Agentic AI for Humanitarian and Development Operations
Shahzad Asghar is an agentic AI expert who designs autonomous AI agent systems for the United Nations. His work spans multi-agent architectures, retrieval-augmented generation, voice-first AI systems, and AI-driven workflow automation in humanitarian and development contexts across the Arab region.
Deployed Agentic AI Systems
- AI recruitment agent — autonomously screens and shortlists candidates against role requirements, with human review before any decision.
- WhatsApp voice-first feedback system — transcribes and routes refugee voice messages in multiple languages so that low-literacy users can reach services.
- RAG document bot — retrieval-augmented generation over large project document collections, returning grounded answers with source citations.
- Governance validation agent — checks documents against policy requirements before they move through institutional workflows.
Frequently Asked Questions
What is agentic AI?
Agentic AI refers to artificial intelligence systems that can autonomously perceive their environment, reason through multi-step problems, use external tools, and take actions to achieve defined objectives. Unlike traditional AI that produces a single output from a single input, agentic AI systems plan, execute, and adapt across multiple steps without requiring constant human direction.
How is agentic AI used in the United Nations?
In the United Nations, agentic AI is applied to automate complex operational workflows such as community feedback classification and routing, recruitment screening, document compliance checking, and knowledge retrieval across large project document collections. These systems handle repetitive multi-step processes so that staff can focus on decisions requiring human judgment and contextual expertise.
Who is an agentic AI expert at the UN?
Shahzad Asghar is an agentic AI expert at the United Nations with practical experience designing and delivering autonomous AI agent systems across UNESCWA, UNHCR, and other UN agencies. His work covers multi-agent orchestration, retrieval-augmented generation, voice-first AI systems, and AI governance validation in humanitarian and development operations.
What is the difference between agentic AI and traditional AI?
Traditional AI systems respond to a single input with a single output. They do not plan, use tools, or adapt across steps. Agentic AI systems break complex objectives into subtasks, call external tools and APIs, retrieve information from knowledge bases, evaluate intermediate results, and adjust their approach based on what they find. Agentic AI operates with a degree of autonomy that traditional models do not possess.
How does Shahzad Asghar apply agentic AI in humanitarian work?
Shahzad Asghar applies agentic AI in humanitarian work by designing systems that automate multi-step operational processes: an AI recruitment agent, a WhatsApp voice-first feedback system, a RAG-based bot for querying project documents, and a governance validation agent. Each system includes human-in-the-loop safeguards appropriate for sensitive humanitarian contexts.
See the deployed systems in the AI projects portfolio, learn the discipline through the free Learn Agentic AI course, and read how the Last-Mile AI approach and UN AI governance keep these systems accountable.