Pakistan Can’t Outrun Climate Change But AI Can Help Us Outthink It

Pakistan is reeling from another season of devastating monsoon floods. Since late June 2025, nearly 1,000 people have lost their lives and more than three million have been affected, according to the National Disaster Management Authority (NDMA). From glacial lake outburst floods in the north to urban inundation in Karachi, the scale and intensity of climate-induced disasters are escalating, exposing critical gaps in forecasting, response, and infrastructure resilience.

The summer began with a record-breaking heatwave, peaking at 52°C, followed by freak hailstorms and cloud bursts that crippled urban centers and rural communities alike. These events highlight a grim reality: climate change, coupled with rapid urbanization, is amplifying Pakistan’s vulnerability to natural disasters.

The widespread devastation from climate-induced disasters has renewed urgency for more resilient systems of disaster preparedness. In this context, Artificial Intelligence (AI) is increasingly being recognized not merely as a technological innovation, but as a strategic enabler of resilience and rapid response.

AI’s transformative potential lies in its ability to process vast, multi-source datasets in real time and deliver actionable information when every minute makes a difference. Machine learning algorithms can synthesize satellite imagery, Internet of Things (IoT) sensor data, and social media feeds to generate hyperlocal forecasts and risk models.

This capability is particularly critical for Pakistan, where conventional meteorological advisories often lack the granularity needed for timely, community-level action.

With climate change intensifying rainfall events, rapid glacial melt and the country’s growing urban density, traditional forecasting and disaster response are being stretched to their limits. Experts warn that unless Pakistan embeds AI and related technologies deep into its disaster-management system, loss of lives, livelihoods, and infrastructure will continue to escalate.

One recent study in Pakistan uses a high-resolution flood susceptibility mapping framework combining geospatial modelling, remote sensing, and machine learning (ML) to delineate areas most likely to be inundated. Meanwhile, AI-driven systems used elsewhere have shown how combining weather forecasts, terrain data and real-time sensor inputs can lead to more accurate flood forecasts and earlier warnings.

One of the most promising applications of AI in disaster preparedness is predictive analytics. AI can enhance the predictive accuracy of flood, cyclone, and earthquake warnings. For instance, early warning systems that use ML to forecast river overflow or flash floods would allow authorities to mobilize evacuations before disaster strikes.

The use of remote sensing data (e.g. from satellites) can provide inputs on rainfall, terrain saturation and river basins in near-real time. In Pakistan, the Jazz-NDMA early warning system has already delivered over three hundred million early warnings to populations at-risk.

Beyond forecasting, AI also plays a critical role in infrastructure resilience. With Pakistan’s aging infrastructure increasingly exposed to extreme weather, such proactive measures are essential. The use of AI in resource optimization is also critical. Algorithms can dynamically allocate emergency supplies, medical aid, and personnel based on real-time needs assessments.

Similarly, natural language processing (NLP) and social media analytics can pick up early distress signals — whether from local citizen reports, SMS / WhatsApp messages, or community radio — helping authorities verify or detect unfolding disaster events faster. AI can also support multilingual communications, crucial in Pakistan’s many languages and remote regions.

Pakistan has begun taking steps in this direction. A prominent example is the partnership between Jazz, Pakistan’s major telecom operator, and NDMA under the Disaster Early Warning System (DEW-3 – Monsoon). Through geo-fenced, location-based SMS alerts, over 23 million people in high-risk zones receive flood and weather alerts (SMS alerts) via Jazz, enabling timely evacuation or other precautionary actions.

Another example is the PDMA Madadgar App in Khyber Pakhtunkhwa, an Android-based risk communication platform that allows citizens to receive real-time updates, report incidents, and locate evacuation centres. A recent evaluation found high levels of user satisfaction for its early warning features and its ability to empower community-based reporting.

In January 2025, Pakistan’s space agency SUPARCO successfully launched the PRSC-EO1 (Pakistan Remote Sensing Satellite – Earth Observation). This indigenous electro-optical satellite is designed to support applications including disaster management, land mapping, agricultural monitoring, environmental surveillance and infrastructure tracking. PRSC-EO1’s high-resolution imagery will give Pakistan greater autonomy in obtaining data during disasters without depending entirely on external sources.

Beyond Pakistan, in Southeast Asia, flood forecasting systems in countries like Bangladesh and Thailand have used AI and remote sensing with notable success, helping authorities anticipate river swelling, issue alerts to rural communities, and execute relocations.

Image credits: Al Jazeera

While these international models operate in different geographical contexts, many of their techniques — especially in integrating satellite data, weather models and community feedback — are adaptable to Pakistan’s varied terrain.

However, the adoption of AI in disaster preparedness is not without challenges. Data fragmentation, limited technical capacity, and regulatory procedures can hinder progress. To overcome these barriers, experts advocate for a multi-stakeholder approach involving government agencies, private sector innovators, academic institutions, and humanitarian organizations.

The NDMA’s Monsoon Contingency Plan 2025 emphasizes the need for proactive and inclusive preparedness strategies. It calls for enhanced coordination among federal and provincial stakeholders, integration of emerging technologies, and capacity building at the grassroots level. The United Nations Office for the Coordination of Humanitarian Affairs (OCHA), in its Inter-Agency Monsoon Contingency Plan, also urged Pakistan to embed AI into its disaster management frameworks.

As Pakistan confronts the challenge of climate vulnerability, the need to leverage AI as a national resilience strategy is clear. The technology offers not just faster response, but smarter prevention. It enables authorities to anticipate disasters, allocate resources efficiently, and safeguard vulnerable populations with unprecedented precision. For Pakistan, embedding AI into disaster preparedness is no longer a choice. It is a necessity to save precious lives and avoid financial losses.