- Introduction
A national strategy is a high-level, state-led planning instrument that sets out long-term priorities and coordinates action across sectors to achieve defined development goals.
Unlike standalone policy statements, a strategy serves as an integrative framework, aligning political intent with administrative execution by setting out objectives, guiding principles, institutional arrangements, and implementation pathways.
The Zimbabwe National Artificial Intelligence Strategy 2026–2030 exemplifies this form.
It is an ambitious framework that positions AI as a driver of inclusive growth and national sovereignty, drawing on UNESCO’s AI Readiness Assessment Methodology and shaped by national consultations.
The strategy sets out eight guiding principles, including human-centric and ethical AI, transparency, inclusivity, and non-discrimination.
However, a national strategy has no direct legal force. Its authority is political and administrative, not binding. Proposals within the strategy, including ethical frameworks, truth-verification mechanisms, and data governance structures, remain normative unless underpinned by clear legal backing and effective enforcement through gazetted legislation.
The strategy is organised around three interrelated objectives:
- Embedding AI across key productive sectors (agriculture, healthcare, mining, public administration, and finance);
- Establishing Zimbabwe as a sovereign AI actor capable of controlling its own data and systems;
- Grounding AI development in Ubuntu principles and the Heritage-Based Education 5.0 model to align technology with social values and national priorities.
To guide this vision, the strategy articulates eight principles:
- Human-centric and ethical AI;
- Transparency and data sovereignty;
- Safety and data security;
- Inclusivity and non-discrimination;
- Availability and accessibility;
- Collaboration and cooperation;
- Innovation and co-creation;
- A local-first, developmental-centric approach.
Collectively, these principles seek to balance technological advancement with social considerations while anchoring AI development within national and cultural contexts.
For the three rights central to MISA Zimbabwe’s mandate, namely freedom of expression, privacy, and access to information, this governance gap is not a technical detail. It is the central problem.
Without enforceable legal safeguards, the strategy’s commitments risk remaining aspirational, while its high-risk provisions (centralised data platforms, AI surveillance infrastructure, and truth-verification systems) may be implemented without the judicial oversight and rights-based constraints that legislation alone can provide.
This analysis examines three high-risk areas in which the strategy’s design, together with Zimbabwe’s existing legal and institutional context, poses identifiable threats to digital rights.
- Freedom of Expression
The Zimbabwe National AI Strategy addresses the right to free expression primarily through its emphasis on transparency, public engagement, and ethical AI development. It introduces mechanisms such as the Nzwisiso.ai campaign and public-facing dashboards to improve public understanding of AI systems and foster trust.
These measures are presented as enabling conditions for an open and informed digital environment in which citizens can engage with emerging technologies and their societal implications.
2.1 The National Reality Check Platform
The strategy proposes the establishment of an AI-powered National Reality Check Platform for truth-verification in media and government communications. The initiative is framed as a mechanism to address misinformation.
The introduction of a centralised platform for determining or verifying “truth” raises immediate concerns about freedom of expression. The strategy does not specify which institution will manage or supervise the platform, nor does it set out criteria, processes, or safeguards for its operation.
This institutional silence creates ambiguity around who exercises authority over information verification and how that authority is constrained.
An AI-supported truth-verification system has the potential to influence which information is amplified, flagged, deprioritised, or suppressed. Without independent oversight and transparent criteria, such a platform could evolve from a tool for combating misinformation into a mechanism for shaping public discourse.
The distinction between verification and control blurs when the same system can monitor content, classify narratives, and influence visibility at scale.
This concern is heightened by Zimbabwe’s existing legal environment. Section 164C of the Cyber and Data Protection Act criminalises “false data messages” and has been used directly against journalists who exercise constitutionally protected speech.
The Cybersecurity and Monitoring Centre operates under the Office of the President and has no judicial oversight. A centralised truth-verification platform layered on this existing architecture creates an enabling environment for algorithmic content moderation without due process.
