Kenya is a developed digital jurisdiction with a binding data-protection regime, an actively enforcing regulator, and an AI bill now before the Senate, but no in-force AI law yet. For a jurisdiction whose AI-specific rules are still a strategy and a bill, the enforced data regime and the international footprint are the profile's centre of gravity.
The shape is a developed jurisdiction whose general AI law is still a bill: an AI strategy and a voluntary standard sit in the soft tier, an AI bill in the draft tier, and the binding tier is enforced general law an AI dispute would meet.
Kenya's data-protection statute and the general law most likely to reach an AI harm, actively enforced with published penalties. Its section 35 gives a right not to be subject to a decision based solely on automated processing, including profiling, with a notification duty, subject to carve-outs. The word artificial intelligence does not appear in the act; it is a data-protection right, not an AI-specific duty.
Source: kenyalaw.orgThe computer-crime law, including false-publication offences that have been the subject of constitutional challenge. Technology-general, with no AI or deepfake-specific provision.
Source: kenyalaw.orgThe telecommunications and broadcasting framework and the sector regulator, the general regime a networked AI service operates within.
Source: kenyalaw.orgThe authorship framework, and unusually accommodating. Following the British model, its interpretation section provides that for a computer-generated work the author is the person by whom the arrangements necessary for the creation of the work were undertaken. So machine-generated output has a route to protection, though the route is untested for generative AI and the copyright board's commentary has leaned toward requiring human authorship. Its permitted acts are a closed schedule with no text-and-data-mining exception.
Source: kenyalaw.orgThe patent framework. The inventor is treated as a natural person, and there is no AI-inventorship provision or AI examination guidance. Kenya is an ARIPO member, so patents can also run through the regional route.
Source: kenyalaw.orgThe flagship AI-specific instrument, built on AI infrastructure, data and AI governance, and research and commercialization. It sets direction and creates no operator duties.
Source: the ministryA technical and organizational standard for AI applications. Voluntary guidance unless incorporated by law, so it binds no operator on its own.
Source: KEBSThe dedicated AI bill. It would create an Office of the Artificial Intelligence Commissioner, classify AI systems by risk, and require consent and labeling for AI-generated content that uses a person's image, voice or likeness, with deepfake offences. Not in force, and at a first-reading stage.
Source: parliament.go.keA draft copyright reform that would expand the fair-dealing purposes, adding parody, caricature, pastiche and satire. A draft, not in force, and it carries no text-and-data-mining exception.
Source: copyright.go.keFounding member; signed in Shanghai 16 Jul 2026, reported signed by the Cabinet Secretary for information, communications and the digital economy; Kenya among the twenty-nine founding states. Official source: Chinese release and Kenyan reporting.
Signatory, 1 to 2 Nov 2023. Official source: gov.uk, the Bletchley signatory list.
Signatory, 11 Feb 2025. Official source: elysee.fr, the statement signatory list.
Adopted by the AU Executive Council July 2024; Kenya an AU member. Official source: au.int.
Adopted 2021, as a UNESCO member; readiness assessment completed. Official source: unesco.org.
Adopted by consensus 22 Sep 2024; applies to Kenya as a UN member. Official source: A/RES/79/1 annex, un.org.
Adopted by consensus in 2024; Kenya a co-sponsor of resolution 78/265. Official source: UN records.
Axes: specificity (x, 0-100) is how squarely the instrument is written for AI; force (y, 0-100) is how hard it binds. Placements are editorial judgments for the comparison plot; the tier column is the authoritative classification. The pattern is a developed jurisdiction whose AI-specific instruments are a strategy, a voluntary standard and a bill low on force, above an enforced binding tier of general law.
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The binding and prescriptive corner is the crowded one: the CAC-led measures put force and detail together, service by service. The sector guidance sits just left of the binding line, nonbinding in form but treated as obligatory. Dashed markers are drafts; the National AI Law would consolidate the whole stack into one statute.
No adjudicated Kenyan court case that turns on artificial intelligence was found. Kenya publishes its judgments, and several matters are often cited as AI cases, but on a close reading they are decided on data-protection, privacy and labour grounds, with AI incidental. Two are recorded below to make that distinction plain, and the negative findings that follow are stated affirmatively. Per the fabrication screen, a citation is given only where it is published and verified.
