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Meeting the Needs of the Assurance Sector: Informing the Kaitiaki Intelligence Platform Design

August 2024

This report outlines the environmental reporting data sought from Māori Agribusiness Collectives by regulators, industry, and sustainability assurance schemes in general. It identifies the types of reporting data that could be automatically generated by a Kaitiaki Intelligence Platform (KIP), a Māori-led initiative to design an environmental sensing network, thereby reducing reporting compliance costs on farmers. Furthermore, it explores opportunities to sell environmental data to assurance providers.

One use of this data is to aid Māori food producers in meeting the sustainability verification standards and environmental reporting requirements of markets, industry, and regulators – referred to collectively in this report as the ‘assurance sector’.

The environmental intelligence needs of this sector is explored in this report, and the extent to which the data they require may be autogenerated by a KIP. The purpose of the report is to create insights that may be used to inform the KIP design and automate reporting to the assurance sector.

The report provides background regarding the assurance sector before drilling down into specific indicators and metrics currently used, or under development, to verify/audit the environmental impacts of land management practices. The report also incorporates insights from 44 thought leaders that operate in the assurance sector – including regulatory agencies, accreditation bodies, assurance providers and retailers to determine their readiness for adopting new technologies to automate environmental reporting processes. It has a strong focus on the three priority areas for Māori and New Zealanders generally: carbon, water, and biodiversity.

This report also defines the relevant indicators and metrics to be incorporated into a KIP design to meet assurance sector requirements, and outlines the next stages that are necessary to ensure acceptance of KIPs by the assurance sector.

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