2.2 The National Interest as an Open-Ended Mandate
The strategy repeatedly emphasises concepts such as national sovereignty and national interest as guiding principles for AI governance. These terms are not defined within the strategy, nor are they explicitly tied to enforceable rights-based safeguards.
In Zimbabwe’s regulatory context, similar language has historically been used to justify interventions that affect freedom of expression. When embedded within an AI governance framework, these open-ended concepts serve as flexible mandates that can be interpreted expansively, particularly in areas involving digital communication and information flows.
AI significantly expands the state’s technical capacity to monitor, analyse, and influence information at scale. In the absence of clearly defined limits, invoking the national interest may justify deploying AI systems beyond narrowly defined regulatory objectives.
The concern is not that the strategy explicitly mandates censorship, but that it creates an enabling environment in which algorithmic mediation of expression becomes both technically feasible and politically justifiable, all without clear legal constraints.
2.3 The Chilling Effect
Beyond direct content moderation, the strategy’s surveillance-enabling provisions (discussed below under privacy) have a secondary effect on expression. Where digital activity is subject to continuous monitoring, individuals may alter their behaviour because they perceive they are being observed. When AI systems analyse communication patterns or flag content as potentially risky, this chilling effect is amplified.
Journalists, human rights defenders, and ordinary citizens may self-censor not because of any explicit prohibition, but because the technical architecture of the AI state renders visibility and risk unpredictable.
- Privacy
3.1 Data Centralisation and the Concentration of Risk
The strategy identifies fragmented databases across government institutions as a constraint and implicitly supports the consolidation and centralisation of data systems, particularly through initiatives such as Project Pangolin (the National AI and Data Platform).
Centralisation of data must be assessed not only in terms of technical efficiency, but also in relation to governance, accountability, and historical patterns of state behaviour.
Zimbabwe has a documented history of state-sponsored surveillance and weak institutional safeguards. In such an environment, consolidating fragmented databases creates conditions for mission creep.
Data collected for one purpose may be repurposed for broader state objectives that infringe the right to privacy under Section 57 of Zimbabwe’s Constitution.
Centralised databases also present higher-value targets for cyberattacks. The concentration of sensitive data increases both the likelihood and potential impact of breaches. The strategy does not sufficiently address these structural vulnerabilities.
3.2 The AI–Cybersecurity Fusion Centre
The strategy proposes establishing an AI–Cybersecurity Fusion Centre that integrates artificial intelligence into cybersecurity systems to enable real-time threat detection, monitoring, and response.
Cybersecurity systems operating in real time rely on continuous monitoring of networks, communications, and user activity. When augmented by AI, these systems can process large volumes of data, identify behavioural patterns, and make automated decisions about potential threats. This expands not only defensive capability but also the scope and intensity of surveillance.
The strategy provides no detailed information on the Fusion Centre’s governance structure, including how it will be managed, what safeguards will be in place, and how its activities will be constrained.
There is no explicit articulation of limits on data collection, retention, or use, nor clarity on how individuals may challenge actions taken on the basis of AI-driven threat assessments.
The integration of AI into cybersecurity not only strengthens defensive capacity but also expands the technical and institutional ability to monitor, analyse, and act upon digital behaviour. Where institutional frameworks required to constrain such power remain underdeveloped, the expansion of security infrastructure may inadvertently increase the scope of surveillance without a corresponding strengthening of safeguards.
3.3 Biometric Data and Irreversible Vulnerability
The strategy’s emphasis on integrated data systems and AI-enabled governance implies a growing reliance on sensitive and potentially biometric data. Unlike conventional data, biometric identifiers cannot be changed once compromised.
A breached password can be reset, but a compromised fingerprint or facial recognition profile remains permanently exposed. This creates irreversible vulnerability, where a single breach can have lifelong consequences.
The strategy relies on the Cyber and Data Protection Act as a baseline safeguard. However, evidence suggests that the underlying governance environment remains weak. The Trust and Safety Index indicates limited public confidence in online privacy and low trust in government digital systems.
The expansion and centralisation of data systems do not occur within a robust regulatory environment but within one characterised by limited institutional capacity and uneven enforcement.
