This research discusses the development of a strategic digital transformation framework for effective governance in the Global South: A case Study of Nigeria public sector agencies (PSAs). Digital transformation in government organisations is seen as the use of digital technologies to develop and implement innovations aimed at improving accountability, transparency and providing effective service delivery. The adaptation of governance to the digital age has been embraced by the public institutions in the Global North (GN), thus improving their economic and governance effectiveness. However, the digital transformation in the GS, especially Nigeria, remains fragmented as it is hindered by socio-political instability and entrenched cultural resistance leaving many public institutions at low digitalisation levels. Digitalisation in the GS PSAs is seen as a quick solution to systemic problems which increasingly failed to deliver expected outcomes due to a mismatch between technology design and institutional reality. This lack of a coherent adaptive and context-sensitive framework has rendered many digital programmes ineffective. Literature revealed the use of similar digital technologies in both GN and GS organisations indicating systemic problems, in the latter, such as limited institutional capacity, weak strategic alignment, and the absence of systemic approaches. Nigeria is therefore faced with complex digital transformation challenges. To proffer solution to the complex digital transformation landscape of the PSAs, this research evaluated some adoption models and the need for integration of more than one model for digital transformation of PSAs of Nigeria was established. This model is called Adaptive Systems Integration Model (ASIM), developed by integrating the technological organisational and environmental (TOE) model, the dynamic capability theory (DCT) and Systems Thinking (ST). ASIM presented a platform to explore contextual variation of the different PSAs, compare institutional dynamics, and uncover recurrent patterns and systemic feedback behaviours, using the TOE, DCT and ST lenses respectively. ASIM therefore presents a lens through which the complex digital transformation of the PSAs of Nigeria can be viewed and understood. To unravel the complexities and seek better understanding of the digital transformation of the PSA, the research adopted a multi-level qualitative research approach. This is to ensure that an in-depth and reliable information that allows for replication data is obtained. Agencies were selected based on several criteria and data collection was through semi-structured interviews and focus group discussions. Sampling method involves a two-way strategy namely stratified and purposive which ensured analytical depth as well as cross-case variation in understanding how digitalisation works across different organisations. Data analysis was carried out using a multi-layered analytical process comprising thematic analysis, individual case and cross-case synthesis and systems mapping using ASIM framework. The findings of this research indicate that digital transformation of the PSAs requires context-specific strategies and that leadership is at the centre of these strategies. The research also found out that the PSAs behave in some peculiar patterns called the archetypes and the knowledge of these archetypes is a panacea to solving the digital transformation problems of the PSAs of Nigeria. This research contributes to the body of knowledge by developing an integrative model (ASIM) as a composite analytical and strategic tool suited for complex public sector environments especially in GS countries like Nigeria. It also contributes to the empirical knowledge on Nigeria’s digital transformation landscape through rich qualitative data and systems modeling. Proposed future work includes the use of more agencies for more generalisability. Other areas of future research would be the use of quantitative research methods like surveys. The ASIM framework could also be varied by either including more theories or models or replacing some of the components of the model to compare the outcomes.