Purpose and Problem: Expanding digital systems and online teaching does not automatically transform a university as an organization. The central problem is how universities translate technological opportunities into sustained changes in their structures, processes, and educational mission. Research on dynamic capabilities, change management, and educational planning has developed considerably, yet the connections among these areas remain insufficiently integrated in the university context. This study develops an organizational capabilities framework for university digital transformation, explaining how sensing opportunities, mobilizing resources, and reconfiguring the organization connect with educational redesign and the creation of value for the university's mission.

Methodology: The study employed a conceptual review design using a structured integrative review and framework synthesis. The evidence window extended from 1 January 2020 to 17 August 2026. The analytical corpus comprised 34 topical studies or authoritative institutional reports. Three methodological references published in 2021 informed the review design but were excluded from thematic counts. Inclusion required a clear connection with organizational digital transformation capabilities and findings applicable to universities. Purely technical studies and studies limited to individual technology acceptance were excluded. Evidence was extracted into a source-code matrix and analyzed in two stages: deductive coding of sensing, seizing and resource mobilization, and reconfiguring capabilities, followed by inductive coding of change-management mechanisms, educational-planning domains, and boundary conditions. Central claims required support from at least two evidence types or two different contexts.

Main Findings: Within the 34-source corpus, seizing and strategic mobilization appeared in 30 sources, organizational reconfiguration in 27, change management and readiness in 23, data and infrastructure in 22, sensing in 15, educational planning and design in 14, and ethical governance and equity in seven. These frequencies indicate the relative thematic emphasis of the selected sources rather than the causal importance of the components; each source could receive multiple codes. Explicit connections between dynamic capabilities and educational planning, together with attention to ethics and equity, were less developed than other areas. The resulting framework links environmental, technological, policy, and educational triggers to sensing opportunities, mobilizing resources, and organizational reconfiguration. Change management translates capabilities into sustained routines through shared sensemaking, participation, communication, empowerment, and institutionalization. Reconfiguring educational planning embeds these changes in curricula, assessment, faculty development, resource allocation, and quality assurance. Data governance, ethics, equity, interoperability, and institutional autonomy constitute boundary conditions. Feedback from outcomes to sensing forms a cycle of organizational learning and capability renewal.

Conclusion: The synthesis suggests that sustainable university digital transformation depends on developing organizational capabilities together and connecting them with changes in the educational core. The framework's distinctive contribution is to explain change management as the mechanism that translates capabilities into routines and educational planning as the domain in which value for the university's mission is realized. Educational quality and relevance, agility, resilience, equity, trust, and efficiency are the expected outcomes. These relationships are conceptual; the framework and the study's seven propositions require empirical testing in universities.

Application: University managers can use the framework to develop a transformation roadmap and a portfolio of capabilities. Each digital project should specify the identified need, required resources and skills, processes or roles to be reconfigured, participating groups, and expected educational value. Evaluation should cover changes in curricula and assessment, student experience, data integration, and the institutionalization of new routines. In Iranian universities, involving education, planning, quality assurance, and human resources alongside information technology can help align decisions. For generative AI applications, assessment redesign and skills development should be accompanied by data protection, bias review, and safeguards for academic integrity.