A technology company headquartered in Almaty deploys a generative AI platform to produce marketing copy, product illustrations, and software modules. The output streams into commercial use within days. Then a competitor reproduces those materials verbatim – and the company's legal team discovers that no one has a clear answer to the most basic question: who, if anyone, owns what the machine created? In Kazakhstan, that question sits at the intersection of intellectual property legislation written for human authors. A civil law tradition ill-equipped for non-human creativity. Additionally, an emerging digital economy agenda that has yet to crystallise into binding statute.
AI-generated works in Kazakhstan are not expressly addressed by current intellectual property legislation, which conditions copyright protection on human authorship. Ownership of machine-produced output must therefore be structured through developer agreements, employment contracts, or commissioning arrangements that designate a human or legal entity as the rights-holder. No standalone AI-specific intellectual property statute is in force as of April 2026, leaving businesses to rely on general copyright, civil, and technology licensing rules while regulatory reform remains in progress.
This analysis examines the doctrinal foundations, the gap between statute and practice, competing interpretations emerging in Kazakhstani courts. Cross-border implications for CIS-region clients. Additionally, the strategic steps that international businesses can take now. before legislation catches up with commercial reality.
Doctrinal foundations: what Kazakhstan's intellectual property legislation actually says
Kazakhstan's intellectual property regime rests on a body of law that spans copyright, patent, and related-rights legislation, all anchored in the civil legislation framework. That regime reflects the Soviet-era civil law inheritance shared across most CIS states: authorship is a personal, inalienable attribute of a natural person. A work qualifies for protection when it is the result of creative intellectual activity by a human being.
This foundational requirement creates an immediate structural problem for AI-generated output. An AI system is not a natural person. It cannot be an author. The creative act, in the doctrinal sense Kazakhstan law employs, must originate in a human mind. Where no human author exists in any meaningful sense – because the machine generated the output autonomously from a prompt – the work may fall outside the protection perimeter entirely.
The concept of a sluzhebnoe proizvedenie (work for hire or service work in CIS intellectual property tradition) offers a partial bridge. Under this doctrine, works created by an employee in the course of employment belong to the employer. Practitioners in Kazakhstan increasingly argue that this mechanism can capture AI-generated output: a developer's employees design, train, and instruct the model, so the resulting output is a service work attributable to the employer-developer. The argument is plausible but has not been tested in published court decisions.
Patent legislation presents a parallel challenge. Inventorship under Kazakhstan patent rules also requires a natural person. An AI system that independently identifies a novel technical solution cannot be named as inventor. The human who directed the AI, validated its output, and filed the application is the candidate inventor – but the degree of human intellectual contribution required to sustain a valid inventorship claim is unresolved. The Kazakhstani patent authority has not issued formal guidance on the threshold of human involvement sufficient to satisfy the inventorship requirement.
Technology licensing arrangements add a further layer. When a foreign company licenses an AI platform into Kazakhstan and the licensed system generates protectable output locally. The question of which legal system's authorship rules govern. the licensor's jurisdiction or Kazakhstan's. is answered by private international law principles in the civil legislation. Choice-of-law clauses in technology licensing agreements therefore carry unusually high stakes in this context.
The gap between statute and practice: where courts and authorities currently stand
Kazakhstan's courts have not yet produced a settled body of case law on AI-generated works. The absence of reported decisions does not mean the question is dormant. it means disputes are being resolved informally. Through commercial negotiation. Alternatively, are simply not being litigated because the economic stakes of an individual case have not yet justified the cost. That will change as AI deployment scales.
What the courts have done is apply existing copyright doctrines in analogous digital-content disputes. In cases involving software authorship and computer-assisted design, courts in Kazakhstan have consistently emphasised the creative contribution of the human programmer or designer as the basis for protection. This line of reasoning is instructive: it suggests that courts will ask, when confronted with an AI-generated work, how much intellectual shaping a human contributed to the final output.
This produces a spectrum rather than a binary rule. At one end, a human artist who uses AI as a tool – selecting parameters, curating outputs, combining elements – retains a strong authorship argument. At the other end, a script that runs an AI model overnight and publishes whatever it produces provides almost no human creative contribution. The overwhelming majority of commercial AI deployments fall somewhere in the middle, and that middle ground is legally uncertain.
