Proceedings of the International scientific and practical conference ―Synergy of Modern Science and Education‖ (February 2-4, 2026) / Publisher website: www.naukainfo.com. – New York, USA, 2026. - 324 p.

43 УДК 330.3 Резніков Роман Борисович PhD з економіки, докторант Інститут економіки промисловості НАН України DIGITAL TECHNOLOGIES FOR DIAGNOSTICS AND FORESIGHT OF ENTERPRISE DEVELOPMENT UNDER GLOBAL CRISES Abstract. Global crises intensify volatility, compress strategic decision windows, and increase the cost of delayed detection of deviations and weak signals. In this context, digital technologies—event streaming, cloud data platforms, process mining, AI/ML, explainable AI, digital twins, and MLOps—transform diagnostics and foresight from episodic analytical exercises into continuously operating socio- technical systems. This paper synthesizes recent research streams on data-driven foresight, process-mining-based diagnostics, explainable AI for decision accountability, digital twins for planning and crisis management, and MLOps for lifecycle reliability. The core argument is that the main limitation is no longer the lack of methods, but weak integration between (i) operational diagnostics (what is happening and why), (ii) anticipatory foresight (what may happen and how plausible), and (iii) governance routines that translate evidence into timely decisions. To address this integration gap, the paper proposes an operational concept—Crisis SenseOps—a closed-loop design that connects real-time sensing, explainable interpretation, scenario-to-trigger translation, decision gates, and learning cycles, thereby making diagnostics and foresight measurable, auditable, and maintainable under turbulence. Keywords: enterprise development; crisis diagnostics; data-driven foresight; process mining; explainable AI; digital twins; event streaming; MLOps; Crisis SenseOps; global crises.