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Africa's foreseeable dependence on artificial intelligence
State of play, systemic risks, warning of the Anthropic episode and strategy to avoid the trap.
How can Africa benefit from artificial intelligence without becoming a mere captive market, data producer and talent provider for ecosystems that it does not control? The question is no longer theoretical: an event that occurred at the very heart of the writing of this dossier has just given the real-scale demonstration.
1. An old story, a new form
African economic history is marked by a recurring paradox: the continent has considerable resources, but a substantial part of their transformation and development is carried out elsewhere. It exports raw materials and imports processed products, technologies, services and standards.
Artificial intelligence could reproduce this scheme in an even more subtle form. The raw material would no longer consist solely of minerals, agricultural products or energy. It would also include data, languages, behaviours, cultural productions, local knowledge and administrative documents — Collected, processed and valued by outside companies, before returning to the continent in the form of pay services or proprietary models. This dependence would then be deeper than previous industrial dependencies: it would affect knowledge, decision-making, the formation of enterprises and the very functioning of institutions.
Access to an artificial intelligence model is a contractual and political permission that can be revoked at any time. Mastery is based on sustainable data, computing, skills, infrastructure, standards and alternatives. Confounding the two is the trap this folder intends to defuse.
2. Global technology concentrated between a few powers
Modern AIA is based on a highly concentrated economy. The United States dominates several strategic layers: advanced proprietary models, cloud platforms, graphics processors, development software, financing and international distribution. China has a significant autonomous ecosystem; Europe, India and several Gulf States are seeking to build their own capacity.
This concentration means that a limited number of companies and states can set prices, access conditions, safety rules, technical standards and, where appropriate, territorial restrictions. African companies are rarely present in the layers where intellectual property and the highest margins are concentrated.
A difficult to access value chain
| Layer | Resource requirements | African dominant position |
|---|---|---|
| Semiconductors | Design, manufacturing, lithography, memories | Almost total dependency |
| Calculation | GPU, servers, networks, storage | Low and concentrated capacity |
| Cloud | Hosting, orchestration, security | Strong foreign dependency |
| Data | Corpus, quality, governance | Significant but fragmented resources |
| Models | Training, adaptation, evaluation | Low presence in border models |
| Applications | Health, finance, agriculture, administration | Significant potential |
| Distribution | API, platforms, operating systems | International domination |
Africa has relatively greater potential in specialized uses and applications than in heavy industrial layers. This specialization can become an advantage — provided that local applications are not entirely dependent on external models and clouds.
3. State of African dependency
3.1. Dependence on foundation models
Foundation models are generalist systems adaptable to many uses. When an African company develops an administrative assistant, diagnostic solution or a legal tool based on a foreign model, it generally does not control essential parameters, training data, future changes, tariffs or usage restrictions. This dependency can remain invisible as long as the service works; it appears abruptly when the supplier changes its prices, its contractual conditions, its privacy policy — or its geographical scope.
3.2 Cloud Dependence
The cloud allows fast access to efficient infrastructure, but it introduces a contractual and legal dependency: data can be processed outside the country or the continent, under the influence of foreign rights. For tax, banking, health, judicial, military or biometric data, the cloud issue becomes a matter of sovereignty and continuity of public functions.
3.3 Weak computing infrastructure and energy dependence
Advanced models require specialized processors, fast grids, storage, cooling and technical teams. African capacities remain weak and highly concentrated in some countries and major cities. An AI data centre is also an energy infrastructure: it requires stable power, high power, emergency and cooling systems. An AI policy cannot therefore be separated from energy policies, telecommunications, water, land-use planning and technical training.
3.4 Linguistic, cultural and cognitive dependence
Most African languages are insufficiently represented in the digital corpus. This weakness leads to a lower quality of responses, the exclusion of non-French- and English-speaking populations, and the gradual marginalization of linguistic heritage. A model mainly formed on external data imperfectly controls African institutions, rights, accounting standards, informal economic practices and historical references.
