The prolonged crisis in North-Eastern Nigeria, shaped by the Boko Haram insurgency and the state’s multifaceted response, has become one of the most complex humanitarian and security emergencies in contemporary Africa. This article offers a theoretically grounded and empirically anchored analysis of how media systems, intelligence institutions, humanitarian governance, and cyber-infrastructure interact to produce, transform, and sometimes undermine political stability in this conflict environment. Drawing strictly on the literature provided, including Kegley’s global political transformation framework, Wolfsfeld’s media–conflict model, Lowenthal’s intelligence–policy nexus, McQuail’s public interest theory of media, and extensive humanitarian and Nigerian security literature, the study develops a multi-layered conceptual architecture linking information flows, strategic communication, intelligence gathering, and humanitarian action.

The article argues that North-Eastern Nigeria represents a paradigmatic case of twenty-first-century hybrid conflict, where insurgency is not only fought with guns and bombs but also through narratives, digital infrastructures, humanitarian governance, and intelligence credibility. The Boko Haram conflict illustrates how state fragility, media convergence, and intelligence failures converge to produce cycles of violence, displacement, and mistrust between civilian populations and governing institutions. The media environment, transformed by digital convergence and pervasive computing, has radically altered how conflict is perceived, reported, and politicized, often creating what Wolfsfeld describes as a “political contest over meaning” in which insurgents, governments, and humanitarian actors struggle for narrative dominance.

Using a qualitative analytical methodology rooted in political communication theory, intelligence studies, and humanitarian governance literature, the article examines how Nigerian and international media representations, intelligence failures and reforms, and humanitarian operational dilemmas shape both local realities and global perceptions of the conflict. It finds that weak intelligence coordination, politicized media narratives, and inconsistent humanitarian strategies have collectively contributed to an environment in which civilian trust is eroded, accountability is weakened, and conflict resolution is delayed.

The study further integrates cyber and intelligence scholarship to demonstrate how digital infrastructures, cyber vulnerabilities, and information warfare now play a constitutive role in both insurgent operations and state responses. Boko Haram’s use of digital communication, combined with Nigeria’s limited cyber-intelligence capacity, has introduced a new layer of insecurity that traditional military strategies cannot adequately address.

Ultimately, the article concludes that sustainable peace and reconstruction in North-Eastern Nigeria depend not only on military success but on the rebuilding of information ecosystems, intelligence professionalism, media accountability, and humanitarian legitimacy. By situating the Nigerian case within broader trends in world politics and digital transformation, the article contributes to both theoretical debates on contemporary conflict and practical discussions on how fragile states can better manage the intersection of security, media, and humanitarian governance.

This scholarly study is aimed at developing an integrated prioritization model for social and administrative infrastructure facilities, applicable to urban planning for territorial communities of Ukraine under the exceptionally stringent budgetary constraints of 2024–2025. The methodological framework of the research is grounded in multi-criteria decision-making analysis (MCDM), supplemented by a systematized examination of the regulatory domain of DBN and an analysis of urban planning implementation practices using case studies from the Kyiv Region (the Myronivka and Bohuslav communities). This approach ensures the comparability of heterogeneous factors, ranging from technical feasibility and life-cycle cost to social significance and administrative expediency, and makes it possible to establish a transparent rationale for ranking facilities within recovery and development programs. The research identifies stable relationships between engineering optimization of design solutions, the adoption of energy-efficient technologies, and the parameters of budgetary and time performance: a reduction in costs of up to 25% and a decrease in project implementation duration of up to 40% were documented. The practical applicability of the developed design methodology is demonstrated, including its effectiveness in completing state expert review procedures with a stated success rate of 100%. Taken together, the results substantiate the proposition that a sustainable development trajectory is attainable provided that high-technology design solutions are incorporated into urban planning documentation and aligned with regulatory requirements, financial limits, and territorial recovery priorities.

The accelerating digitization of organizational systems, combined with the proliferation of artificial intelligence across industrial, environmental, and governance domains, has profoundly reshaped how contemporary enterprises conceptualize, manage, and mitigate risk. Change management, once grounded primarily in procedural controls and human judgment, has increasingly become a data driven, algorithmically mediated domain in which predictive systems continuously evaluate the potential consequences of organizational transformation. This article develops a comprehensive theoretical and empirical synthesis of predictive artificial intelligence as a core infrastructure for risk governed change management and organizational resilience. Drawing on a wide range of interdisciplinary scholarship, including disaster resilience theory, intelligent process automation, predictive maintenance, and digital supply chain surveillance, the study situates predictive risk scoring within broader socio technical systems of governance and control. Central to this analysis is the concept of Change Advisory Boards as epistemic and regulatory institutions that must now operate within environments of algorithmic foresight and automated decision support, as demonstrated by recent developments in predictive risk scoring for change management (Varanasi, 2025).

The article advances three interconnected arguments. First, predictive artificial intelligence fundamentally redefines organizational risk from a retrospective assessment of failure to a prospective calculus of probabilistic futures, thereby transforming how change initiatives are authorized, sequenced, and monitored. Second, the integration of predictive risk scoring into governance structures such as Change Advisory Boards generates new forms of institutional rationality that blend human expertise with machine based inference, producing both enhanced resilience and novel forms of opacity and ethical risk. Third, these systems must be understood within a larger ecology of digital infrastructures, including Internet of Things enabled environments, intelligent manufacturing, smart cities, and climate adaptive systems, all of which contribute streams of data that feed algorithmic risk engines.

Methodologically, the study employs a qualitative integrative research design grounded in interpretive synthesis of the provided scholarly corpus. Rather than treating predictive models as purely technical artifacts, the article analyzes them as socio technical constructs embedded in regulatory regimes, organizational cultures, and epistemological assumptions about risk and control. The results demonstrate that predictive artificial intelligence enhances the anticipatory capacity of organizations, allowing them to simulate the cascading effects of change across complex systems, but also introduces challenges related to transparency, accountability, and institutional trust.

The discussion situates these findings within broader debates on the governance of artificial intelligence, the limitations of existing risk management standards, and the future of human centric decision making in algorithmically mediated organizations. By articulating a theoretically grounded framework for predictive AI enabled change management, this article contributes to the emerging field of digital risk governance and provides a foundation for future empirical and normative research on resilient, ethically governed intelligent enterprises.