- Access to Information
The strategy addresses access to information primarily through data availability, central to which is Project Pangolin, intended to aggregate and make government data accessible for AI development and policy use. This is complemented by a public-facing AI dashboard and digital literacy initiatives.
Availability does not equate to accessibility. Evidence from the ITU Universal and Meaningful Connectivity framework shows that although internet connectivity in Zimbabwe has expanded, meaningful access remains uneven, particularly along geographic, socio-economic, and gender lines.
Access to high-speed internet, data affordability, device availability, and digital literacy levels vary significantly between urban and rural populations.
Initiatives such as Project Pangolin assume that making data available will lead to broader access and utilisation. However, where connectivity is limited or unaffordable, and digital skills are uneven, large segments of the population are effectively excluded. The benefits of increased data availability are likely to be concentrated among already-connected and institutionally supported actors.
4.1 Trust as a Constraint on Information Access
Beyond structural access, trust introduces an additional constraint. The Trust and Safety Index indicates limited confidence in online privacy, as well as low levels of trust in government websites, applications, and communications.
Citizens are sceptical not only about how their data is handled, but also about the reliability and intent of information provided through official digital channels.
Where trust in government communications is low, the availability of information does not necessarily translate into its acceptance, use, or perceived legitimacy. Access to information is constrained not only by infrastructure but by credibility. State-led information systems may struggle to achieve widespread uptake in a fragmented trust environment.
4.2 Linguistic Barriers to Access
Artificial intelligence technologies are largely developed within global, predominantly English-speaking ecosystems. As a result, there is limited terminology in Zimbabwe’s local languages (Shona, isiNdebele, and others) to accurately describe AI tools, processes, and services.
Access to information is not simply a question of exposure, but of comprehension. Where individuals lack the linguistic tools to interpret complex technological concepts, information becomes abstract and inaccessible, even when technically available.
This is particularly relevant to the Nzwisiso.ai literacy campaign. Without the development of locally grounded terminology, such initiatives risk limited reach and effectiveness, particularly among non-English-speaking populations.
4.3 The National Reality Check Platform and Information Gatekeeping
The National Reality Check Platform, examined above under freedom of expression, also has direct implications for access to information. Access is not only about the availability of data but also about the diversity, plurality, and independence of information sources.
A centralised verification platform may introduce informational gatekeeping, in which certain types of content are validated while others are marginalised. In an environment where trust in government communication is already low, this may further erode confidence in official information systems and narrow the range of perspectives considered credible.
- Conclusion
The Zimbabwe National AI Strategy is conceptually coherent and politically anchored. It reflects a genuine effort to position AI within national development. However, when assessed against the rights to freedom of expression, privacy, and access to information, a consistent pattern emerges: technological capability is expanding faster than the institutional and legal frameworks needed to constrain it.
Three structural problems run through the analysis:
First, centralisation without safeguards. The strategy consolidates data, governance authority, and information verification within executive-led structures without correspondingly strengthening independent oversight, judicial scrutiny, or protections for enforceable rights.
Second, open-ended mandates. Concepts such as national interest and sovereignty are invoked without clear legal definition, creating flexible authority that can be interpreted expansively, even in contexts where similar language has historically been used to restrict rights.
Third, the readiness mismatch. The strategy assumes a digitally integrated environment capable of supporting advanced AI systems. Yet evidence on connectivity quality, affordability, digital literacy, data governance capacity, and public trust points to persistent gaps. AI does not resolve these imbalances. It amplifies them.
The window to shape Zimbabwe’s AI governance framework from a rights-based perspective is open now. It will close as legislation is drafted. The strategy itself has no legal force, but it will be used to justify legislation, regulations, and institutional mandates.
This piece is part of a series on Zimbabwe’s National AI Strategy and its implications for digital rights, curated by Helen Sithole. The series examines freedom of expression, privacy, and access to information through the lens of Zimbabwe’s evolving AI governance landscape. Writes – Helen Sithole