3.5 Dependence on data and skills
Africa produces many data, but often not digitized, fragmented, poorly documented or hosted abroad. In the absence of local infrastructures, these data can be captured and valued by external platforms: the continent risks exporting raw data and reimporting high value-added services. The pool of young talent is important, but advanced skills remain insufficient in model architecture, distributed computing, cybersecurity, algorithmic audit and data engineering — and retention of these talents remains a major challenge in the face of foreign ecosystems with better wages and direct access to computing.
4. Systemic risks to the continent
| Risk | Event | Main effect |
|---|---|---|
| Technology | Dependence on foreign models, chips, clouds and APIs | Lack of mastery of critical tools |
| Economic | Recurring payment of licences, capture of value abroad | Foreign currency outflows, low value appropriation |
| Cognitive | Models formed on small African corpus | Marginalization of local languages, standards and knowledge |
| Geopolitics | Export restrictions or limited access to partners | Access conditional on external decisions |
| Operational | Integrating AI into essential functions | Risk of interruption, locking or rising costs |
An economy that imports models, cloud, software and computing can use the AI without capturing most of its revenues. The African user pays a subscription and produces data; the supplier consolidates revenue, finances product improvement and increases its technological advance. In addition, automation can affect service activities in which several African countries were hoping to position themselves — call centres, data entry, translation, administrative support, repetitive accounting services — with a risk of deindustrialisation of services even before full industrialization.
A bank, administration or company that deeply integrates a foreign model into its processes becomes vulnerable to unavailability. This may result from a political decision, sanction, bankruptcy, cyberattack, tariff increase, removal of functionality — or a territorial restriction. It is precisely this last scenario, long presented as theoretical, which is illustrated by current events.
5. Anthropic episode: anatomy of a warning
On June 12, 2026, in the middle of the week of finalisation of this dossier, an event came to confirm point by point the central thesis of this work. The US company Anthropic, one of the world's leading suppliers of artificial border intelligence models, has received from the US government an export control directive ordering it to suspend, without delay, any access of foreign nationals to its two most advanced models, Claude Mythos 5 and its derivative version Claude Fable 5 (Official communiqué ofAnthropic).
Chronology of a unilateral decision
- LaunchAnthropic highlights the safeguards supposed to prevent unauthorized access to Mythos' most sensitive capabilities — in particular its cybersecurity capabilities — via Fable 5 commercial version.
- 12 June 2026, 17:21 Washington timeAnthropic receives a directive from the U.S. government citing reasons for national security, without detailing its technical basis (Al Jazeera).
- A few hours laterThe Directive aims to: « any foreign national, both inside and outside the United States, including foreign employees of Anthropic itself ». Without being able to distinguish in real time US users from foreign users among hundreds of millions of accounts, Anthropic simply disables both models for all its global customers (Fortune ; National Law Review).
- Anthropic reactionThe company claims to comply with the Directive while contesting its proportionality: it considers that the flaw mentioned by the authorities would be narrow, not universal, and accessible by other public models not subject to the same checks. It advocates a framework for blocking deployments deemed dangerous that is transparent, fair and based on verifiable technical facts — Considering that the procedure followed here does not meet these criteria (detailed analysis of Snyk).
An American decision, an immediate global effect
The most instructive aspect of this episode, for an African observer, is not so much the nature of the fault invoked as the mechanics of the decision itself. A national administration was able, in the space of one evening, to cut off access to a tool used by hundreds of millions of people around the world, without notice, without a call procedure accessible to the users concerned, and without any possibility for third countries — of which no African State — to make a point of view. The supplier's nationality was sufficient to render the extraterritorial decision by construction: any non-American user, wherever he is on the planet, was placed overnight on the wrong side of a legal border he had not chosen.
Companies that had built deep integrations around these models — internal tools, business platforms, code management systems — have been forced to urgently review their architectures, without immediately available alternatives offering an equivalent level of capacity.
Five lessons for Africa
For any African institution — bank, tax administration, audit firm, cybersecurity operator — having built a critical process around a single leading model, this episode must be read as a concrete alarm signal, not as a distant peripetia. The recommendations already made in this dossier — multi-model architecture, reversibility clause, open backup model, technical abstraction layer, regular rocking tests — It is no longer a matter of theoretical prudence: they now describe a risk already materialised, identically, for a general public product.
