Proceedings of the International scientific and practical conference ―Oxford International Science Forum‖ (February 6-8, 2026) / Publisher website: www.naukainfo.com. - Oxford, United Kingdom, 2026. - 245 p.

10 which options are funded as staged initiatives with explicit learning milestones; governance specifies decision rights, data ownership, security constraints, and cross- unit alignment. The fourth stage is execution with closed-loop learning , where digital delivery (often agile) is paired with continuous measurement and systematic review, updating assumptions and reshaping the option portfolio. The methodological novelty is not merely in naming a loop, but in formalizing its decision triggers and measurement logic suitable for crisis environments. Examples include time-to-detect disruption (latency of sensing), time-to-pivot (organizational reconfiguration speed), resilience KPIs (recovery time objectives, supplier diversification indices, cyber incident containment time), and value-creation continuity (ability to sustain service levels during shocks). This approach aligns with dynamic-capabilities routines (work [4]), complements structured strategy questions (work [5]) by embedding them into a recurring cycle, and extends resilience-focused perspectives (work [6]) by making digital data/AI infrastructure part of the strategy formation method rather than only an execution layer. It also supports multi-objective strategy formation consistent with Industry 5.0 principles (work [7]), enabling explicit trade-offs between growth, sustainability, and human-centric outcomes through portfolio governance and measurable constraints. Conclusion. Methods for forming enterprise development strategies based on digital technologies under global crises are evolving toward continuous, option-oriented, and evidence-driven models. Systematic reviews in digital transformation and strategic management show that while conceptual understanding has advanced significantly, research still lacks an integrated, crisis-calibrated method that operationalizes strategy formation as a repeatable process with measurable triggers and feedback. The crisis-adaptive digital strategy loop proposed in this paper addresses this gap by combining dynamic capabilities, staged portfolio commitments, and data/AI-enabled learning into a coherent method suitable for turbulent environments. As crises increasingly define the competitive landscape, such methods can become a practical foundation for enterprises to transform digital technologies from episodic initiatives