ZIMBABWE stands at a momentous juncture. As we finalise our National Artificial Intelligence Strategy (2025–2030), it is not enough to treat this exercise as another technical checklist.
We must ask ourselves whether this strategy will truly empower every Zimbabwean to shape our digital future, or whether it will simply reinforce existing hierarchies of expertise.
Thinking deeper requires us to move from a model of top-down knowledge transfer, what Paulo Freire famously called the “banking model” of education, toward a dialogical process in which citizens become active co-creators of policy and practice.
The first technological revolutions, the printing press and electricity, were visible to all. Towns lit up, pamphlets circulated, ideas spread. AI, in contrast, operates behind the scenes, humming within servers and algorithms. Its impact, while not less profound, can remain hidden until systems are already deployed.
If we fail to name this quiet revolution and invite broad participation, we risk ceding control of our destiny to unseen code and opaque decision-making processes.
It is, therefore, critical that the Zimbabwean public understands not only the potential of AI, but also the values and assumptions embedded within every dataset and every algorithm.
Our conventional approach to policy-making in Zimbabwe, as in many parts of the world, has relied on a narrow circle of specialists drafting frameworks in isolation.
Citizens are then expected to absorb these policies as passive recipients. This banking model of expertise assumes that knowledge is an object to be deposited, rather than a process to be co-constructed.
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Paulo Freire argued that true learning emerges when learners and educators engage in reciprocal dialogue, jointly investigating reality and transforming it through collaborative action.
Applied to AI governance, this approach demands that we dismantle hierarchical barriers and place lived experience on equal footing with technical analysis.
Imagine, instead, a process in which rural farmers deliberate on how drone-collected data could predict drought, while blending scientific models with generations of local weather lore.
Envision persons with disabilities co-designing accessibility standards for AI-driven learning platforms, ensuring that technological innovation serves all members of society.
Such a problem-posing, dialogical method transforms policy-making into an ongoing cycle of listening, reflection, and adaptation, precisely the kind of dynamic engagement that Freire envisioned.
A strategy drafted in isolation may appear robust on paper, but it risks becoming a suit of armour, impenetrable to critique and detached from lived realities.
Narrowly defined expert groups can overlook systemic biases, whether gendered, urban-centric, or elitist, that warp AI systems toward unfair outcomes.
Without broad moral reflection, algorithms may optimise efficiency at the expense of human dignity. Moreover, sidelining grassroots innovators deprives our nation of the creative spark that arises when local problem-solvers contribute their insights.
Zimbabwe’s resilience and ingenuity have always stemmed from inclusive collaboration; our AI roadmap must honour this legacy.
We need not reinvent the wheel. The European Union’s AI Act offers a risk-based regulatory model with mandatory human oversight; we can adapt its taxonomy to include a “cultural integrity” category rooted in Zimbabwean values. Unesco’s recommendation on the ethics of artificial intelligence emphasises human rights, justice, and cultural diversity, principles that resonate deeply with our own communal ethos.
The African Union’s Data Policy Framework asserts data sovereignty and cross-border collaboration, guiding us to balance national control with regional research partnerships. And United Nations Development Programme’s Digital Public Infrastructure Principles highlight open standards and inclusive design, inspiring us to pioneer open-source AI tools for local languages and challenges.
To transform these global best practices into a genuinely Zimbabwean strategy, I propose a phased, deeply participatory roadmap.
In the discovery phase, we should map existing AI initiatives across health, agriculture, and education, and conduct ethnographic field visits that bring policy-makers directly into communities.
The dialogue phase would convene provincial forums without technical presentations, replaced instead by open-ended questions and skilled facilitation in Shona, Ndebele, and English.
During the co-creation phase, hybrid working groups pairing citizens with data scientists and ethicists would draft policy modules on data governance, risk mitigation, and capacity building.
A national “AI Citizen Assembly” would then validate the near-final draft, with all feedback and revisions transparently published in local media.
Finally, implementation would proceed through pilot projects governed by community oversight committees, ensuring that policies evolve in response to real-world outcomes.
Embedding ethics into everyday AI practice is the ultimate test of this strategy’s success. We must celebrate data stewards who rigorously uphold privacy, elevate storytellers who surface algorithmic harms, and reward developers, who partner with communities to deliver public-good innovations.
When ethical reflection becomes woven into the very fabric of AI ecosystems, we ensure that our technologies serve human dignity rather than undermine it.
ICT and Courier Services minister Tatenda Mavetera, your visionary leadership, has already set Zimbabwe on a promising digital trajectory. By championing a Freirean, problem-posing approach, you can signal that our nation refuses to adopt a one-size-fits-all blueprint.
Instead, we will pioneer an Afrocentric model of AI governance where policy and people co-evolve.
Beaullah Chirume, Martin Muduva, Professor Tawanda Mushiri, Leonard Jukwa, Tendai Zengeni, and Loveness Ngwanga, the depth of your expertise is invaluable, but it gains even greater power when multiplied by the wisdom of everyday Zimbabweans.
The most profound policy insights often emerge when a farmer challenges a drone’s data or a teacher questions whether an adaptive learning app truly respects the lyricism of our languages.
Our National AI Strategy can become Zimbabwe’s defining achievement in the digital age, provided that we embrace a culture of dialogue rather than declarations, collective inquiry instead of hierarchical expertise, and engaged citizenship over passive acquiescence.
When we think deeper, we see that AI is not just code and silicon; it is a mirror reflecting our hopes, fears, and values. Will we avert our eyes, or lean in together to shape technology in the image of our highest ideals?
Sagomba is a chartered marketer, policy researcher, AI governance and policy consultant, ethics of war and peace research consultant. — [email protected]; LinkedIn: @Dr. Evans Sagomba; X: @esagomba.
