Proceedings of the International scientific and practical conference ―New York Global Science Conference 2026‖ (March 6-8, 2026) / Publisher website: www.naukainfo.com. – New York, USA, 2026. - 250 p.

14 pressure. In work [3], Marinković et al. synthesize corporate foresight research and outline trajectories for future research; yet, a persistent gap is the ―impact pathway‖ problem—how firms operationalize foresight as a routine capability that demonstrably improves strategic responsiveness and development outcomes rather than producing episodic insights. In work [4], Goel, Martin, and ter Hofstede propose a data governance framework for process mining derived from a Delphi study, arguing that reliable process data is a strategic asset and governance is a missing prerequisite for dependable insights; the gap for enterprise program implementation is that governance frameworks are frequently not integrated with strategy and change governance, which leads to analytically correct findings that do not translate into sustained operational improvements or strategic reconfiguration. In work [5], Akhramovich, Serral Asensio, and Cetina systematically review the application of process mining to Industry 4.0 and show how process mining supports discovery, conformance, and enhancement, including performance analysis and predictive extensions; the remaining gap is methodological-to-operational translation—how to standardize process mining and related diagnostics into an enterprise program (roles, cadence, prioritization, and benefit realization) rather than fragmented use cases. In work [6], Zarour, Alzabut, and Al-Sarayreh identify best practices, challenges, and maturity models for MLOps adoption, highlighting the organizational complexity of operationalizing analytics and ML; the gap for diagnostics and foresight programs is that many enterprises do not treat analytical models and pipelines as governed ―production assets,‖ which weakens robustness, auditability, and continuity of diagnostic signals under crisis conditions. In work [7], Luesink et al. examine scenario planning as a technique to enable foresight in crisis management and report that organizations invest in training and capacity building but often lack consensus on methods and institutionalization; the implementation gap is therefore not awareness but standardization and integration—scenario work must be connected to a diagnosable baseline, decision triggers, and accountable execution to create strategic impact.