AI and PCVE: A Practitioner’s Guide from the United Nations
The United Nations Office of Counter-Terrorism 2026 Practice Guide on Artificial Intelligence and Preventing and Countering Violent Extremism outlines how AI is reshaping the Global Programme on Preventing and Countering Violent Extremism (PCVE)’s. AI generates misinformation, disinformation, and synthetic content, creating operational challenges for practitioners. It also provides tools for monitoring extremist activity, developing messaging, detecting inauthentic material, and engaging vulnerable groups when applied responsibly.
The Evolving Threat Environment
The guide details how violent extremist actors are incorporating AI into propaganda production, multilingual content scaling, and synthetic media generation. Generative systems reduce production time for text, audio, and video. Deepfake tools complicate attribution and public trust. Platform algorithms shape visibility and engagement patterns in ways that affect radicalization pathways. The document presents this environment as a structural condition for contemporary prevention work, requiring technical literacy and analytical adaptation.
Adoption and Barriers
A survey of 120 PCVE practitioners from 45 countries found that fewer than one quarter currently use AI. Barriers include concerns about reliability, bias, privacy, and transparency, as well as limited organizational capacity and training. Most respondents expressed interest in future AI adoption and indicated a desire for training on human rights, ethics, legal frameworks, and practical AI use in PCVE contexts.
Defined Operational Use Cases
Rather than advocating broad technological adoption, the guide identifies specific applications. These include large scale open source monitoring, narrative testing and trend analysis, detection of coordinated inauthentic behavior, identification of synthetic media, and strengthened monitoring and evaluation through data analysis. AI is positioned as an analytical support tool embedded within established workflows. However effective implementation requires addressing security and knowledge gaps, algorithmic bias, discrimination, and impacts on privacy and freedom of expression. Human oversight, risk assessments, auditing, and collaboration are essential components of responsible AI integration.
Governance and Human Rights Safeguards
A substantial portion of the guide focuses on safeguards. It requires documented risk assessments prior to deployment, continuous human oversight, transparency mechanisms, and audit procedures. The guide addresses risks of algorithmic bias, discriminatory outputs, privacy violations, and mission creep. AI integration must comply with international human rights law, including protections for freedom of expression and due process. Institutional accountability is framed as a non negotiable component of implementation.
Capacity Building and Resources
Organizational readiness is critical. The guide stresses preparation before adoption. Organizations are advised to build AI literacy across leadership and operational staff, establish procurement standards and technical due diligence processes, engage with stakeholders, define evaluation metrics, pilot interventions, and engage external technical expertise where necessary. The document includes practical worksheets and assessment tools, including checklists, risk assessment templates, ethical guidelines, and stakeholder mapping tools designed to evaluate whether an institution has the governance and technical capacity to deploy AI responsibly.
For a real-world example of how AI is adding a new tool to the insurgent actor’s toolbox on the battlefield, take a look at Matthew Turner’s recent essay, Violent Non‑State Actors and Generative AI in Warfare: The RSF and the Sudanese Civil War. As he outlines, the use of coordinated online campaigns, bot networks, and disinformation in a conflict setting reinforces how extremist and irregular actors exploit digital platforms, aligning with the UN guide’s concern about synthetic content complicating prevention work.
