Country Profile on AI Governance: Guinea (Conakry)

Mean of all 10 indicator scores. West Africa mean 1.70 · all 54 states mean 1.76.

1. S1.1

   National AI strategy existence

   Score 3 / 4

   The Government of Guinea formally validated a 10-year National AI Roadmap (2026–2035) on December 20, 2025.

   Note: The country used the UNDP's Artificial Intelligence Landscape Assessment (AILA) framework to finalize this adoption.

   Sources notreafrik.com (opens in a new tab)

2. S1.2

   Strategy adoption date

   Score 0 / 4

   Formally validated during a high-level national workshop on December 19–20, 2025.

   Note: Validated in partnership with the United Nations Development Programme (UNDP).

   Scoring basis Threshold applied. Raw value: none (adoption date). No formally adopted national AI strategy. Raw value read from the evidence: "Formally validated during a high-level national workshop on December 19–20, 2025." [validation workshop only; formal adoption not stated (score_raw 2025-12-01). Listed for second-edition review: The Thresholds sheet counts Guinea among the strategies adopted within 12 months, which would score 1. The final score is 0 because the evidence shows a validation workshop only. S1.1 scores 3 on the same event.

   Sources guineenews.org (opens in a new tab)

3. S1.3

   Political commitment signals

   Score 3 / 4

   High-level backing by the transition leadership under Gen. Mamadi Doumbouya, culminating in the launch of the "DouIA2" initiative and the signing of the "Manifesto of Conakry" in April 2026.

   Note: Minister of Digital Economy, Rose Pola Pricemou, positioned AI as a central pillar of national sovereignty.

   Sources csig.edu.gn (opens in a new tab)

4. S1.4

   Dedicated AI budget allocation

   Score 1 / 4

   Financial tracking for the 2026–2035 roadmap remains deeply embedded within the broader Ministry of Digital Economy and ICT transformation budgets.

   Note: No standalone, ring-fenced national budget exclusively for AI has been identified as an isolated line item yet.

   Sources mpten.gov.gn (opens in a new tab)

5. S1.5

   AU Continental AI Strategy alignment

   Score 2 / 4

   The roadmap explicitly references alignment with regional frameworks (Smart Africa alliance guidelines) and the core principles of the AU Continental Strategy Phase I.

   Note: Guinea hosted the TAS 2025 under the theme "AI for Africa", indicating high macro-policy awareness.

   Sources smartafrica.org (opens in a new tab)

6. S1.6

   Multi-stakeholder consultation

   Score 2 / 4

   The AILA-driven validation process in late 2025 involved formal tech working groups, domestic university researchers, and private sector representatives.

   Note: While formal consultation occurred for the roadmap's design, a permanent multi-stakeholder monitoring mechanism is still emerging.

   Sources osiris.sn (opens in a new tab)

7. S1.7

   Sector prioritisation

   Score 2 / 4

   The strategy explicitly targets key socio-economic pillars: public administration modernization, mining efficiency, and agricultural optimization.

   Note: Focuses on using edge AI and data analytics to mitigate corruption and boost structural crop yields.

   Sources csig.edu.gn (opens in a new tab)

8. S1.8

   Implementation roadmap

   Score 3 / 4

   The 10-year plan is divided into 3 clear operational phases: 1. Foundations & Data Governance; 2. Public Service AI Integration; 3. Regional AI Leadership.

   Note: Meets the criteria for a structured phased plan, moving from base architecture to execution.

   Sources notreafrik.com (opens in a new tab)

9. S1.9

   Monitoring and evaluation framework

   Score 1 / 4

   The M&E framework is legally planned under Phase 1 of the 2026–2035 roadmap but has not yet produced active, open annual public reporting cycles.

   Note: Currently marked as "Planned" because operational tracking tools are still being deployed under the new DouIA2 transition.

   Sources guineenews.org (opens in a new tab)

10. S1.10

    Strategy review mechanism

    Score 1 / 4

    Strategy adjustments are structured on an ad-hoc basis shifting between the technical iteration of DouIA1 to DouIA2, without an institutionalized adaptive calendar.

    Note: Review updates remain bound to ongoing executive initiatives rather than statutory auto-reviews.

