processes with the concept of the WARMI-world. The authors’ original model — the Eight-Vector «AI Project Prioritization Wheel» — has been developed. It harmoniously integrates global standards (data readiness, development cost, time-to-value, profitability) with specific local criteria of wartime resilience (resistance to blackouts and labor shortages) and customercentricity. The division of criteria into stimulant and destimulant indicators along with their reverse normalization is scientifically substantiated. An algorithm for calculating the Integral Priority Index based on a dynamic weighting system has been proposed for military scenarios involving infrastructural shock, workforce deficit, financial exhaustion, and postwar recovery conditions. The scientific novelty of the study lies in creating the first comprehensive domestic scoring model for selecting AI initiatives adapted to the conditions of the WARMI-world. A three-tier priority scale for portfolio management (Classes A, B, C) has been defined, preventing inefficient capital dissipation and the risks of shadow AI. The practical value of the study consists in the fact that the proposed model provides top management with a visual, transparent tool (the «Prioritization Wheel») to eliminate internal corporate political lobbying and make objective innovation decisions, thereby enhancing the overall viability and resilience of the business.

Keywords: artificial intelligence; AI automation; customer-centricity; wartime resilience; WARMI-world; AI Prioritization Wheel; integral priority index.

Fig.: 2. Tabl.: 1. Formulae: 1. Bibl.: 15.

Pohorelova Kateryna A. – Candidate of Sciences (Economics), Associate Professor, Department of Public Administration, Management and Marketing, Volodymyr Dahl East Ukrainian National University (17 Ioanna Pavla II Str., Kyiv, 01042, Ukraine)
Email: [email protected]
Klimenko Yaroslav I. – Postgraduate Student, Department of Public Administration, Management and Marketing, Volodymyr Dahl East Ukrainian National University (17 Ioanna Pavla II Str., Kyiv, 01042, Ukraine)
Email: [email protected]

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