Abstract
Generative AI (GAI) promises superior analytics and agility in strategy work, yet organisations struggle to move beyond pilots towards routinised decision inputs. This study investigates how GAI becomes embedded in strategic decision-making (SDM) through a qualitative single-case analysis of a global multi-brand group, based on 27 semi-structured executive interviews triangulated with internal documents and industry reports. Structured inductive coding yields a process model identifying enablers, leadership-driven adoption, quick wins, prompt-based experimentation, workforce training, secure platforms, and dedicated investments, and barriers such as strategic ambiguity, limited awareness, hallucination risks, prompt-engineering deficiencies, data readiness, and privacy or IP concerns. The analysis specifies a four-stage pathway comprising Awareness and Exploration, Experimentation and Pilots, Formal Adoption and Integration, and Institutionalisation and Transformation, with admission gates for quality, provenance, explainability, and accountability. Human-in-the-loop arrangements redistribute responsibilities between AI and managers, while governance templates and socio-technical alignment determine whether GAI outputs are admitted into formal deliberation. Findings reframe GAI not as an autonomous oracle but as decision support within decision systems, clarifying conditions under which creative or efficient outputs become strategically admissible. The study contributes a socio-technical, governance-anchored model that addresses the pilot-to-decision gap and offers actionable heuristics for scaling GAI responsibly in strategic decision-making.