    Sources lelynx.net (opens in a new tab)

Mean of the 9 scored indicators; 1 carries no score. West Africa mean 1.18 · all 54 states mean 1.32.

No score: 1 not scored (excluded from the mean).

1. G2.1

   AI-specific legislation

   Score 1 / 4

   There is no dedicated AI law enacted in Guinea. However, preliminary regulatory discussions have begun following the official validation of the National AI Roadmap (2026–2035) in late 2025.

   Note: Scored as "Under discussion" due to technical workshops stemming from the newly adopted national AI strategy.

2. G2.2

   Data protection law status

   ○Not scored: Excluded from the pillar mean

   Guinea enacted Law No. L/2016/037/AN on Cybersecurity and Personal Data Protection. However, the data protection authority (APD) established by this text is not yet fully operational on the ground.

   Note: The text is officially Enacted, but practical enforcement suffers from a lack of a fully structured, autonomous oversight authority.

   Scoring basis Not determined; excluded from the pillar mean.

   Sources dataprotection.africa (opens in a new tab)

3. G2.3

   DPA AI mandate

   Score 1 / 4

   Because the data protection authority is not yet structurally independent or active, it lacks any formal or informal mandate to oversee AI algorithms or data processing models.

   Note: The 2016 framework did not anticipate specific AI challenges like algorithmic accountability or deepfakes.

   Sources africadataprotection.org (opens in a new tab)

4. G2.4

   DPA staffing and budget

   Score 0 / 4

   No independent budget or full-time permanent staff has been allocated specifically to a functional data protection authority in Guinea.

   Note: Oversight responsibilities are temporarily absorbed at the macro level by the internal technical directorates of the MPTEN.

   Scoring basis Threshold applied. Raw value: 0 (FTE staff).

   Sources dtri.uneca.org (opens in a new tab)

5. G2.5

   AI regulatory body existence

   Score 1 / 4

   The establishment of a dedicated National AI Governance Council was formally proposed during the validation of the 2026–2035 strategy and subsequent national tech forums.

   Note: Currently sits at the administrative proposal and project design phase.

   Sources csig.edu.gn (opens in a new tab)

6. G2.6

   Institutional design model

   Score 0 / 4

   A specific institutional design model has not been formalized yet; Guinea is currently under a ministry-led incubation phase for tech policy.

   Note: No structural governance model (such as a hybrid or independent agency) is legally defined at this stage.

7. G2.7

   Malabo Convention ratification

   Score 2 / 4

   Guinea is among the African states that have formally deposited their instruments of ratification for the AU Malabo Convention on Cyber Security and Personal Data Protection.

   Note: Ratification is confirmed at the African Union level, but structural local implementation across domestic agencies remains incomplete.

   Sources dataprotection.africa (opens in a new tab)

8. G2.8

   Enforcement actions taken

   Score 0 / 4

   No public enforcement actions, formal investigations, or fines related to the misuse of AI systems or data pipelines have been recorded in Guinea.

   Note: Zero score due to the absence of case law or active regulatory complaints.

9. G2.9

   Extraterritorial provisions

   Score 0 / 4

   Existing legislation (the 2016 law) does not contain extraterritorial provisions capable of regulating or sanctionnering foreign AI systems operating from outside national borders.

   Note: The current legal framework remains strictly territorial, focusing primarily on traditional cybercrime.

10. G2.10

    IP framework for AI

    Score 0 / 4

    Guinea's intellectual property framework (governed by the OAPI Bangui Agreement) has not undergone any formal review or amendment to address AI-generated content or copyright ownership.

    Note: Intellectual property rights in Guinea remain strictly limited to direct human creations under existing copyright laws.

    Sources oapi.int (opens in a new tab)

Mean of the 9 scored indicators; 1 carries no score. West Africa mean 1.40 · all 54 states mean 1.51.

No score: 1 context only.

1. I3.1

   Data center count

   Score 2 / 4

   Guinea currently has 2 primary active colocation/public data facilities: the state-built national data center operated by SOGEB (Société de Gestion du Backbone National) and the commercial data tier managed by GUILAB.

