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◆ Service Industries Journal2026-01-27· Delphi method

Strategic and ethical enablers of responsible AI adoption in service industries: an exploratory causal Fuzzy Delphi – DEMATEL approach

Labaran Isiaku, Abdillahi Mohamoud Sheikmuse

原始摘要(英文原文)· Original abstract
This exploratory study identifies the strategic and ethical enablers that facilitate responsible artificial intelligence (AI) adoption in Nigeria’s service industry. Using a hybrid Fuzzy Delphi – DEMATEL framework, 20 experts (ten each from the public and private sectors) participated in two Delphi rounds to validate and analyze key enablers. Twelve critical factors were retained and classified into two systemic groups: six causal enablers (organizational readiness, transparency, leadership support, workforce reskilling, strategic alignment, and data privacy) and six effect enablers (technological infrastructure, equality – diversity – inclusion, change readiness, accountability/corporate digital responsibility, regulatory compliance, and ethical risk awareness). Sensitivity analyses with ±10–30% perturbations and bootstrap resampling confirmed model robustness, with no role changes among the enablers. The findings provide an exploratory causal framework that integrates strategic and ethical dimensions while reflecting the contextual realities of Nigeria’s service sector, offering actionable guidance for policymakers and managers to advance responsible AI implementation.
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Strategic and ethical enablers of responsible AI adoption in service industries: an exploratory causal Fuzzy Delphi – DEMATEL approach — 科研速览 Science Skim