As of 27 August 2026, the official Korean title of the so-called Hanwoo Act is the Act on the Transition and Support of the Hanwoo Industry in Response to Carbon Neutrality (탄소중립에 따른 한우산업 전환 및 지원에 관한 법률). Promulgated as Act No. 21003 on 22 July 2025, it took effect on 23 July 2026. Its Enforcement Decree and Enforcement Rule took effect on 21 August 2026. The Act is therefore no longer a future blueprint; it is a current legal framework with subordinate legislation in force.
Saying that this law ‘opens’ the era of AI Carbon Intelligence Platforms does not mean that it orders the adoption of any platform. The statute contains no guarantee of private software procurement, carbon-data ownership, data-sale revenue or carbon-credit issuance. The more precise claim is that managing carbon neutrality, supply, quality and farm stability together requires more connected and auditable data than before, creating a larger policy role for AI-enabled analytical infrastructure.
Start with the correct legal name and status
The official Korean short title is Hanwoo Industry Act. Titles used in other languages are explanatory translations for readers; the Korean text remains authoritative. National Assembly bill No. 2211249 was the committee alternative proposed by the Chair of the Agriculture, Food, Rural Affairs, Oceans and Fisheries Committee and was dealt with in plenary session on 3 July 2025. The bill-stage text and the promulgated Act should not be cited as if they were the same procedural document.
The Act had been effective since 23 July 2026, while Presidential Decree No. 36597 and Ministry of Agriculture, Food and Rural Affairs Ordinance No. 785 were enacted and brought into force on 21 August. On 20 August, the ministry officially announced implementation of the five-year comprehensive plan, annual implementation plans, the Hanwoo Industry Development Council, supply measures and farm-stability provisions. Materials prepared in late July may therefore be less specific than those issued after 21 August.
The legal force also varies by clause. Some provisions require the state to pursue policies or devise measures; Article 9 says the minister ‘may’ establish and operate the integrated information system; and farms are required to ‘endeavour’ to achieve carbon neutrality and reduce greenhouse gases. None of these formulations should be converted into a universal duty to install sensors or use a named software product.
Hanwoo policy moves from isolated projects to a data-based system
Article 5 requires a comprehensive Hanwoo industry plan every five years. It must cover market conditions and outlook, self-sufficiency and an appropriate herd size, environmental improvement for carbon neutrality and climate response, price stabilization, farm-stability programmes, resource and crop-livestock circulation, and energy recovery from livestock manure. The Decree adds timetables and publication procedures for the comprehensive and annual plans. Environmental and industrial policy are thus placed on the same planning cycle.
Article 7 permits surveys and statistics on production, distribution, processing and consumption to support those plans, including requests for information or opinions from relevant bodies. Article 9 then permits an Integrated Hanwoo Industry Information Management System, based on those survey results and statistics, to provide information on production, raising, distribution and consumption and to manage industry conditions systematically.
Article 6 of the Decree requires the system to include the Article 7 survey results and statistics, as well as other information the minister considers necessary for systematic management and information provision. Operation is entrusted to the Korea Institute for Animal Products Quality Evaluation under the Livestock Industry Act. Yet this provision alone does not settle public access, private APIs, farm-level raw-data collection, commercial reuse or a private platform's right to connect. Detailed governance and protection of personal and commercially sensitive information remain necessary.
National and regional plans need targets, baselines and performance indicators.
Surveys and statistics provide a basis for repeated updates across production, distribution and consumption.
The integrated system can become a public starting point for connecting otherwise fragmented results.
R&D, education and support programmes need evaluation data before and after technology adoption.
The Development Council considers supply, appropriate herd size, environmental technology and resource circulation together.
Carbon Intelligence is needed where carbon, supply, quality and farm economics meet
Article 11 requires the state to pursue policies supporting crop-livestock circulation, greenhouse-gas reduction technology, low-methane feed and the use of agricultural by-products. Farms are to endeavour to improve resource circulation, manure energy recovery and other reductions. The provision establishes policy directions, but it does not prescribe a methane sensor or require data submission to a particular platform.
Article 12 covers long-term supply policy, analysis and forecasts for farmers, a five-year assessment of herd numbers, and management projects considering expected supply, production and operating costs. It also requires plans for differentiated environmental and social responsibility by farm scale. Keeping herd management and greenhouse-gas management in separate spreadsheets can make one policy create costs for another. Animal numbers, shipment age, growth, feed efficiency, prices, costs and emissions-related indicators must be read together.
Article 8 on feeding and quality R&D and commercialization, Article 18 on low-carbon feeding education, and Article 22 on quality and distribution improvements belong to the same data chain. Assessing whether earlier shipment reduces total feeding time and costs, whether low-methane feed affects productivity or health, and whether grade and sales price change requires more than environmental data. Carbon Intelligence is the ability to read climate performance and farm economics together.
Animal and herd data: identity, entry, weight, health, breeding, movement and shipment timing
Input data: feed type, purchases and feeding quantity, forage share, energy and water use
Production and finance data: growth, shipment age, grade, sale price, feed and disease-control costs
Environmental data: measured or estimated enteric methane, manure treatment, energy recovery and barn conditions
Evidence and quality data: source, calibration, missing or amended records, consent and access rights
The practical role of AI is measurement, connection and decision support
An AI Carbon Intelligence Platform should design data lineage and decision processes before designing a spectacular dashboard. It should connect farm sensors, feed purchase and feeding logs, traceability, slaughter and quality records, manure management and programme evidence across time and by animal or farm. Every calculation should be traceable to its source. AI can then flag anomalies and gaps, compare baselines with observed values and explain policy scenarios.
