Nicaragua has no law, strategy or policy addressed to artificial intelligence of any kind. For a jurisdiction with no domestic AI governance at all, the confirmed founding seat is the profile's centre of gravity.
The shape is one of the sparsest in the field: nothing in the soft or draft tiers touches artificial intelligence, and the binding tier is general law an AI dispute would meet. The entire AI-specific weight of the profile sits in the regional band, where Nicaragua holds a confirmed founding seat in the new AI cooperation organization.
Nicaragua's data-protection statute, covering automated and non-automated processing, so AI processing of personal data is nominally in scope. It carries no automated-decision or profiling right. It creates a supervisory authority under the Ministry of Finance and Public Credit, but that authority was never established, so the law cannot be applied in practice. The statute most likely to govern an AI or data harm, and the one least enforced.
Source: La GacetaThe computer-crime law. Its article 30 criminalizes spreading false or distorted information causing alarm, the provision widely used to control online speech. Technology-general, with no AI or deepfake-specific wording; AI-enabled conduct would be charged under its general fraud and false-information offences.
Source: La GacetaThe telecommunications framework and the Nicaraguan Institute of Telecommunications and Posts (TELCOR), the sector regulator and the body that signed the WAICO agreement for Nicaragua.
Source: La Gaceta; TELCORThe constitutional basis for privacy and the right to know what data authorities hold, with a habeas-data remedy before the constitutional chamber of the Supreme Court.
Source: La GacetaThe authorship framework. Its article 2 defines the author as the natural person who creates a work, and it carries no computer-generated-works provision. Its limitations are a closed enumerated list governed by a three-step test. No AI-authorship rule.
Source: WIPO LexThe patent, utility-model and industrial-design framework. Its article 14 vests the right to the patent in the inventor, treated as a natural person, distinguished from an applicant who may be a natural or legal person. No AI-inventorship provision or practice.
Source: WIPO LexConfirmed founding member; signed in Shanghai 16 Jul 2026 by the Director General of TELCOR, Nahima Diaz, for the Government of Nicaragua; Nicaragua among the twenty-nine founding states. Official source: Nicaraguan state media (Canal 6, Barricada); Prensa Latina.
Adopted 2021, as a UNESCO member; no readiness assessment produced. Official source: unesco.org.
Adopted by consensus 22 Sep 2024; applies to Nicaragua as a UN member; Nicaragua backed a dissenting amendment set aside before adoption. Official source: A/RES/79/1 annex, un.org.
Adopted by consensus in 2024, the second a China-led capacity-building resolution; Nicaragua bound as a UN member; no co-sponsorship confirmed. 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 stark: every instrument sits at the low-specificity end, because no instrument in Nicaragua is written for AI at all.
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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 court case where artificial intelligence is materially at issue was found in Nicaragua, and no dedicated deepfake offence with a citable article exists. Nicaragua has no accessible public court-judgment database and a politically controlled judiciary, so a non-public matter cannot be ruled out, but nothing is reported. One matter is recorded below as a reported incident, not an adjudicated case, and per the fabrication screen no case number is invented.
Portals and sweeps: WIPO Lex and the RPI pages; the National Assembly legislation database; Nicaraguan media of record. Nicaragua provides essentially no public court-judgment access, so the absence of case law is not proof that no matter exists.
Nicaragua has no AI policy of any kind behind its rights law: the author and the inventor are natural persons, the copyright limitations are a closed list under a three-step test, and no office has issued AI guidance.
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 patent law vests the right to the patent in the inventor, treated 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, guidance or grant evidence specific to AI-assisted inventions exists, and no DABUS-type filing has tested Nicaragua.
What we look forProtection applied where human choices shape the work, and refusal of purely machine output.
The findingThe copyright law defines the author as the natural person who creates a work, so a human who directs an AI tool and contributes authorship can hold copyright, while purely AI-generated output has no qualifying author and no route to protection. There is no computer-generated-works provision and no ruling tests the point, so it is untested.
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 copyright limitations are a closed enumerated list governed by a three-step test, with no open fair-use clause and no mining carve-out. With copyright silent, 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 findingNicaragua is a WIPO member, but the WIPO Conversation submissions record shows no traceable submission from Nicaragua or the RPI, and no substantive session participation was found. Membership without a submission earns the middle.
What we look forA standalone AI examination text, not AI handled quietly under general practice.
The findingNo dedicated guidance from the RPI on examining AI-related filings was found; its published guidance is the ordinary filing and examination rules. 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. There is no AI policy of any kind to carry such a duty.
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.
Nicaragua has no law, strategy or policy addressed to artificial intelligence of any kind. There is no AI statute, no national AI strategy, and not even a soft-law ethics instrument, which sets it apart from most jurisdictions that have at least a plan on paper. What governs the field is general law: a 2012 data-protection statute whose supervisory authority was never created, so it operates barely at all; a 2020 cybercrime law whose false-information offence is used to control online speech; and intellectual-property statutes that confine authorship and inventorship to human makers. The single materially new development is external and confirmed: Nicaragua is a founding member of the World Artificial Intelligence Cooperation Organization, its accession signed in Shanghai by the head of the state telecommunications regulator. That the same regulator was identified as the operator of a 2021 state social-media influence network is the country's sharpest piece of connective tissue. For a jurisdiction with no domestic AI governance at all, the confirmed founding seat is the profile's centre of gravity.
The site does three things: it maps every instrument that governs AI in Nicaragua, 10 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. Nicaragua's standout credential is a founding seat in the AI cooperation organization that is confirmed in its own official record, named signatory and all.
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