How to Select AI Companies for Entrepreneurship Programmes in Nigeria

Define the entrepreneurship outcome

State the change the programme wants to create before selecting technology. Examples include helping participants validate business ideas, improving digital skills, connecting enterprises to markets, tracking mentoring, strengthening financial records or measuring job creation. Each outcome requires different data, workflows and safeguards. A clear result statement prevents an expensive platform from becoming an unused dashboard.

Score companies against programme criteria

Use a weighted scorecard. Evaluate understanding of the target community, relevant technical capability, data protection, accessibility, implementation approach, evidence and learning, training, support, cost transparency and scalability. Require each bidder to show how its proposed features connect to programme indicators. Give more weight to delivery evidence and clarity than to the number of features promised.

Test inclusion in the design

Participants may use low-cost phones, have limited data, speak different languages or share devices. Women, persons with disabilities and people in underserved communities may face additional barriers. Ask whether the solution supports mobile-first use, simple language, low-bandwidth access, assisted onboarding and accessible interfaces. Inclusion should be tested with actual users, not assumed in a proposal.

Protect participant and business data

Entrepreneurship platforms can hold identity details, contact information, financial records and commercially sensitive ideas. The provider should define access roles, data retention, consent or other lawful bases, secure exports and incident procedures. Programme teams should know which data are required for delivery and which are collected only because the platform makes it easy.

Require a pilot and learning cycle

Start with a representative cohort and a limited set of workflows. Measure completion, active use, user comprehension, staff workload, output quality and participant outcomes. Collect qualitative feedback and review unintended effects. The contract should allow findings to change the design before scale-up.

Plan for evidence and reporting

A useful system should turn programme activity into reliable evidence without creating excessive data-entry work. Agree on indicator definitions, reporting frequency and data-quality checks. Dashboards should help programme managers act, while exports should support donor reporting and independent evaluation. AI-generated summaries must remain traceable to source data and reviewed by responsible staff.

Check sustainability and ownership

Clarify recurring costs, maintenance, hosting, integrations, administrator training, documentation and data portability. Ask what happens after grant funding ends. A sustainable system can be maintained at a realistic cost, transferred to trained staff and adapted as the programme changes.

Why PLUDAB is relevant

PLUDAB Technology Limited develops websites, custom software, databases, school systems and AI-enabled solutions for Nigerian organisations. Based in Maiduguri, PLUDAB brings local implementation awareness to projects serving youth, women, institutions and development programmes. We can support discovery, prototyping, deployment, training and ongoing improvement.

Frequently asked questions

What should NGOs ask an AI vendor first?

Ask what programme outcome the technology will improve and how that improvement will be measured.

Should price be the main selection factor?

No. Compare total cost, adoption, risk, evidence, support and long-term ownership alongside the initial price.

How long should a pilot run?

It should run long enough to test a real participant journey and reporting cycle; the appropriate period depends on programme design.

Sources

• Nigeria Data Protection Commission: https://ndpc.gov.ng
• National Information Technology Development Agency: https://nitda.gov.ng
• United Nations Sustainable Development Goals: https://sdgs.un.org