Algorithmic accountability adds a related dimension. Kazakhstan's digital services legislation imposes obligations on operators of automated decision-making systems in certain sectors. Where an AI system produces output that causes harm – a defamatory text, an infringing image – questions of software liability arise under the general tort provisions of civil legislation. The operator or deployer, not the AI, bears exposure. Practitioners advising on AI deployment in Kazakhstan note that the software liability question is often more immediately pressing than the authorship question, because it triggers insurance, indemnification, and contractual risk-allocation decisions from day one.
The Komitet po pravam intellektual'noy sobstvennosti (Committee on Intellectual Property Rights of Kazakhstan, the primary IP administrative authority) has not published dedicated guidelines on AI-generated works. It continues to process applications under existing examination criteria. In the absence of official guidance, a significant share of AI-related filings are receiving standard treatment – meaning examiners are applying human-authorship requirements without any AI-specific adaptation. Applications that disclose AI involvement risk rejection or administrative challenge if the human creative contribution is not clearly articulated.
For international clients operating in Kazakhstan, this gap between statute and practice represents a lost opportunity if left unmanaged. A company that secures ownership of its AI-generated IP portfolio through well-drafted contracts and well-structured filings today will hold enforceable rights when the legal position clarifies. A company that waits may find that its output has entered the public domain or been claimed by a competitor who acted faster.
To explore how AI-generated intellectual property rights can be secured and enforced in Kazakhstan, contact us at info@ferrazwhitmore.com.
Competing interpretations: authorship, originality, and the human-contribution threshold
Three competing interpretive approaches have emerged among Kazakhstani legal practitioners and academic commentators. Understanding them is essential for structuring IP protection strategies.
The first approach is strict constructionism: if the statute requires a human author, AI-generated output without meaningful human creative input simply does not qualify for copyright protection. The work enters the public domain on creation. Proponents argue this position is consistent with the text of the legislation and avoids judicial overreach. The practical consequence is that any business relying on AI-generated content as a competitive asset must look to contractual secrecy, trade secret law, or technical protection measures rather than copyright.
The second approach is instrumental attribution: the human who operates, configures, or deploys the AI is treated as the de facto author by analogy to the relationship between a photographer and a camera. The AI is merely a sophisticated tool. This reasoning has support in the civil law tradition – Kazakhstan's copyright legislation protects derivative works and compilations produced by human editors even when the underlying material is not original. A skilled prompt engineer who shapes, selects, and refines AI output can arguably be positioned within this tradition.
The third approach is legislative gap-filling: courts or the IP authority should recognise a sui generis protection category for AI-generated works by analogy to the protection afforded to databases and computer programs under existing legislation. Neither databases nor software is a traditional "creative" work in the doctrinal sense, yet both receive protection. Advocates argue that extending analogous protection to AI output is the least disruptive path to a workable regime. This approach has gained traction in academic circles but has not been adopted in any published administrative or court decision in Kazakhstan.
The practical consequence of this three-way division is that no single strategy is risk-free. Businesses cannot rely on the courts to adopt any particular approach in a future dispute. The prudent response is to layer protections: structure ownership through contracts (capturing the instrumental attribution argument). Deposit works with the IP authority (preserving evidentiary priority). Additionally, maintain trade secret controls (providing fallback protection if copyright fails).
For AI-assisted software specifically, Kazakhstan's digital services and technology legislation provides a partial overlay. Software is protected as a literary work under copyright law, and software developed with AI assistance is generally registered without difficulty provided a human author is identified. The challenge arises when the software itself is almost entirely AI-generated. In that scenario, practitioners in Kazakhstan recommend documenting the human decision-making steps – architecture choices, training data curation, output validation – as contemporaneous evidence of authorship contribution.
Our detailed overview of intellectual property rights and registration procedures in Kazakhstan provides further context on the general protection mechanisms available under current legislation.
Cross-border implications for CIS clients and international businesses
Kazakhstan operates within a web of international intellectual property obligations. It is a member of the Berne Convention framework, which means copyright protection is mutual across member states. This has a direct consequence for cross-border AI deployments: a work that qualifies for copyright protection in the country of origin receives equivalent protection in Kazakhstan. Conversely, if the work does not qualify in Kazakhstan – because no human authorship can be established – Berne Convention minimum standards do not override the domestic requirement.
