Gender diversity as a strategic governance capability in the age of AI

Purpose This paper aims to reframe board gender diversity as a strategic governance capability rather than a symbolic initiative or universal performance lever. It explains inconsistent diversity–performance findings and clarifies when diversity may strengthen oversight in algorithmically mediated environments. Design/methodology/approach Drawing on structured evidence mapping and interdisciplinary research in corporate governance, leadership, efficiency economics, organizational demography and artificial intelligence (AI) governance, the paper develops a structured integrative conceptual synthesis focused on power, expertise–authority alignment and technological oversight. Findings Diversity effects are contingent rather than automatic. Board gender diversity is most likely to strengthen governance when three enabling conditions are present: representation thresholds that convert presence into voice, expertise aligned with authority and inclusive power structures that enable challenge. Under algorithmic complexity, these conditions may strengthen oversight of bias, explainability, privacy, cybersecurity, vendor dependence and technocratic capture. Practical implications Boards and policymakers should move beyond numerical representation to structural influence. Diverse directors should occupy consequential committees, have relevant expertise and decision rights and be supported by practices that enable challenge. Boards should evaluate participation, committee assignments and technology-governance structures so diversity contributes to accountability, risk oversight and resilience rather than symbolic compliance. Social implications Representation-focused reforms are insufficient when formal inclusion does not produce influence. More substantively inclusive governance can strengthen accountability and stakeholder responsiveness in algorithmic organizational environments. Originality/value The paper moves beyond the business-case debate by integrating intersectionality, governance, efficiency and AI-governance perspectives into a mechanism-based framework showing how board diversity becomes a strategic governance capability under algorithmic complexity.