Written by Azeez Elijah O. and Echezona Perpetua Nonye
As librarians, we see the same headlines you do. Libraries in Europe, North America, and parts of Asia are using AI to search catalogues faster, answer readers’ questions through chatbots, and sort millions of records in hours. Then we look at what is happening in many libraries here in Africa, and the gap is clear.
Some say African libraries are simply not interested. That is not true. Most librarians we know are curious and eager to learn. The problem is that many obstacles stand between interest and action. Let me walk you through the biggest ones.
1. Poor and Costly Internet
AI tools need a steady internet connection. Many of our libraries have slow, unreliable internet, and some have none. Where it exists, data is expensive. A library that struggles to keep one computer online cannot run an AI-powered search system or a virtual assistant.
Power is part of the same problem. Frequent outages mean even the best tools sit idle.
2. Not Enough Money
Libraries in Africa are often at the bottom of the funding list. Salaries, books, and building repairs already eat up small budgets. Buying AI software, paying for subscriptions, and upgrading computers feel like luxuries.
Many of the best AI tools are also priced in dollars or euros. When our currencies lose value, those costs keep climbing, and a tool that was affordable last year may be out of reach this year.
3. A Skills Gap
Most library schools in Africa still teach cataloguing, classification, and reference work in the traditional way. These skills still matter, but few programmes teach data skills, AI tools, or digital preservation in any depth.
Many working librarians have never had a single training on AI. You cannot be expected to use or manage a tool you were never taught. We need training for staff already on the job, not just for students.
4. Africa Is Missing from the Data
AI learns from data, and most of that data comes from outside Africa. Many AI tools do not understand our local languages, names, places, or history. Ask a chatbot a question in Yoruba, Hausa, Igbo, Amharic, or Swahili, and the answers are often poor or wrong.
Our own collections also need work. Many African archives, theses, and local records are not yet digitised. If the content is not online, AI cannot learn from it or help people find it. Our knowledge is then left out of the tools the world is building.
5. Weak Policies and Poor Planning
Few African countries have clear national policies on AI in libraries. Many libraries have no digital strategy of their own. Without a plan, projects start with excitement, run for a year or two, and stop when the donor funding ends.
Questions about data privacy, copyright, and ethics also need clear answers. Who owns the data? How do we protect the personal information of our users? When rules are missing, many library leaders choose to wait instead of risk a mistake.
6. Resistance to Change and Fear of Job Loss
Some people ask, “Will AI replace librarians?” The worry is real, and we should talk about it openly. AI can handle repeated tasks, but it cannot replace human judgment, trust, and care for readers. A librarian helps a student find the right source, teaches a child to read, and knows the community. AI cannot do these things.
Still, fear slows adoption. Leaders and staff who do not understand AI often avoid it. The answer is learning, not silence.
7. Little Local Research and Few Success Stories
Most research on AI in libraries comes from outside Africa. We have too few local case studies showing what works with our budgets, our internet speeds, and our users. Without these examples, it is hard to convince leaders to invest.
So, Why Are We Moving Slower?
It is not a lack of talent or interest. Other regions started with better internet, steady funding, strong training, and data in their own languages. We are trying to catch up while still fixing the basics. That is a harder race, and we should say so plainly.
What Can We Do?
The gap can be closed, step by step. Here is where I think we should start:
- Start small. Use free or low-cost AI tools for simple jobs, such as writing abstracts, tagging records, or answering common questions.
- Train staff. Libraries, associations, and library schools should offer short, practical AI courses.
- Digitise local content. Our stories, languages, and research must be online so AI can include them.
- Work together. Libraries can share tools, costs, and lessons through networks and partnerships.
- Push for policy. Library associations should speak to governments about funding and clear AI guidelines.
- Share our stories. Every small success, written down and shared, helps another library take its first step.
Final Thoughts
AI will not fix every problem in our libraries, and it should not be treated as magic. But used well, it can help us serve more people, save time, and make African knowledge easier to find.
The first step is to be honest about what is holding us back. The next step is to act on it, even in small ways. As digital librarians, we are well placed to lead that effort.
What challenges have you faced with AI in your library? Share your thoughts in the comments. I would like to hear from you.