Africa does not have a shortage of digital strategies. It does not lack research papers, policy documents, technical reports, development frameworks, consultants, conferences, workshops, or pilot projects either. The continent has accumulated a substantial body of knowledge about digital transformation; yet, one uncomfortable question remains: How much of what Africa already knows actually becomes institutional knowledge? This is fundamentally different from asking whether a digital strategy is implemented. Implementation merely asks whether a strategy becomes action, whereas institutional learning asks something deeper: when an action succeeds or fails, does the institution learn from it and change its future trajectory? That distinction matters because when institutions do not systematically learn, every new digital programme begins to look like an unprecedented problem. Previous lessons vanish when projects end, staff move, consultants leave, governments change, or vendors are replaced, resulting in a damaging, perpetual cycle of digital reinvention.

Africa Has More Digital Knowledge Than Its Institutions Absorb

The continent’s digital transformation literature has grown considerably, meaning the research landscape is far from empty. A 2025 systematic review of 204 peer-reviewed studies published between 2005 and 2024 found increasing academic and policy attention to the relationship between digital transformation, the knowledge economy, and development in Sub-Saharan Africa (Edjang-Nguema & Torrent-Sellens, 2025). However, producing knowledge is only one part of the equation. The harder question is whether public institutions possess the mechanisms required to absorb, interpret, and apply it.

This disconnect is historically rooted. Over a decade ago, Nkohkwo and Islam (2013) conducted a comprehensive literature review identifying systemic barriers, ranging from poor infrastructure and inadequate funding to leadership deficiencies and socio-cultural misalignments, that consistently derailed e-government initiatives across Sub-Saharan Africa. Despite decades of identifying these identical barriers, modern institutions still lack strong mechanisms for turning knowledge into decisions. This reality is supported by a 2020 study examining knowledge translation across 35 countries in the WHO African Region, which found that evidence collation and synthesis mechanisms were available in only 15 countries, while functional knowledge-translation platforms existed in just 16 (Sombie et al., 2020). A country can host universities producing rich research and development organisations publishing endless reports, yet still lack the institutional infrastructure to turn that data into policy.

We Keep Treating Digital Projects as New Beginnings

Consider the lifecycle of a typical government digital platform launch. There is often a feasibility study, a corps of consultants, a formal procurement process, a designated project team, initial training, and even a post-implementation report. Then, the project ends. Several years later, another administration launches an identical digital initiative. The technology is newer, the vendor is different, and the project wears a new name, but the underlying institutional problems remain unchanged.

This repetition occurs because the lessons from the previous project were never converted into the institution’s operational memory. In the analytics of digital transformation, we frequently measure whether systems were deployed, counting users, transactions, uptime, and budgets. However, we rarely ask: What did the institution learn, and what did it alter because of that learning?

Research shows that knowledge needs a pathway into practice.

Recent African research provides a vital lesson regarding this gap. A 2026 multi-country study examined integrated knowledge translation across Ethiopia, Malawi, Rwanda, South Africa, and Uganda, identifying three core components associated with successful implementation: continuous engagement between researchers and decision-makers, researchers’ commitment to research impact, and direct links to existing knowledge-translation routines (Sell et al., 2026). This challenges the flawed assumption that simply publishing evidence is sufficient. Knowledge requires relationships, institutional routines, and human actors explicitly responsible for its translation. The study noted that while leadership motivation and funder support facilitated implementation, structural issues like administrative challenges, competing priorities, and rapid staff turnover created immense difficulties (Sell et al., 2026). Evidence needs an institutional pathway into decision-making; without it, research remains entirely external to the organisation.

Reports are not institutional learning.

A PDF sitting on a website is not institutional memory. A conference presentation is not automatically institutional capability, and a temporary workshop does not equate to organizational change. Knowledge only becomes an institutional capability when it enters day-to-day routines, standards, budgets, procurement practices, training programmes, and governance structures. This is where the knowledge-to-action framework becomes paramount. Research on knowledge translation has already shown the immense value of structures that bring evidence together and organically connect researchers with decision-makers (Sombie et al., 2020). The implication is straightforward:

knowledge must be given a structural route into institutions.

Failure Should Produce Institutional Memory

While failed public-sector technology projects create political criticism, audit concerns, and professional consequences, they also generate invaluable assets. A failed interoperability project reveals exactly where agencies cannot share data; a cybersecurity incident exposes vulnerabilities in procurement or incident response; and a poorly adopted government platform highlights deep-seated issues with training, incentives, or user needs.

Recent research supports this broader interpretation of failure. A 2026 systematic review identified four interconnected dimensions associated with e-government project failure in Africa: contextual pressures, structural governance weaknesses, rigid process mechanisms, and relational misalignment (Furusa & Phahlane, 2026). This moves the discussion beyond purely technical faults. A project can fail even when the technology works perfectly because governance, context, processes, and relationships dictate long-term sustainability. The post-mortem question should not just be Why did the project fail?, but rather What did the institution learn, and where was that learning stored?

Ghana offers a useful example.

This dynamic is particularly visible in Ghana. A 2026 study in Public Administration Review examined e-government adoption in Ghana through a longitudinal case study of a digital nonprofit registration process, interviewing civil servants across central and local government authorities. The research discovered that both structural conditions and the personal attitudes of public officials toward technology shaped the ultimate adoption process (Zook, 2026). Crucially, it highlighted that in resource-constrained environments, decisions to adopt technology are often influenced by external pressures rather than the immediate operational needs of frontline institutions. What happens when an organisation adopts a digital system without developing the internal routines, incentives, skills, and knowledge required to absorb it? The technology is introduced, but organisational learning lags behind.