   Note: Most small-to-medium enterprises and banks still rely heavily on localized in-house server rooms or remote European servers.

   Scoring basis Threshold applied. Raw value: 2 (data centres).

2. I3.2

   Data center capacity (MW)

   Score 1 / 4

   The cumulative estimated power capacity across the available sovereign server infrastructure in Conakry is estimated at approximately 1.5 MW.

   Note: Power stability remains a major operational constraint, causing facilities to rely heavily on backup generators.

   Scoring basis Threshold applied. Raw value: 1.5 (MW).

   Sources worldbank.org (opens in a new tab)

3. I3.3

   Submarine cable landing points

   Score 1 / 4

   Guinea officially has 1 operational submarine cable landing point located in Conakry for the ACE (Africa Coast to Europe) cable. A construction agreement was signed in May 2026 to add a second connection via the Medusa Africa su

   Note: The Medusa Africa cable link is planned to go live between 2029-2030 to end the country's single-cable vulnerability.

   Scoring basis Threshold applied. 1 cable systems (TeleGeography, accessed 2026-10-06).

   Sources developingtelecoms.com (opens in a new tab)

4. I3.4

   International bandwidth (Gbps)

   Score 1 / 4

   The total lit international bandwidth capacity passing through the ACE landing station to service local ISPs sits around 45 Gbps.

   Note: Capacity is highly bottlenecked during marine cable fault incidents along the West African coast.

   Scoring basis Threshold applied. 45 Gbps ÷ 14.75m = 3.05 Gbps per million.

   Sources guilab.com.gn (opens in a new tab)

5. I3.5

   Hyperscaler presence

   Score 0 / 4

   No global public cloud hyperscalers (AWS, Microsoft Azure, Google Cloud, or Oracle) have built edge zones or physical cloud data centers within Guinean borders.

   Note: Cloud workloads are routed through South African, European, or regional West African nodes (like Côte d'Ivoire).

   Sources smartafrica.org (opens in a new tab)

6. I3.6

   GPU/HPC access

   Score 0 / 4

   There are no dedicated high-performance computing (HPC) environments or commercial GPU clusters (such as Nvidia H100s/A100s) available domestically for AI training.

   Note: Local research institutes and universities operate solely on standard CPU-based cloud slices or consumer-grade hardware.

   Sources csig.edu.gn (opens in a new tab)

7. I3.7

   Data localisation provisions

   Score 1 / 4

   Data localization requirements are strictly sectoral, focusing primarily on financial/banking records under central bank (BCRG) rules and public administrative data.

   Note: The general data protection law of 2016 outlines data care principles but lacks comprehensive domestic cloud storage mandates for all private sectors.

   Sources dtri.uneca.org (opens in a new tab)

8. I3.8

   Cross-border data flow framework

   Score 2 / 4

   Cross-border transfers are governed by a regional framework. Guinea has ratified the AU Malabo Convention and aligns with the ECOWAS Supplementary Act on Personal Data Protection.

   Note: Transfers outside the ECOWAS zone require authorization, but structural local enforcement mechanisms remain weak.

   Sources dataprotection.africa (opens in a new tab)

9. I3.9

   Foreign AI surveillance spending

   ○Context only: Context flag outside the score

   No explicit, unclassified budget figures are publicly disclosed for foreign AI-enabled biometric surveillance systems or smart city camera infrastructure.

   Note: While certain facial recognition architectures exist near border zones, funding structures remain opaque.

   Scoring basis Context flag; outside the score.

10. I3.10

    Sovereign cloud initiatives

    Score 1 / 4

    A domestic sovereign cloud solution to host all digitized public administrative tasks and vital registries is currently planned under Phase 1 of the National AI Strategy (2026-2035).

    Note: Ranked as "Planned" because physical data center migration and localization architectures are still being drafted by SOGEB.

    Sources notreafrik.com (opens in a new tab)

Mean of all 10 indicator scores. West Africa mean 1.14 · all 54 states mean 1.20.

1. H4.1

   AI researchers per million

   Score 1 / 4

   Estimated at fewer than 1 AI researcher per million population. Active AI specialists are mostly localized within the newly founded West African Institute of Mathematics and specific private tech cells.