6. Four scenarios by 2030-2040
| Scenario | Main advantage | Principal risk | Evaluation |
|---|---|---|---|
| Passive consumption | Rapid adoption | Absolute dependence | Not sustainable |
| National hubs | Emergence of champions | Continental Fragmentation | Useful but insufficient |
| Geopolitical diversification | Reduction of supplier risk | Multiple dependency | Defensive measure |
| Regional autonomy | Trading and substitution capacity | Complex coordination | Most credible option |
In the first scenario, the continent quickly adopts foreign tools without developing significant infrastructure or local capacities: productivity gains are fast, but dependence, foreign exchange outflows and the marginalization of local languages are increasing — exactly the type of vulnerability that Anthropic episode illustrates. In the fourth, countries mutualize computing centres, cloud trust, data, specialized models and training programs: this scenario does not remove dependence on foreign technologies, but it allows them to be used from a less vulnerable position — and less exposed to an external unilateral decision.
7. Avoiding the trap: the graduated autonomy strategy
Sovereignty does not mean that each country has to produce its chips, cloud and big model. It consists of maintaining the ability to choose, change suppliers, protect sensitive data, audit critical systems and maintain critical functions in case of failure — the same one that has just reached hundreds of millions of users without notice.
| Concept | Definition | Relevance |
|---|---|---|
| Autorate | All production nationally | Unrealistic for most States |
| Absolute independence | Not dependent on outside actors | Short-term unreachable |
| Functional sovereignty | Monitoring key decisions and data | Required |
| Strategic autonomy | Limit critical dependencies, organize alternatives | Priority objective |
| Diversification | Distribute risks among multiple suppliers | Additional measure |
The cost of infrastructure requires a regional approach: computing hubs could be carried out by the African Union, ECOWAS, WAEMU, CEMAC, SADC and the East African Community, accessible to universities, administrations, companies and research centres. Smaller models, the Edge AI and the TinyML are particularly suitable for environments where connectivity and energy are constrained; they reduce cloud dependence and allow robust local use — including in the event of a breach of access to an external supplier.
The most rational objective is not to compete immediately with the largest generalist models, but to build specialized models better suited to local needs: OHADA law and African jurisprudence, SYSCOHADA and business management, national languages and voice synthesis, tropical agriculture and water management, public health, administration and land, natural resources and regional trade. Critical services should never depend on a single model: any architecture should include a main model, an alternative provider, an open backup model, an abstraction layer and regular rollover tests — the public order must, for its part, impose location of sensitive data, reversibility, transparency of subcontractors and explicit continuity clause in case of export restriction.
8. Operational road map
Phase 1 — 2026-2028: secure and map
- Mapping critical infrastructure, skills, data and dependencies.
- Classify public data according to their sensitivity level.
- Insert reversibility clauses in public and private contracts.
- Prohibit single model dependence for critical services.
- Constitute African linguistic, legal and administrative corpus.
- Train decision makers, engineers, professionals and auditors.
- Identify regional computing and cloud trust projects.
- Adopt or update national AI strategies.
Phase 2 — 2028-2032: sharing and producing
- Implementation of regional calculation poles.
- Creating Clouds of Trust.
- Development of African specialized models.
- Strengthening of laboratories and universities.
- Integration of African languages.
- Financing of local enterprises.
- Harmonization of standards and certification mechanisms.
Phase 3 — 2032-2040: getting in the value chain
- Develop advanced design and evaluation capabilities.
- Participate in international research programs.
- Master certain hardware and software segments.
- Export specialized platforms.
- Negotiate collectively access to border technologies.
9. Governance, funding and indicators
| Level | Key responsibilities |
|---|---|
| Continental | Common principles, standards, diplomatic positions, research priorities |
| Regional | Computing centres, shared cloud, training, certification, dedicated funds |
| National | Regulation, sovereign data, education, public order, local ecosystem |
The indicators to be followed over time include the GPU capacity available locally and regionally, the number of African languages integrated into digital tools, the number of engineers, researchers, lawyers and auditors trained, and the share of critical systems with a reversibility plan — and, even more directly after the June 2026 episode, the share of AI expenditures paid to foreign suppliers without an identified alternative.