Context matters, and lessons cannot simply be copied.

Institutions must develop the capacity to understand how new technologies interact with existing human processes, incentives, and governance arrangements. For this reason, African nations cannot treat lessons from one country as plug-and-play solutions for another. Schuppan’s (2009) seminal study of e-government in Sub-Saharan Africa argued that unique institutional and cultural contexts must dictate digital deployment, warning that blindly transferring ICT solutions and organisational concepts from developed countries is highly inappropriate. A successful digital model in Estonia, Rwanda, or South Africa cannot simply be copied into a different institutional environment and expected to yield identical outcomes. The lesson must be understood, adapted, tested, and iterated. That is institutional learning, not imitation.

The Same Applies to Cybersecurity Governance

This issue becomes even more critical when digital transformation intersects with cybersecurity. Cybersecurity is not a siloed technical function solved by purchasing firewalls or endpoint protection; it involves laws, skills, cross-border cooperation, and executive decision-making. Ifeanyi-Ajufo (2023) argues that Africa’s cyber-governance environment is intensely shaped by political, institutional, and capacity-related factors, noting that effective digital transformation requires appropriate governance mechanisms alongside technical infrastructure. Therefore, cybersecurity incidents must become sources of structural learning. If a public health institution suffers a data breach, the resolution should not end with restoring systems. The organisation must interrogate the governance failures, procurement decisions, and training deficits that allowed the vulnerability to exist. Without this feedback loop, the exact same weakness survives to strike again.

Africa Needs a Knowledge-to-Action Infrastructure

If digital transformation is to become sustainable, African countries must invest in institutional knowledge infrastructure alongside fiber-optic cables. This framework requires five foundational elements:

• Digital Project Learning Repositories: Major public technology projects must leave behind structured, open records detailing what worked, what failed, and why.
• Mandatory Post-Implementation Learning: Project closure must move beyond financial audits to include structured learning reviews that actively feed into future procurement and policy design.
• Evidence-to-Policy Mechanisms: Regular institutional channels must be built to translate raw research evidence into usable administrative decisions.
• Institutional Memory Beyond Individuals: Critical operational knowledge cannot disappear when a single project manager, consultant, or civil servant leaves. Standards, documentation, and knowledge-management systems must preserve memory across political transitions.
• Active Feedback Loops: Digital transformation must operate as a continuous, closed cycle: Evidence → Decision → Implementation → Evaluation → Learning → Adaptation → New Decision.

The Role of Universities and the Metric of Maturity

Within this infrastructure, universities must shift from acting as mere factories for research papers to becoming active nodes connecting evidence to practice. As demonstrated by the integrated knowledge translation framework, continuous engagement between researchers and decision-makers must begin long before a final report is written (Sell et al., 2026). Researchers must engage practitioners when defining research questions, and policymakers must communicate real-world operational constraints early on, creating a collaborative, two-way knowledge ecosystem.

Ultimately, Africa’s digital transformation conversation must stop focusing exclusively on visible, superficial outputs like the number of people connected, databases created, or government portals launched. While these indicators matter, true digital maturity rests on harder questions: How quickly can lessons from one project influence another? Are failed projects actively changing future procurement decisions? Do institutions remember why previous projects failed? The greatest cost of weak institutional learning is repeated failure. A country that invests in a digital project, generates valuable lessons, but fails to institutionalise them is doomed to re-invest resources to solve the exact same problem a decade later. Digital transformation is not merely a technology or implementation problem—it is a learning problem. Africa’s digital future will depend entirely on its ability to convert fleeting project experiences into permanent institutional capabilities.

Reference

• 1. Edjang-Nguema, A., & Torrent-Sellens, J. (2025). Digital transformation, knowledge economy, and development in Sub-Saharan Africa: A systematic review of nexus and challenges. African Review of Economics and Finance, 17(1), 82–106. https://doi.org/10.31920/2410-4906/2025/v17n1a3
• 2. Furusa, S. S., & Phahlane, M. (2026). Interplay of flawed ICT governance and contextual realities: A systematic review of e-government project failures in Africa. Computers, 15(8), 490. https://doi.org/10.3390/computers15080490
• 3. Ifeanyi-Ajufo, N. (2023). Cyber governance in Africa: At the crossroads of politics, sovereignty and cooperation. Policy Design and Practice, 6(2), 146–159. https://doi.org/10.1080/25741292.2023.2199960
• 4. Nkohkwo, Q. N., & Islam, M. S. (2013). Challenges to the successful implementation of e-government initiatives in Sub-Saharan Africa: A literature review. Electronic Journal of e-Government, 11(1), 253–267.
• 5. Schuppan, T. (2009). E-government in developing countries: Experiences from Sub-Saharan Africa. Government Information Quarterly, 26(1), 118–127. https://doi.org/10.1016/j.giq.2008.01.006
• 6. Sell, K., Rehfuess, E., Bayiga-Zziwa, E., Osuret, J., & Pfadenhauer, L. (2026). Evaluating the implementation of integrated knowledge translation in a multi-country research consortium in Sub-Saharan Africa: A mixed methods comparative case study. Implementation Science, 21, 33. https://doi.org/10.1186/s13012-026-01494-3
• 7. Sombie, I., et al. (2020). Knowledge translation in Africa: Are the structures in place? Health Research Policy and Systems, 18, 102. https://doi.org/10.1186/s12961-020-00633-8
• 8. Zook, S. (2026). E-government adoption in Ghana: Structural conditions and employee affective orientation. Public Administration Review, 86(4), 1060–1073. https://doi.org/10.1111/puar.70068