Chapter One — 1.1 Background to the Study

Generative artificial intelligence — large language model-based tools capable of producing text, summarising documents, and assisting with analysis on request — has moved unusually fast from research curiosity to everyday work tool since ChatGPT's public release in late 2022, spreading quickly across sectors that depend heavily on writing, synthesis and analysis. The international development sector fits that description closely: programme reports, donor proposals, monitoring and evaluation frameworks, and policy briefs are the currency of the work, and early anecdotal accounts suggest development professionals have begun turning to generative AI tools to help produce them.

Abuja occupies a particular place in this picture. As Nigeria's federal capital, it hosts the country offices of most major bilateral and multilateral donors and United Nations agencies operating in Nigeria, alongside a dense cluster of international and Nigerian non-governmental organisations delivering programmes across health, governance, humanitarian response and economic development. The professionals working within this cluster — programme officers, monitoring and evaluation specialists, policy analysts and technical consultants — represent a distinct population whose adoption of generative AI has not yet been studied on its own terms, separate from the broader Nigerian technology-adoption literature that has tended to focus on banking, education and general e-government use cases.

1.2 Statement of the Problem

Existing research on technology adoption in Nigeria offers a reasonably developed picture of how bank customers, students and public-sector workers take up new digital tools, but says little about a population defined less by the sector they work in and more by the kind of work they do: writing- and analysis-intensive knowledge work carried out under donor accountability requirements. Development organisations in Abuja are, in practice, already making individual and sometimes organisational decisions about generative AI — permitting it, restricting it, or saying nothing and leaving staff to decide for themselves — without much evidence about what actually drives a development professional to adopt or avoid these tools. This study addresses that gap by identifying the determinants of generative AI adoption specifically among development professionals based in Abuja.

1.3 Objectives of the Study

1. To determine the extent of generative AI tool adoption among development professionals in Abuja.
2. To examine the influence of perceived usefulness and perceived ease of use on generative AI adoption within this population.
3. To assess the role of social influence and organisational facilitating conditions — training, guidance, and access — in shaping adoption.
4. To investigate the effect of data confidentiality and donor-compliance concerns on willingness to adopt generative AI tools.
5. To recommend how development organisations in Abuja might approach generative AI-related policy and training based on the study's findings.

1.4 Research Questions

1. To what extent have development professionals in Abuja adopted generative AI tools in their work?
2. How do perceived usefulness and perceived ease of use influence adoption within this population?
3. What role do social influence and organisational facilitating conditions play in adoption?
4. How do data confidentiality and donor-compliance concerns affect willingness to adopt generative AI tools?
5. What policy and training implications follow from these findings for development organisations in Abuja?

1.5 Significance of the Study

This study is significant to development organisations based in Abuja weighing how to approach generative AI internally, offering evidence rather than assumption about what actually shapes staff adoption. It is equally relevant to technology-adoption researchers, extending a literature that has so far said little about the development sector as a distinct professional population, and to generative AI tool providers and trainers seeking to understand the specific concerns — donor confidentiality chief among them — that distinguish this audience from the general public.

1.6 Scope of the Study

The study is limited to development professionals working for organisations based in Abuja, covering bilateral and multilateral donor agencies, United Nations bodies, and international and Nigerian non-governmental organisations. It examines adoption of general-purpose generative AI tools such as ChatGPT, Microsoft Copilot and Google Gemini rather than sector-specific or custom-built AI systems, and does not extend to development professionals based outside Abuja or to organisational-level procurement decisions about AI tools.