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Artificial intelligence, when intentionally aligned with the prevention pillar of the Women, Peace, and Security (WPS) agenda, can serve as a powerful tool for anticipating conflict, protecting individual security, and strengthening democratic resilience.
Artificial intelligence (AI), when intentionally aligned with the prevention pillar of the Women, Peace, and Security (WPS) agenda, offers a powerful tool for anticipating conflict, protecting individual security, and strengthening democratic resilience. Currently, AI implementation in security is largely reactive, focusing on operational or post-crisis responses, with limited scope for preventive initiatives like early warning systems or building social cohesion. Utilizing AI for prevention demands a deliberate rethinking of its application and the security paradigms that determine risk prioritization and tech governance. The WPS agenda provides a proven model for conflict prevention, and integrating its principles into AI governance and policy structures can facilitate more comprehensive and context-sensitive approaches. Reframing AI as a preventive instrument across government, civil society, and the private sector presents a critical opportunity to reduce both digital and physical pathways to conflict and advance more inclusive and sustainable security outcomes.
Current global approaches to AI governance are fragmented, largely voluntary, and focused on innovation, risk management, or post-harm mitigation rather than systematic conflict prevention. Existing frameworks, such as those from the OECD or EU, establish important norms but do not prioritize early warning, conflict prevention, or the protection of individual and community security as core objectives. There is a significant gap in comprehensive governance that integrates gender analysis, conflict-prevention research, and the WPS agenda into the lifecycle and application of AI systems for security. Bridging this gap requires coordinated, cross-sector action to move beyond reactive governance towards a proactive, prevention-focused approach.
Prevention must be a core objective in national security and AI use. Government departments and agencies are urged to establish and enforce requirements for gender-responsive and conflict-informed risk assessments for AI systems being developed and deployed in governance, security, and information environments. This should leverage existing laws like the Elie Wiesel Genocide and Atrocities Prevention Act of 2018 and the U.S. Women, Peace and Security Act of 2017 to ensure risks are identified and mitigated preemptively. AI governance should build upon these established structures, mandating the integration of WPS prevention principles in diplomacy, foreign policy, and security planning. Federal funding should also be directed towards targeted research examining AI's influence on early warning indicators, individual security, and democratic resilience.
These organizations should advance applied, interdisciplinary research that directly links developing AI governance structures with WPS and conflict prevention outcomes, thereby bridging the persistent gap between technical development and policy implementation. Leaders and organizations must translate complex technical risks into actionable tools and operational guidance for policymakers, moving beyond abstract analysis. The work of the Institute of Strategic Dialogue (ISD) on misogynistic radicalization pathways serves as a strong example, delineating specific policy asks like standardized transparency reporting and mandated intersectional analysis in AI risk assessments. Furthermore, these entities can serve as vital conveners, bringing together tech leaders, security practitioners, and WPS experts to share insights, coordinate responses, and foster crucial partnerships.
Prevention must be integrated throughout the full lifecycle of AI systems, embedding gender analysis and conflict-prevention metrics into design, testing, and deployment processes rather than treating them as secondary considerations. Companies have a crucial role in actively identifying and mitigating AI-enabled harms, including the spread of deepfakes, coordinated harassment, and mis/disinformation that disproportionately target women and marginalized populations. Investment in education initiatives and improving AI literacy for policymaking and public resilience is essential, emphasizing that AI should support, not replace, human critical thinking and expert-led implementation. Institutionalizing transparency and accountability mechanisms is paramount to ensure AI systems align with democratic values and human security, especially as they scale and shape public discourse.
Digital gender-based violence and targeted attacks must be formally recognized as core national and international security concerns. Significant investments in AI literacy are necessary to strengthen both policymaking capabilities and public resilience against AI-enabled threats, concurrently reinforcing the principle that AI should support, rather than replace, human judgment and expertise. Crucially, cross-sector collaboration must be institutionalized as a standard component of AI governance, ensuring that prevention strategies are deeply embedded in both policy design and their practical implementation across all relevant domains.