   Note: The absolute pool of peer-reviewed AI researchers inside Guinea remains extremely small, though growing.

   Scoring basis Threshold applied. Raw value read from the evidence: "Estimated at fewer than 1 AI researcher per million population." [score_raw = 0.8]. Listed for second-edition review: The raw value is an unsourced estimate.

   Sources ioam.uganc.edu.gn (opens in a new tab)

2. H4.2

   DPA staff with AI competency

   Score 0 / 4

   Since the national Data Protection Authority (APD) is not yet structurally or operationally independent, there are 0 full-time DPA staff members with explicit AI technical skills.

   Note: Technical reviews are handled ad-hoc by MPTEN ministry IT personnel rather than dedicated DPA computer scientists.

   Scoring basis Threshold applied. Raw value: 0 (staff).

   Sources dtri.uneca.org (opens in a new tab)

3. H4.3

   University AI programs

   Score 2 / 4

   There are exactly 2 higher education institutions offering formal advanced degrees in AI: the West African Institute of Mathematics (IOAM) at UGANC (Master & PhD in AI & Data Science) and Kofi Annan University of Guinea (UKAG) (Master in AI & Data Science).

   Note: These programs were launched to address the massive local deficit in advanced computing and data engineering.

   Scoring basis Threshold applied. Raw value: 2 (universities).

   Sources ioam.uganc.edu.gn (opens in a new tab)

4. H4.4

   African-authored AI publications

   Score 1 / 4

   Fewer than 5 academic publications in major indexed AI/ML journals feature an author explicitly affiliated with a domestic Guinean institution annually.

   Note: Most local tech papers focus broadly on general ICT, infrastructure deficits, or cybersecurity rather than core ML architecture models.

   Scoring basis Threshold applied. 2.0 papers/yr ÷ 14.75m people = 0.14 per million (floors applied). Raw value read from the evidence: "Fewer than 5 academic publications in major indexed AI/ML journals" [score_raw = 4.8; source used: "major indexed AI/ML journals"]. Checked against the evidence on 7 October 2026: confirmed.

   Sources researchgate.net (opens in a new tab)

5. H4.5

   AI patents filed

   Score 0 / 4

   No AI-related or software algorithmic patents have been filed or registered domestically with national branches of OAPI by Guinean entities.

   Note: Software algorithms are generally protected under copyright framework rather than industrial patents under the Bangui Agreement.

   Scoring basis Threshold applied. Raw value: 0 (AI patent applications/year).

   Sources oapi.int (opens in a new tab)

6. H4.6

   K-12 CS education

   Score 1 / 4

   Computer science in public schools is rare, but early pilot steps have been initialized under the Ministry of National Education's structural reform roadmap.

   Note: Access is largely confined to premium private high schools in Conakry offering specialized international IT tracks.

   Sources universiteactu.com (opens in a new tab)

7. H4.7

   AI workforce training programs

   Score 1 / 4

   Government-backed AI training is currently marked as "Planned" and "Pilot" via the emerging ecosystem setup at the Cité des Sciences et de l'Innovation de Guinée (CSIG).

   Note: Initial educational modules have been framed through strategic agreements (e.g., with Tether for tech literacy) to train local youth.

   Sources guinee7.com (opens in a new tab)

8. H4.8

   Labour transition policy

   Score 0 / 4

   There is no government framework or labor policy addressing automation, job displacement, or workforce re-skilling due to AI deployment.

   Note: The immediate policy focus is on baseline digital job creation rather than managing structural algorithmic displacement.

9. H4.9

   Informal economy AI assessment

   Score 0 / 4

   No formal studies or institutional assessments have been conducted by the government regarding the impact or integration of AI within Guinea's massive informal economy.

   Note: The 10-year strategy focuses primarily on formal public administration and structured farming/mining sectors.

10. H4.10

    African language NLP coverage

    Score 0 / 4

    There is no meaningful, native NLP or LLM framework supported directly by domestic Guinean research for major local languages (Pular/Fula, Mandinka, Susu).

    Note: While certain global open-source community groups are gathering baseline text datasets, no mature localized LLM pipelines exist within state institutions yet.