10. General conclusion — of dependence on negotiated interdependence
Africa cannot and must not escape the global ecosystem of artificial intelligence. Foreign technologies can accelerate modernization, improve public services, support health, agriculture and education. The danger lies in their use without a mastery strategy, no alternative, no data protection and no progressive construction of African capabilities. Technology available today can be withdrawn tomorrow by an external decision — This is no longer a working hypothesis, it is a fact observed in real time during the writing of this dossier.
The solution does not lie in an unrealistic technological downturn, nor in an unconditional openness. It is based on a negotiated interdependence: using the best available technologies while maintaining the ability to choose, audit, adapt, replace and continue to function.
The trap would be to confuse access and control. Access is a revocable permission. Mastery is a sustainable capacity. Africa must invest less in the appearance of innovation and more in foundations: energy, data, calculation, skills, research, standards and regional cooperation.
To go further on BAOBIZZ
This dossier is part of a broader reflection that BAOBIZZ has been pursuing for several months on artificial intelligence. The following articles, classified under the heading 🤖 IA & Tech of the blog summary, illuminate from other angles some of the issues addressed here.
- Artificial intelligence and law & numeral professions: mutations, risks and opportunities — on audit, consulting and the number directly affected by automation mentioned in Section 4.
- Accompanying the head of business: the accountant, strategic vision in the era of artificial intelligence — the role of the digit professions in the rational adoption of AI by African companies.
- School at the time of Artificial Intelligence: reinventing teaching to train tomorrow's citizens — echo the dependency on skills dealt with in Section 3.5.
- The end of the truth: when artificial intelligence makes a world of doubts — on cognitive and cultural risk developed in section 4.
- Submitted, docile and perfect: the feminization of artificial intelligences, mirror of an algorithmic patriarchate — on cultural biases encoded in models designed outside of Africa.
- Marshall McLuhan in the face of artificial intelligence: the medium become spirit — a complementary theoretical reading of cognitive dependence on dominant models.
- Virtual Masters: How African online scams trap the world — on the misuse of AI from the continent, in contrast to the dependence suffered.
- Learning time: artificial intelligence or man's temptation without effort — on the risk of individual dislearning, as a mirror of cognitive deindustrialisation dealt with in section 4.
- Metavers: technological mirage or the future of the Internet? — Another example of a technological promise to consider with the same methodological caution.
See also the interactive tool « Will your job survive the AI? », which makes it possible to assess in practice the exposure of a given profession to the risks described in this dossier, as well ascomplete article index to explore the entire IA & Tech section.
Sources and references
- African Union, Continental Artificial Intelligence StrategyJuly 2024.
- World Bank, Digital Progress and Trends Report 2025: Strengthening AI Foundations.
- UNCTAD, Technology and Innovation Report 2025 — Inclusive Artificial Intelligence for Development.
- Stanford Institute for Human-Centered AI, AI Index Report 2026.
- UNESCO, work on AI in education and on African languages in the face of AI.
- OECD, AI Governance in AfricaCase studies and recommendations, 2026.
- International Telecommunication Union, AI Standards for Global Impact: From Governance to Action.
- Anthropic, public declaration of 12 June 2026 on the suspension of access to Fable 5 and Mythos 5.
- Al Jazeera, « US orders Anthropic to disable AI models for all foreign nationals »13 June 2026.
- Fortune, « Disable Anthropic Fable and Mythos AI models following U.S. government export ban »13 June 2026.
- National Law Review, « AI Company Anthropic Suspends Access to Claude Fable 5, Claude Mythos 5 Following US Export Control Directive ».
- Snyk, « When a Government Pulls an AI Model: What the Fable 5 and Mythos 5 Suspension Means for Security Teams ».
- Africa Data Centres Associationsectoral work on data centre capacity in Africa.
Quantitative and regulatory data must be updated before any official publication, with some developments in the sector particularly rapid.