Portals and sweeps: the national case-law database; WIPO Lex and the copyright board and industrial-property institute pages; Kenyan legal media of record. Kenya publishes judgments, so the negative findings are reasonably firm.
Kenya, following the British model, protects computer-generated works through the person who arranged their creation, but the route is untested for generative AI; the patent law holds the human line and no training exception exists.
The AI-IP Index reads a country on two questions that usually get folded together. Accommodation asks how far the law will go to protect intellectual property that a machine helped produce. Institution asks how much administrative machinery sits behind that law: its guidance, its international submissions, its disclosure duties.
A country can be generous on paper and have built almost nothing, or cautious and highly organised, so the two are scored apart and reported as a pair. Each rests on three questions, scored 0, 0.5 or 1.
How far the law will protect intellectual property that a machine helped make.
How much administrative machinery sits behind that law.
The scale runs the same way on both axes: 0 is the open or developed end, 1 is the restrictive or absent one, and 0.5 sits between for anything conditional or untested. Read as a pair, the two scores show whether AI-assisted work can be protected here, and whether the office has said so in writing.
Within each axis the three questions carry equal weight. That is a deliberate choice, not an oversight. An AI developer might reasonably value freedom to train above patent inventorship, but weighting is where indices lose their credibility, so the score stays a flat mean and the choice is stated in the open. Each cell also cites a statute section, a case or an office page, so any single score can be challenged without disputing the rest.
Two positions are worth naming. A country can be open on the law but thin on machinery, an open-but-undeveloped stance that bets on ambiguity. Or it can be restrictive on rights yet run an active office, a restrictive-but-developed stance that reflects a settled policy choice rather than a gap. The pair of scores tells those two apart where a single ranking would blur them.
A rubric is only as good as the results it produces on cases where the answer is already known. These three jurisdictions sit outside this series and are scored with the same six questions, as a check. Their law is the best documented anywhere, so if the scale puts them where the law actually sits, the scale is doing its job. They are reference points, not editions.
Firm judicial settlement at both poles and the weakest statutory position on training. The courts have closed the door on AI inventors and AI authors, while everything on training rides on unresolved fair-use litigation. There is no per se duty to declare AI use in a filing, only a candour duty that bites where the use is material.
Thaler v. Vidal, 43 F.4th 1207 (Fed. Cir. 2022); Thaler v. Perlmutter (D.C. Cir. 2025), cert. denied 2 Mar 2026; Bartz v. Anthropic (N.D. Cal. 2025); USPTO revised inventorship guidance, 90 Fed. Reg. 54636 (28 Nov 2025); 89 Fed. Reg. 58128 (17 Jul 2024); 89 Fed. Reg. 25609 (11 Apr 2024).
The most permissive statutory position on training and the strongest transparency duty in force, sitting over an authorship question no court has answered. Read the label carefully: training and transparency run through EU law, but patents run through the EPO under the European Patent Convention, which is not an EU institution and covers 39 states.
Directive (EU) 2019/790, arts. 3 and 4; Regulation (EU) 2024/1689, art. 53(1)(c) and (d); EPO J 8/20 (2021); EPO Guidelines G-II 3.3.1 (2026 edition); Infopaq C-5/08; Painer C-145/10.
Liberal on patents since the Supreme Court abandoned the Aerotel test in February 2026, conservative on copyright, and currently thin on AI-specific machinery after the dedicated AI examination guidance was withdrawn. Section 9(3) nominally protects a work with no human author for 50 years, the widest AI-output right on paper, but no court has ever applied it to generative AI.
CDPA 1988 ss. 9(3), 12(7), 29A, 178; Thaler v Comptroller-General [2023] UKSC 49; Comptroller-General v Emotional Perception AI [2026] UKSC 3; UKIPO practice notice, 14 Jul 2026; Data (Use and Access) Act 2025 ss. 135 to 137.
The check earned its keep twice. The untested rule held: section 9(3) of the UK Copyright Act reads like the widest AI-output right anywhere, yet because no court has applied it to generative AI it scores as untested rather than open, which is the correct answer and the one a headline reading would miss. The check also exposed a limit worth stating. The Institution axis measures AI-specific machinery, not general office capacity, so a long-established office can score poorly when it has withdrawn its AI guidance and imposes no disclosure duty. Read that axis as what an office has built for AI, nothing wider.
