Areas of Expertise

Last updated: 2026-08-14

Shahzad Asghar works across eight domains built over 20 years with the United Nations: artificial intelligence implementation, machine learning and predictive analytics, digital transformation, cybersecurity governance, data analytics, humanitarian technology, cloud architecture, and large language models with retrieval-augmented generation.

Shahzad Asghar's expertise spans eight domains built over 20 years with the United Nations: artificial intelligence implementation, machine learning and predictive analytics, digital transformation, cybersecurity governance, data analytics and business intelligence, humanitarian technology, cloud architecture on Azure and AWS, and large language models with retrieval-augmented generation systems. His work includes a $2.5M transformation program achieving 83% efficiency gains.

Over 20 years of progressive experience across 8 core domains, delivering AI and digital transformation solutions for the United Nations and international organizations.

Artificial Intelligence Implementation

Designing and deploying AI solutions in complex humanitarian environments, including NLP systems, computer vision applications, and AI-powered decision support tools. Led the DigitalAAP project selected for the UN Global Pulse Accelerator.

Machine Learning & Predictive Analytics

Building predictive models for refugee resettlement matching, protection risk assessment, and resource allocation optimization. Applying ML techniques to improve outcomes for 700,000+ refugees.

Digital Transformation

Leading enterprise-wide digital transformation programs across UN agencies. Managed a $2.5M digital transformation initiative achieving 83% efficiency gains at UNHCR Jordan.

Cybersecurity Governance

Establishing cybersecurity governance frameworks, conducting penetration testing, and designing regional cybersecurity workshops. Built UNHCR Jordan's first comprehensive cybersecurity framework.

Data Analytics & Business Intelligence

Managing large-scale data operations, building dashboards, and enabling data-informed decision-making across humanitarian operations. Leading a 12-person Data Analysis Group.

Humanitarian Technology

Bridging technical innovation with real-world humanitarian needs in resource-constrained environments. 11 emergency deployments across Syria, Bangladesh, Yemen, DRC, Ethiopia, and South Sudan.

Cloud Architecture (Azure & AWS)

Designing cloud-based solutions on Microsoft Azure and AWS for humanitarian applications. Azure Solutions Architect Expert certified. Secured partnerships with Microsoft and AWS generating over $1M in refugee-centric project funding.

Large Language Models & RAG Systems

Implementing LLM-based applications including Retrieval-Augmented Generation (RAG) systems, multi-agent AI architectures, and the ADP portal for automatic chart analysis at UNESCWA.

How these eight fit together

These are not eight separate practices. In an institutional setting they are one problem seen from different sides. A model is only as good as the data operation feeding it, which is why analytics sits next to machine learning rather than beneath it. A system that cannot be secured cannot be deployed, which is why cybersecurity governance is a design input rather than a review stage. And a capability that works in a connected office and fails in a field operation has not been delivered, which is the constraint humanitarian technology adds to every other domain on this list.

The through-line is that capability and control have to advance together. Building a model without the register, the risk tier, and the stopping condition produces something nobody is willing to put in front of a decision that matters. Building the governance without the engineering produces a policy that describes systems the organisation cannot actually run.

Where this work is written up

Each domain has a longer treatment elsewhere on this site. AI governance in the United Nations covers decision rights and oversight. Humanitarian AI covers systems serving people who cannot choose another provider. Information technology audit in the age of AI covers assurance once a system is live, and the Last-Mile AI Framework covers delivery where infrastructure is unreliable.

For the systems themselves, see the builds and the AI projects. For how the work is organised rather than what it covers, see areas of practice, and for the sequence it was built in, the career journey.