    Scoring basis Threshold applied. Raw value: 0 of 3 (languages supported / major languages), normalised 0. 0% of major domestic languages. Raw value read from the evidence: "There is no meaningful, native NLP or LLM framework supported directly by domestic Guinean research for major local languages (Pular/Fula, Mandinka, Susu)." [s. Checked against the evidence on 7 October 2026: confirmed.

    Sources masakhane.io (opens in a new tab)

Mean of all 10 indicator scores. West Africa mean 1.04 · all 54 states mean 1.05.

1. N5.1

   AI companies count

   Score 0 / 4

   No official registry from MPTEN or APIP includes companies exclusively specializing in AI. Local commercial tech activity remains limited to general IT services.

   Note: Embryonic niche market; the very few automated or AI-driven implementations remain integrated within generic SaaS applications.

   Scoring basis Threshold applied. Raw value: 0 (companies). Raw value read from the evidence: "No official registry from MPTEN or APIP includes companies exclusively specializing in AI." [directory used: MPTEN/APIP registries]. Checked against the evidence on 7 October 2026: confirmed.

   Sources service-public.gov.gn (opens in a new tab)

2. N5.2

   Private AI investment (USD)

   Score 0 / 4

   World Bank digital economy diagnostics and private equity monitoring confirm the absence of tracked private VC capital flowing into Guinea's AI space.

   Note: Tech funding inside the country is almost exclusively directed toward baseline telecom infrastructure and Fintech expansion.

   Scoring basis Threshold applied. Raw value: 0 (USD/year). Raw value read from the evidence: "confirm the absence of tracked private VC capital flowing into Guinea's AI space". Checked against the evidence on 7 October 2026: confirmed.

   Sources thedocs.worldbank.org (opens in a new tab)

3. N5.3

   AI incubators/accelerators

   Score 0 / 4

   Active domestic tech hubs (such as Saboutech) or university-led incubation cells are generalist. No acceleration structure targets AI software models natively.

   Note: While CSIG provides foundational data training workshops, a dedicated, institutionalized AI-specific corporate accelerator is absent.

   Scoring basis Threshold applied. Raw value: 0 (incubators/accelerators).

   Sources csig.edu.gn (opens in a new tab)

4. N5.4

   Regulatory sandbox (AI)

   Score 0 / 4

   No live or planned regulatory testing environment, programmatic exemption spaces, or fintech-style AI sandboxes are cited by ARPT or MPTEN.

   Note: Scored as "None". National tech focus is currently locked onto standard digital laws and infrastructure security consolidation.

   Sources service-public.gov.gn (opens in a new tab)

5. N5.5

   Government AI procurement

   Score 0 / 4

   Public procurement guidelines do not outline specialized legal frameworks, preference clauses, or set-asides for purchasing domestic AI platforms.

   Note: Marked as "No". Public software contracts focus on basic digitisation of public administrative records and tax databases.

   Sources thedocs.worldbank.org (opens in a new tab)

6. N5.6

   AI safety evaluation capacity

   Score 0 / 4

   No testing lab, national computing center, or statutory body (including ANSSI Guinea) has the internal infrastructure to run algorithmic audit tools.

   Note: Scored as "None". Strategic institutional attention is prioritized on traditional perimeter network cybersecurity.

   Sources oacps-ri.eu (opens in a new tab)

7. N5.7

   ISO/IEC 42001 adoption

   Score 0 / 4

   The ISO/IEC 42001 international standard for AI Management Systems has not yet been introduced or integrated into state industrial policies.

   Note: Assessed as "Unknown". Local enterprises and ministry sub-directorates have not deployed formal auditing workflows.

   Sources dounia.org (opens in a new tab)

8. N5.8

   Standards body AI competency

   Score 1 / 4

   The Guinean Institute for Standardization and Metrology (IGNM) exists but targets traditional industries and agriculture, missing an AI committee.

   Note: Scored as "Exists, no AI focus". Broader technical frameworks for the digital economy are only beginning to see preliminary standardization scoping.

   Sources service-public.gov.gn (opens in a new tab)

9. N5.9

   AI risk assessment frameworks

   Score 0 / 4

   There are no regulatory guidelines, voluntary baseline standards, or risk management matrices designed to evaluate algorithmic deployment in Guinea.