Data quality: detect sensor faults, unit errors, missing periods, duplicate animals and anomalous patterns.
Baselines and scenarios: estimate emissions and cost changes before and after feed, shipment-age or manure-treatment changes.
Policy matching: compare farm conditions with programme requirements and suggest possible support, education or pilot routes.
Evidence packages: bundle raw data, formulas, versions and approval logs for review and follow-up audits.
Interoperability: support standardized exchange between the public integrated system and farm, cooperative and research systems.
A private platform is more credible as a complement to the public system than as its presumed replacement. Public institutions can manage statistics and policy, while field solutions reduce recording burdens, provide operational feedback, manage consent and automate evidence. Real integration depends on published standards, legal authority, institutional agreements and security review.
A measurement does not automatically become an officially recognized reduction. Direct enteric-methane measurements, estimates derived from feed records, national-inventory factors, and certification or subsidy methodologies serve different purposes and carry different uncertainty. Calibration, representativeness, missing-data treatment, baselines, additionality, double-counting safeguards and third-party verification must remain distinct so that AI does not present a plausible number as a settled result.
How carbon data may create value—and what the law does not guarantee
Official policy already offers examples where evidence meets economic support. The Livestock Environmental Management Institute's 2026 Low-Carbon Agriculture Programme links activity payments to verifiable practices such as feeding low-methane feed, improving manure treatment and shipping steers earlier. It also announces an additional incentive for certified low-carbon livestock farms performing selected activities. The ministry's low-carbon livestock certification likewise relies on verified mitigation practices and emissions performance. This shows that evidence can support payments and market confidence, not that every data point can be sold independently.
Lower administrative cost when proving eligibility and implementation for support programmes
Evidence for low-carbon certification and trust in distribution, procurement or branding
Operational savings through feed efficiency, shipment-age and health-management improvements
Data value for R&D, pilots and performance-based programme design
The Hanwoo Industry Act does not grant farms property or revenue-sharing rights in carbon data, promise support for private platform fees, or authorize credits solely from sensor readings. Payments remain subject to annual programme guidelines, budgets, applications, implementation and verification. Certification premiums are not automatic. Connection to voluntary carbon markets or emissions trading would require a separate methodology, registration, additionality, permanence, leakage, double-counting controls and verification.
The implementation agenda for turning policy space into infrastructure
Before collecting more data, stakeholders should ask: what must be known, to what accuracy, to change which decision? Unlimited collection can increase recordkeeping burdens and fears of surveillance. The first work is to agree on a minimum dataset for each policy purpose, acceptable uncertainty, retention periods, farmers' consent and rights to view and correct records, protection of commercial information, and the allocation of public and private responsibility.
Government: publish carbon, supply and financial indicators and calculation rules, with version histories.
Public institutions: design data dictionaries, quality rules, access tiers and interoperability specifications for the integrated system.
Farmers and producer groups: negotiate data scope, field benefits, correction, secondary use and revenue-sharing principles.
Technology firms and researchers: disclose device performance and model error, separating policy figures from advisory predictions.
Finance and distribution bodies: align verification so the same reduction is not counted repeatedly across subsidies, certification and credits.
A smallest viable pilot would connect only the necessary feed, animal, shipment, manure and financial data from willing farms in one region. Its success metrics should be missing-data rate, farmer recording time, time to prepare programme evidence, reproducibility of calculations, changes in farm decisions and cost-benefit—not the number of sensors or dashboard screens. Improvement on these metrics would justify expansion to other regions and policies.
Conclusion: a legal starting point for connection, not a carbon-data revenue law
The Act's largest shift is to place carbon neutrality inside Hanwoo industrial policy alongside supply, quality, R&D, education and farm stability, rather than treating it only as an external environmental constraint. Because surveys, statistics and an integrated information system sit in the same law as greenhouse-gas reduction, supply management and R&D, there is now institutional space to examine trade-offs and results together.
That space does not automatically become a market for one AI platform or carbon income for every farm. Standards, measurement methodologies, verification, consent, security, cost sharing and procurement still require follow-on design. The opportunity for an AI Carbon Intelligence Platform is therefore not to overstate the law. It is to become trusted infrastructure that lowers farmers' recording burden, improves the evidence behind policy, and explains choices that can advance both emissions reduction and farm stability.
Sources
About AI Safety Korea
AI Safety Korea is a Climate Tech company building the digital infrastructure for livestock carbon management. Through its AI-powered Carbon Intelligence Platform, NexVue, the company enables real-time methane monitoring, digital MRV, and data-driven carbon management to support sustainable livestock production and the global transition toward carbon-neutral agriculture.
I Safety Korea 소개
에이아이세이프티코리아는 AI 기반 Carbon Intelligence Platform을 통해 축산 탄소관리의 디지털 인프라를 구축하는 글로벌 Climate Tech 기업입니다.
자체 개발한 NexVue는 축산농가의 메탄(CH₄) 배출을 실시간으로 측정하고, AI 기반 분석과 디지털 MRV(측정·보고·검증)를 통해 탄소 데이터를 신뢰할 수 있는 디지털 자산으로 전환합니다.
AI Safety Korea는 축산업의 지속가능성을 높이고 탄소중립 농업과 글로벌 탄소시장을 연결하는 세계적인 Carbon Intelligence Platform 기업으로 성장하는 것을 목표로 합니다.