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Dual effects of digital agents: a three-tier metric system for assessing the impact on company competitiveness

Chebotarev

2026 · DOI: 10.18323/3034-2074-2026-2-65-3
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TLDR

The resulting framework creates a foundation for the quantitative assessment of the impact of digital agents on company competitiveness, taking into account the observed heterogeneity of their implementation.

Abstract

Abstract: Problem. The proliferation of digital agents in business processes of companies produces multidirectional effects on their competitiveness, ranging from productivity growth to the loss of employee skills. A measurement apparatus that covers both aspects simultaneously and explains their origins does not yet exist, and this gap becomes critical as implementations scale up. Aim. To develop a categorical framework and a three-tier metric system that allows measuring the dual effects of digital agents, based on the causal mechanism of their generation and on the distinction of who makes the decision – a human or a digital agent. Methods. The work is carried out in a theoretical-methodological genre; its foundation consists of the four-step transfer of established frameworks in the economics of innovation from humans to digital agents while preserving the core of each original approach. The conceptual basis is formed by agency theory and the triad of artificial intelligence properties (autonomy, learnability, and opacity), with the unifying distinction being who makes decisions in the business process (a human or a digital agent). Results. A causal scheme is constructed in which the positive and negative sides of each effect arise within the same link of the mechanism. Eight channels of influence of digital agents on company competitiveness are identified, ranging from productivity to the composition of innovation authors. Three tiers of metrics are proposed, which differ in the degree to which the outcome depends on the decision-making subject. Each channel is assigned a primary measurement tier, and when an agent transitions to independent action, some channels move to higher tiers. Conclusions. The duality of the effects of digital agents is demonstrated as a structural property of a single mechanism, rather than a balance of independent factors. A three-tier classification of metrics is proposed based on sensitivity to who makes the decision – a human or a digital agent – and eight channels of influence are linked to these tiers. The resulting framework creates a foundation for the quantitative assessment of the impact of digital agents on company competitiveness, taking into account the observed heterogeneity of their implementation.