   Note: Scored as "None". Tech risk assessments are restricted to standard business continuity paradigms and data privacy compliance.

   Sources oacps-ri.eu (opens in a new tab)

10. N5.10

    University-industry AI partnerships

    Score 1 / 4

    Multi-stakeholder tech forums and ecosystem alignment spaces exist (such as the DounIA platform and specific CSIG workshops), bridging academia and developers.

    Note: Scored as "Informal". These spaces facilitate broad skill transfers regarding modern data structures but lack formal corporate joint R&D labs.

    Sources dounia.org (opens in a new tab)

Mean of all 10 indicator scores. West Africa mean 1.21 · all 54 states mean 1.26.

1. E6.1

   Algorithmic impact assessment

   Score 0 / 4

   Digital legislation under MPTEN oversight focuses on data privacy and cybercrime, without statutory clauses requiring automated impact evaluations.

   Note: Marked as "None". Impact assessments are exclusively mandated for environmental or standard structural infrastructure projects.

   Sources service-public.gov.gn (opens in a new tab)

2. E6.2

   Bias audit requirements

   Score 0 / 4

   National tech laws lack specific mandates or evaluation criteria for algorithmic drift, data discrimination, or bias testing across public and private platforms.

   Note: Scored as "None". Automated decision-making audits have not yet been codified into Guinea's digital frameworks.

   Sources thedocs.worldbank.org (opens in a new tab)

3. E6.3

   Transparency obligations

   Score 0 / 4

   No legal statutes impose public notice mandates or algorithmic explainability standards when interacting with or deploying autonomous systems.

   Note: Scored as "None". Standard data protection rights focus strictly on access, modification, and data retention limits.

   Sources service-public.gov.gn (opens in a new tab)

4. E6.4

   Citizen redress mechanism

   Score 1 / 4

   While no AI-dedicated window exists, citizens can file generalized administrative complaints through the Data Protection Authority (APDP) regarding unlawful automated data processing.

   Note: Scored as "DPA complaint" (represented here as basic regulatory recourse). True automated redress pathways are completely integrated within broad privacy remits.

   Sources service-public.gov.gn (opens in a new tab)

5. E6.5

   Judicial AI remedy

   Score 0 / 4

   The Guinean judicial apparatus operates under traditional civil and commercial frameworks without past litigation or judicial precedent concerning automated algorithms.

   Note: Marked as "No precedent". Judges and specialized commercial courts lack dedicated training curricula on algorithmic liability.

   Sources oacps-ri.eu (opens in a new tab)

6. E6.6

   AI advisory body diversity

   Score 0 / 4

   No statutory, interministerial, or independent national AI council or advisory body has been formally gazetted or instituted.

   Note: Marked as "No advisory body". Broader scientific guidance falls under generalist research entities.

   Sources service-public.gov.gn (opens in a new tab)

7. E6.7

   Global AI governance participation

   Score 1 / 4

   Guinea participates as an observer or general voter within standard consensus-driven UN platforms (e.g., ITU, UNESCO AI Ethics recommendations) but holds no active seats in GPAI or OECD AI groups.

   Note: Scored as "Observer". Broad multinational declaration sign-off occurs at regional and global levels without high-frequency operational committee presence.

   Sources unesdoc.unesco.org (opens in a new tab)

8. E6.8

   Civil society AI engagement

   Score 1 / 4

   Civil society organizations, digital rights advocates, and tech collectives participate via ad-hoc workshops and panel consultations organized during multi-stakeholder forums.

   Note: Scored as "Ad hoc consultation". Forums like the DounIA platform and local internet governance summits host civil society but lack binding administrative roles.

   Sources dounia.org (opens in a new tab)

9. E6.9

   African ethical framework reference

   Score 0 / 4

   Incipient internal digital strategy discussions focus on replicating standard European or international tech governance frameworks, missing references to Indigenous ethical philosophies.

   Note: Scored as "No reference". Legal adaptations focus on technical harmonization with regional ECOWAS regulations.