The Evraziyskiy patentnyy ofis (Eurasian Patent Office, known as EAPO), of which Kazakhstan is a member state, processes regional patent applications covering multiple CIS jurisdictions in a single procedure. AI-assisted inventions filed through the EAPO face the same inventorship challenge as domestic filings: a natural person must be identified. The EAPO examination practice has not yet produced published guidance on how much human intellectual contribution satisfies the inventorship requirement, but the trend across member states is toward a high threshold. CIS clients considering regional patent protection for AI-assisted innovations should expect scrutiny and should document human inventive contribution carefully.
For businesses operating between Kazakhstan and the European Union, the divergence between Kazakhstan's current position and the EU's evolving AI Act compliance regime creates planning complexity. The EU AI Act imposes obligations on providers and deployers of high-risk AI systems that extend to transparency, algorithmic accountability, and human oversight requirements. A company operating in both markets must satisfy EU-level obligations for its AI systems while managing Kazakhstani IP ownership questions through a separate legal analysis. These two regulatory tracks do not currently intersect in any binding international instrument. However. They do interact commercially: a product that discloses its AI origins for EU compliance purposes may simultaneously weaken a copyright ownership argument in Kazakhstan by demonstrating the absence of human authorship.
Technology licensing agreements crossing the Kazakhstan–EU border therefore require careful drafting. IP ownership provisions, representations about the origin of licensed materials, and indemnification clauses for IP infringement should all address the AI-generation dimension explicitly. A licensor that warrants clear title to AI-generated content without addressing the authorship question under both applicable laws exposes the licensee to an unquantified risk.
The Russia–Kazakhstan comparison is also instructive for CIS practitioners. Russia's intellectual property legislation confronts identical structural challenges. Courts there have addressed analogous questions with slightly more published guidance – leaning toward instrumental attribution in cases involving AI-assisted creative tools. Kazakh practitioners are watching Russian judicial developments closely, though the two systems are formally independent and Russian court positions carry no binding weight in Kazakhstan.
For a comparative perspective on how these questions are being handled in the Russian legal system, our analysis of AI-generated works and intellectual property in Russia examines the emerging doctrinal positions in that jurisdiction.
For CIS-based businesses, the cross-border dimension underscores a structural opportunity. Companies that build IP portfolios through properly structured ownership chains. clear contracts, documented human contribution, voluntary deposit. Additionally. Trade secret protocols. will be positioned to enforce rights across the CIS region as both domestic legislation and regional practice evolve. Those that defer structuring decisions will face a more crowded and contested landscape.
To discuss how cross-border AI intellectual property strategy applies to your operations in Kazakhstan and the broader CIS region, reach out to info@ferrazwhitmore.com.
Strategic recommendations and the regulatory outlook
Kazakhstan's government has identified artificial intelligence as a priority within its digital economy agenda. Policy documents reference AI-driven productivity goals and position Kazakhstan as a regional technology hub. This agenda creates a political impetus for regulatory reform that did not exist five years ago. Businesses should expect legislative movement – but not immediately, and not in a predictable direction.
The most likely near-term development is administrative guidance from the IP authority on how existing authorship and inventorship requirements apply to AI-assisted works. Such guidance, even if non-binding, would provide a practical standard for filings and dispute resolution. A more ambitious reform – a standalone AI legislation framework or amendments to copyright and patent legislation – would require parliamentary action and is unlikely before 2027 at the earliest.
In the interim, the following strategic steps represent best practice for international businesses deploying AI in Kazakhstan.
Contract-first ownership structuring. Every agreement touching AI-generated output – developer agreements, employment contracts, commissioning arrangements, technology licensing terms – should specify who owns the output and on what basis. The instrumental attribution argument is strongest when a human being made documented creative or inventive choices. Contracts should record those choices and assign resulting rights explicitly.
Voluntary IP deposit. Kazakhstan's IP authority accepts voluntary deposit of copyright works. Deposit does not create rights, but it creates a dated evidentiary record. For AI-generated works where authorship may be challenged, deposit by the designated human rights-holder provides a defensible priority position. The cost is modest; the evidentiary value in a future dispute can be significant.