Each row below carries the test we applied and the finding behind the score, with a source. The rationale, not the number, is the point.
Scores verified 21 July 2026, against AIP Index codebook v1.0. A score is only true as of its date.
What we look forA granted patent or a clearly workable examination route, not merely a silent statute.
The findingThe industrial-property act treats the inventor as a natural person, so an AI-assisted invention with a human inventor is open in principle while the machine cannot be named. No examination practice or guidance addresses AI-assisted inventions, and no DABUS-type filing has tested Kenya; patents may also run through the regional ARIPO route.
What we look forProtection applied where human choices shape the work, and refusal of purely machine output.
The findingThe copyright act, following the British model, provides that for a computer-generated work the author is the person by whom the arrangements necessary for the creation of the work were undertaken, so machine-generated output has a route to protection, unlike in the human-author-only jurisdictions. The route is untested for generative AI and the copyright board's commentary has leaned toward human authorship, so it earns the middle rather than the open pole.
What we look forA statutory or judicial mining lane. Silence scores against the miner, since the reserved-rights default governs.
The findingThere is no training or text-and-data-mining exception. The fair-dealing permitted acts are a closed schedule, and the draft copyright bill would expand the purposes but adds no mining exception and is not in force. With copyright silent on mining, the reserved-rights default governs the use of works for training.
What we look forA traceable, substantive submission on the record, not bare membership.
The findingKenya is a WIPO member and an ARIPO member and is broadly active, but no traceable substantive submission from Kenya or its offices to the WIPO Conversation on frontier technologies was found. Membership and general activity without a submission earn the middle.
What we look forA standalone AI examination text, not AI handled quietly under general practice.
The findingNo dedicated guidance from the industrial-property institute on examining AI-related filings was found; the copyright board's commentary on human authorship is non-binding and not examination guidance. A reasonable-search negative.
What we look forA mandatory declaration inside the filing, not a proposal or an informal request.
The findingNo filing requires declaring AI use, and no in-force instrument imposes a labeling or transparency duty on AI-generated content. The data act's automated-decision right is not a disclosure duty, and the labeling duty that would reach content sits in the draft AI bill.
Method. Six questions, three per axis, scored 0, 0.5 or 1 against AIP Index codebook v1.0. The three questions in each axis are weighted equally by choice, and the two axes are reported as a pair, never blended into one number. Every score cites a statute, case or office page, carries a verified date, and records its direction of travel apart from the level. Positions are editorial judgements read from primary law and office practice, not official scores. WIPO's public catalogue of IP-office AI initiatives does not score jurisdictions on this basis, so the readings here come straight from the source law. Not legal advice.
Kenya is a developed digital jurisdiction with a binding data-protection regime, an actively enforcing regulator, and an AI bill now before the Senate, but no in-force AI law yet. AI governance is soft for now: a National AI Strategy for 2025 to 2030 and a voluntary Kenyan standard on AI applications set direction, while a draft Artificial Intelligence Bill, read a first time in April 2026, would create an AI commissioner and mandate the labeling of synthetic media. What binds is the Data Protection Act of 2019, which the data commissioner enforces with real penalties and which carries an automated-decision right, together with the cybercrime law and the intellectual-property statutes. On the IP side Kenya is unusual: its copyright act follows the British model and protects computer-generated works, assigning authorship to the person who arranged their creation, though that route is untested for generative AI. Kenya is broadly engaged abroad, a Bletchley and Paris signatory and a founding member of the World Artificial Intelligence Cooperation Organization. For a jurisdiction whose AI-specific rules are still a strategy and a bill, the enforced data regime and the international footprint are the profile's centre of gravity.
The site does three things: it maps every instrument that governs AI in Kenya, 16 of them, ordered by how hard each one binds; it reads the same instruments a second time by how squarely each is written for AI; and it records the matters where AI meets the law, with what was searched and found empty stated as plainly as what was found. Every claim traces to a primary source, and absences are recorded rather than papered over.
A membership claim enters this table only from an official list: a declaration annex, a treaty signature table, an organization's own record or an official government statement. Kenya is one of the more internationally engaged jurisdictions in the band, a Bletchley and Paris signatory and a confirmed WAICO founder.
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