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                <identifier>ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:2:11925</identifier>
                <datestamp>2026-05-19T11:49:40Z</datestamp>
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                    <dim:field mdschema="dc" element="title" lang="en">Artificial Intelligence Leadership and the Decoupling of Human Agency: Evidence of Misaligned Innovation in Agentic AI Systems</dim:field>
                    <dim:field mdschema="dc" element="date" qualifier="issued">2026</dim:field>
                    <dim:field mdschema="dc" element="identifier" qualifier="uri">http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/2/11925</dim:field>
                    <dim:field mdschema="dc" element="identifier" qualifier="uri">https://www.mdpi.com/2076-3387/16/5/239 </dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="id:55257" confidence="-1">A. Ignjatović Pertini</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="orcid::0000-0001-8684-4228" confidence="-1">A. Vujko</dim:field>
                    <dim:field mdschema="dc" element="description" qualifier="abstract">This study examines how artificial intelligence (AI) leadership reconfigures the relationship
between technological systems, human capabilities, and innovation activity, focusing on the
emergence of innovation processes that operate independently of human agency. Moving
beyond dominant efficiency-oriented perspectives, it demonstrates that AI-driven leadership enables the decoupling of innovation from human capabilities, thereby generating
governance risks in agentic AI environments. Drawing on a survey of 3079 respondents
across industries and regions, the study employs exploratory and confirmatory factor
analysis and structural equation modeling. The results show that AI leadership is associated with increased innovation activity while exerting a significant negative effect on
human capabilities, with no significant relationship between human capabilities and innovation outcomes. The absence of mediation suggests that innovation outputs emerge
independently of human input, reflecting structural misalignment rather than system-level
efficiency gains. These findings indicate structural decoupling between human agency
and innovation outcomes, with AI-enabled systems increasingly substituting for human
capabilities, while human capabilities are progressively marginalized. The study reframes
AI-driven innovation as a governance problem and introduces the AI–Human Alignment
Diagnostic Scale (AI-HADS) as a structured approach to assessing misalignment.</dim:field>
                    <dim:field mdschema="dc" element="type">article</dim:field>
                    <dim:field mdschema="dc" element="identifier" qualifier="doi">https://doi.org/10.3390/admsci16050239</dim:field>
                    <dim:field mdschema="dc" element="citation" qualifier="volume">16</dim:field>
                    <dim:field mdschema="dc" element="citation" qualifier="issue">5</dim:field>
                    <dim:field mdschema="dc" element="citation" qualifier="spage">1</dim:field>
                    <dim:field mdschema="dc" element="citation" qualifier="epage">25</dim:field>
                    <dim:field mdschema="dc" element="identifier" qualifier="issn">2076-3387</dim:field>
                    <dim:field mdschema="dc" element="source">Administrative Sciences</dim:field>
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