Trade secret protocols. Where copyright protection is uncertain, trade secret law provides an independent protection layer. Kazakhstan's civil and commercial legislation recognises confidential commercial information as protectable. Internal AI models, training datasets, and proprietary output pipelines can be protected as trade secrets provided access controls, confidentiality agreements, and security measures are in place. This protection does not depend on authorship and is not affected by the human-creativity requirement.
Algorithmic accountability documentation. For AI systems deployed in digital services or automated decision-making contexts, maintaining records of how the system was designed, trained, and monitored serves both software liability management and IP ownership purposes. The same documentation that demonstrates human oversight for regulatory compliance also demonstrates human creative or inventive contribution for IP purposes.
Technology licensing review. Inbound technology licensing agreements should be reviewed for AI-origin representations. An agreement that warrants clear title to licensed materials without addressing AI generation creates exposure. Outbound licenses should include representations about ownership structure and indemnities calibrated to the residual authorship risk.
The regulatory outlook beyond these immediate steps involves watching three developments. First, any administrative guidance from the Kazakhstani IP authority on AI filings. Second, the first published court decisions addressing AI-generated works – when they emerge, they will set a de facto standard even in the absence of binding precedent in Kazakhstan's civil law system. Third, progress on a potential AI-specific legislation initiative at the level of the Eurasian Economic Union, which could produce harmonised rules across member states including Kazakhstan.
Businesses that engage a lawyer in Kazakhstan with cross-border AI and technology experience now – before these developments occur – will be better positioned to shape their IP portfolio around whatever rules emerge. Reactive restructuring after a legislative change or an adverse court decision is consistently more expensive and less effective than proactive portfolio design.
Our broader AI and technology law practice for Kazakhstan clients is described in detail at AI and technology law services in Kazakhstan, covering regulatory compliance, software liability, and IP strategy.
Frequently asked questions
Q: Can an AI system be named as the author of a work under Kazakhstan intellectual property legislation?
A: No. Kazakhstan's intellectual property legislation, like the civil law systems of most CIS states, restricts authorship to natural persons. An AI system cannot hold rights. Ownership of AI-generated output must be attributed to a human or legal entity through a contractual or statutory mechanism – typically the developer, employer, or commissioning party.
Q: How long does it take to register an IP right over AI-assisted software or creative output in Kazakhstan?
A: Copyright in Kazakhstan arises automatically on creation and does not require registration. However, voluntary deposit with the state IP authority – which provides an official timestamp useful in disputes – typically takes several weeks to a few months. Patent or design registration for AI-assisted technical output follows standard examination procedures and can take one to three years.
Q: Does Kazakhstan currently have AI-specific intellectual property legislation comparable to the EU AI Act?
A: Not yet. Kazakhstan has not enacted standalone AI-specific intellectual property legislation. Existing rules draw on general copyright, patent, and civil legislation. Regulators have signalled interest in AI Act compliance-style obligations through digital economy policy documents, but no binding statute equivalent to the EU regime is in force as of the date of this analysis. Businesses should monitor legislative developments closely.
About Ferraz & Whitmore
Ferraz & Whitmore is an international law firm based in Lisbon, advising business clients across 46 jurisdictions. Our team combines Portuguese civil law expertise with English common law tradition to deliver cross-border legal solutions in AI and technology law, intellectual property strategy, and digital services regulation. We advise technology companies, investors, and in-house legal teams navigating AI-generated works questions in Kazakhstan and across the CIS region. Our AI and technology law practice spans both civil law systems – including the Kazakhstani legislative environment – and common law jurisdictions, with particular depth in cross-border technology licensing, software liability, and algorithmic accountability matters. The firm's Lisbon base provides direct access to EU regulatory developments, while our CIS practice supports clients managing the gap between emerging AI legislation and existing IP regimes. As a law firm in Kazakhstan advising international clients, Ferraz & Whitmore builds IP ownership structures designed to remain defensible as the regulatory position evolves. To discuss your AI intellectual property strategy in Kazakhstan, contact us at info@ferrazwhitmore.com.
Disclaimer: This publication is provided for informational purposes only and does not constitute legal advice. The information herein should not be relied upon as a substitute for professional legal counsel tailored to your specific circumstances. Ferraz & Whitmore assumes no liability for actions taken or not taken based on the contents of this material. For advice regarding your particular situation, please contact info@ferrazwhitmore.com.