An AI-Era Safety Net for Nigeria’s Poorest

What if the poorest households didn’t need “connections” or “long legs” to access help—only a phone number and a fair system? Urban slum families are crushed by unstable income, unsafe water, disease outbreaks, and sudden displacement. This awful tragedy is a vicious circle - it repeats every month, every rainy season, every rent hike. The practical use of AI in Nigeria’s slums is not hype: it’s targeting support better, reducing leakage, and making essential services reachable—cash, sanitation, health, skills, and micro-jobs—through offline-first tools like USSD, agent networks, and community verification. Done right, tech can turn survival into momentum.

How do you escape poverty when your “address” isn’t recognised, your work is informal, your landlord can evict you overnight, and your water source can make your child sick? How do you plan when every week brings a new shock—price spikes, clinic fees, flooding, demolition, or sudden unemployment? This is the daily calculus of urban slum households—and it’s why poverty in Nigeria is widespread and stubbornly persistent.

Nigeria’s own data shows the scale of deprivation: the 2022 Multidimensional Poverty Index reports 63% of people (about 133 million) as multidimensionally poor, spanning health, education, living standards, and work. On the monetary side, the World Bank estimates ~47% of Nigerians lived in poverty in 2024 (projection)—nearly half the country. In cities, the pain concentrates in informal settlements where public services often arrive late—if at all—yet households still pay “informal taxes” to survive: higher water costs, higher transport costs, higher health risks.

In late December 2025 through January 2026, mass evictions/demolitions in Makoko displaced thousands, with protests met by tear gas and families left scrambling for shelter. That’s what “ongoing issue” looks like: poverty plus instability, repeating on a loop.

So where does AI and modern tech actually help?

1) A “Neighbourhood Safety Net” that works on USSD, not hype

The most useful innovation for slum households is a reliable, offline-first social support system:

• USSD enrollment + agent onboarding (because many households are feature-phone first).
• A simple household profile (family size, vulnerabilities, location cluster—not invasive surveillance).
• Community verification (CDAs, religious/community leaders, market associations) to reduce ghost beneficiaries.
• Grievance + appeals line so people can contest errors.

AI’s role here is narrow but powerful: deduplication, fraud/leakage detection, and smarter prioritisation when funds are limited—so the help reaches real families faster.

2) Micro-cash + shock response, triggered by real signals

Urban poverty is volatile. The goal is to prevent one shock from becoming permanent setback:

• Small, frequent micro-transfers for the most vulnerable (pregnant mothers, under-5 households, disabled, elderly).
• Shock triggers: flooding alerts, sudden disease spikes, food inflation hotspots, eviction spikes—so support arrives before coping turns destructive (pulling kids out of school, selling tools, borrowing at predatory rates).
• “Nudges” by SMS/IVR (clinic reminders, immunisation days, school resumption) without punishing people.

3) Sanitation vouchers + service mapping (a high-impact, low-glamour win)

Unsafe water and sanitation are silent poverty multipliers. UNICEF notes that poor water and sanitation contribute to heavy under-5 disease burden, including diarrhoea deaths.

A practical model:

• Digital sanitation vouchers delivered to eligible households (USSD/QR/agent redeemable).
• A mapped network of local toilet businesses, pit emptiers, water vendors, mini-treatment points—so “access” becomes measurable.
• AI helps optimise placement (where demand is highest), monitor service quality, and flag outbreaks early.

This aligns with UNICEF’s push for citywide inclusive sanitation approaches that explicitly include informal settlements.

4) “Micro-jobs” and skills that pay this week

Many slum residents are working—just not earning enough. Create a micro-jobs exchange tied to verified completion:

• Drain clearing, waste sorting, community clean-ups, basic repairs, caregiving support, logistics errands.
• AI matching that prioritises proximity (walkable jobs), safety, and fairness.
• Instant payout to wallet/agent cashout—small but dependable.

Layer in skills: short modules via WhatsApp audio + IVR in local languages, with micro-credentials and referral links to apprenticeships.

5) Health access without humiliation

Use tech to reduce out-of-pocket chaos:

• A USSD “clinic queue ticket” system and IVR triage to reduce wasted transport trips.
• Stock-visibility for essential drugs at partner clinics/pharmacies.
• Disease early-warning dashboards built from anonymised symptoms + community reports, not invasive tracking.

6) Accountability that slums can actually use

The poorest often know what is failing—but lack power to prove it.

• One short code for complaints (extortion, missed payments, fake agents, service denial).
• Public, privacy-safe dashboards showing how much reached each area and how fast issues are resolved.
• AI clustering to detect hotspots of corruption or system failure quickly.

The principle is simple: AI shouldn’t watch poor people—it should watch the system on their behalf.

Urban slum poverty in Nigeria is a perpetual emergency—made worse by evictions, floods, health outbreaks, and rising living costs. The solution isn’t one mega-app. It’s a practical “poverty stack” built on USSD, agent networks, community verification, sanitation vouchers, micro-jobs, and transparent grievance systems—using AI mainly to reduce leakage, prioritise need, and spot failures fast.