   Sources oacps-ri.eu (opens in a new tab)

10. E6.10

    Youth participation

    Score 1 / 4

    Youth engineers, graduate researchers, and youth-led tech communities participate in specific capacity-building roundtables and innovation ecosystem workshops.

    Note: Scored as "Ad hoc". The Cité des Sciences et de l'Innovation actively opens technical workshops and data-training labs to youth, though without formal decision-making seats.

    Sources csig.edu.gn (opens in a new tab)

Mean of all 10 indicator scores. West Africa mean 1.66 · all 54 states mean 1.55.

1. R7.1

   AU AI Strategy alignment

   Score 1 / 4

   National digital policymakers within the MPTEN are structurally aware of the African Union Continental AI Strategy, but a formal transposition or strategic alignment mapping has not been officially launched.

   Note: Scored as "Awareness". National priorities remain anchored in standard digital transformation, cybersecurity, and connectivity frameworks.

   Sources service-public.gov.gn (opens in a new tab)

2. R7.2

   Kigali Declaration endorsement

   Score 3 / 4

   The high-level African declarations on AI and tech governance, including the outcomes of regional ministerial steps like the Kigali frameworks, are under institutional review by the Ministry's digital directorates.

   Note: Scored as "Under consideration". Diplomatic endorsement processes for emerging continental digital protocols are handled at the interministerial level.

   Scoring basis Official signatory list applied. Signatory of the Africa Declaration on AI (Kigali, 4 April 2025), C4IR list: "Endorsed" = 3.

   Sources c4ir.rw (opens in a new tab) · thedocs.worldbank.org (opens in a new tab)

3. R7.3

   REC AI governance coordination

   Score 2 / 4

   Guinea actively coordinates with the Economic Community of West African States (ECOWAS) on regional digital harmonization, cyber security conventions, and cross-border tech infrastructure acts.

   Note: Scored as "Active participant" regarding broad Regional Economic Community (REC) digital frameworks. Specialized sub-committees on AI are still embryonic.

   Sources service-public.gov.gn (opens in a new tab)

4. R7.4

   Cross-border AI agreements

   Score 0 / 4

   No bilateral treaties, technical memoranda of understanding (MoUs), or cross-border regulatory governance agreements targeting artificial intelligence models exist.

   Note: Scored as "None". Current cross-border digital arrangements focus exclusively on physical fiber optic connectivity and regional roaming protocols.

   Sources oacps-ri.eu (opens in a new tab)

5. R7.5

   Election integrity AI provisions

   Score 0 / 4

   National electoral regulations, organic laws, and institutional codes do not contain clauses or specific guidelines addressing deepfakes or automated micro-targeting.

   Note: Scored as "None". Electoral safeguards follow traditional statutory formats regarding media access and standard public broadcast regulations.

   Sources service-public.gov.gn (opens in a new tab)

6. R7.6

   Disinformation response framework

   Score 1 / 4

   Synthetic media and algorithmic disinformation campaigns are handled reactively by state communication regulators and security branches on an incident-by-incident basis.

   Note: Scored as "Ad hoc". While general cyber legislation penalizes the spread of false news online, a specialized, AI-native counter-disinformation framework does not exist.

   Sources thedocs.worldbank.org (opens in a new tab)

7. R7.7

   AI election incidents documented

   Score 1 / 4

   There are zero officially verified, audited, or systematically documented cases of AI-driven deepfakes or automated systemic interference in national elections.

   Note: Kept at "0" for the metric score. Monitoring systems lack specialized forensic tools to definitively categorize or archive algorithmic operations.

   Scoring basis Threshold applied. Raw value: 1 (rule band). Scored on documented institutional response, not incident count.

   Sources service-public.gov.gn (opens in a new tab)

8. R7.8

   Platform content moderation

   Score 1 / 4

   Intermittent and informal administrative outreach occurs with major social media networks regarding public safety, but no binding national parameters exist for AI content moderation.

   Note: Scored as "Informal dialogue". Regulatory touchpoints rely on broad standard escalations rather than codified algorithmic compliance frameworks.

   Sources thedocs.worldbank.org (opens in a new tab)

9. R7.9

   Geneva Dialogue participation

   Score 2 / 4

   A high-level technical delegation involving regional digital fellows and ministerial representatives is actively planned for the key global governance events.

