The CPC system uses AI to strengthen data verification procedures and support accuracy, consistency, and auditability across the program. AI functions strictly as a support layer and does not replace approved emissions methodologies, verification standards, or human judgment.
Emissions calculations within the CPC system are performed using established methodologies. AI tools support data preparation before and after these calculations by ensuring inputs are complete, consistent, and aligned with program requirements.
AI-enabled validation is applied during farm-level data intake. As data is received, automated checks review submissions for completeness, reasonable value ranges, and internal consistency. Submissions that fall outside expected patterns or constraints are flagged for further review and assessed by program personnel prior to use in emissions modeling.
AI tools also support the alignment of real-world farming practices with required model inputs. This reduces manual interpretation errors, identifies missing or inconsistent variables, and highlights assumptions that may influence carbon intensity outcomes. Emissions calculations themselves remain fully methodology driven and unchanged.
For verification and reporting, AI supports the organization and assembly of standardized audit documentation. Reported practices, supporting evidence, reviewer notes, and final outcomes are compiled in a consistent format to improve traceability and reduce administrative effort while maintaining clear review controls.
Downstream, AI-supported consistency checks are used to monitor CPC records across the chain of custody. These checks help ensure issued CPC volumes align with verified production and support the prevention of double counting.
Across all applications, AI is used to support data validation and documentation. All decisions and approvals remain the responsibility of human reviewers to preserve the integrity, credibility, and defensibility of the CPC system.