   Note: Scored as "Delegation planned". This matches the structured framework of ongoing international technical and diplomatic representation for July 2026.

   Sources dounia.org (opens in a new tab)

10. R7.10

    G20/multilateral AI engagement

    Score 0 / 4

    Guinea is not an active member, working group contributor, or formal state partner in G20 or BRICS digital economy tracks dedicated to AI architectures.

    Note: Scored as "None". Multilateral technical engagement remains primarily channeled through the African Union and standard United Nations bodies.

    Sources oacps-ri.eu (opens in a new tab)

Mean of all 10 indicator scores. West Africa mean 0.63 · all 54 states mean 0.78.

1. M8.1

   AI governance budget disbursed

   Score 0 / 4

   No publicly reported AI governance budget disbursed.

   Note: No dedicated AI governance budget identified in Guinea.

   Scoring basis Threshold applied. Raw value: 0 (USD). Raw value read from the evidence: "No dedicated AI governance budget identified in Guinea." Checked against the evidence on 7 October 2026: confirmed.

2. M8.2

   Health AI regulation

   Score 0 / 4

   No specific Health AI regulation identified in Guinea.

   Note: Guinea has an AI Roadmap (2026–2035), but no dedicated regulation governing AI use in healthcare.

   Sources ecofinagency.com (opens in a new tab)

3. M8.3

   Health AI devices approved

   Score 0 / 4

   No publicly available record of AI-enabled health/medical devices approved by a national regulatory authority in Guinea.

   Note: No evidence of a national approval framework or approved registry for AI health devices in Guinea.

   Scoring basis Threshold applied. Raw value: 0 (authorised devices). Raw value read from the evidence: "No publicly available record of AI-enabled health/medical devices approved by a national regulatory authority in Guinea." Checked against the evidence on 7 October 2026: confirmed.

4. M8.4

   Government AI system registry

   Score 0 / 4

   No government AI system registry identified in Guinea.

   Note: Guinea has adopted an AI Roadmap (2026–2035), but no public registry of government AI systems has been established.

   Sources ecofinagency.com (opens in a new tab)

5. M8.5

   AI governance M&E reports

   Score 0 / 4

   No published monitoring and evaluation (M&E) reports on AI governance implementation identified in Guinea.

   Note: AI governance framework is still emerging; no structured M&E reporting system exists yet.

   Scoring basis Threshold applied. Raw value: 0 (reports). Raw value read from the evidence: "No published monitoring and evaluation (M&E) reports on AI governance implementation identified in Guinea." Checked against the evidence on 7 October 2026: confirmed.

6. M8.6

   Agriculture AI governance

   Score 0 / 4

   No sector-specific AI governance provisions identified for agriculture in Guinea.

   Note: AI initiatives exist at national digital transformation level, but agriculture-specific AI governance framework is not yet developed.

   Sources ecofinagency.com (opens in a new tab)

7. M8.7

   Financial services AI governance

   Score 0 / 4

   No AI-specific governance provisions for financial services identified in Guinea’s financial regulatory framework.

   Note: Financial sector regulation exists generally (central bank oversight), but no AI-specific guidance or enforcement measures are in place.

   Sources ecofinagency.com (opens in a new tab)

8. M8.8

   Education AI governance

   Score 0 / 4

   No AI-specific governance provisions identified in the education sector in Guinea.

   Note: Education sector policies do not yet include AI governance measures; AI integration remains at early planning stage

   Sources ecofinagency.com (opens in a new tab)

9. M8.9

   Measurable governance outcomes

   Score 0 / 4

   No documented measurable outcomes of AI governance implementation identified in Guinea.

   Note: AI governance structures are still at planning stage; no implemented systems generating measurable outcomes yet.

   Sources ecofinagency.com (opens in a new tab)

10. M8.10

    WHO AI health guidance adoption

    Score 0 / 4

    No formal national adoption of WHO guidance on Ethics and Governance of AI for Health identified in Guinea.

    Note: Guinea has not formally adopted WHO AI health governance framework; national AI policy remains at roadmap level.

    Sources who.int (opens in a new tab)