Партнёр KPMG Australia, как сообщалось, использовал ИИ для списывания на внутреннем тесте по обучению ИИ и был оштрафован на 10 000 австралийских долларов

Влияние на бизнес и риски МСБ

The operational impact of this incident—where a senior partner at KPMG Australia was fined $10,000 by the firm's compliance board for copying proprietary training test questions into the public ChatGPT to cheat on an internal assessment—resulted in a severe breach of confidentiality, audit investigations, and loss of leadership credibility. Copying proprietary corporate materials into public AI models leaks intellectual property and violates client confidentiality, exposing the firm to potential contract breaches and legal claims. Regulatory Impact Alignment: Financial audits, transaction tracking, and internal reporting algorithms must comply with Sarbanes-Oxley (SOX) Section 404 and AICPA SOC 2 Type II regulations. Accounting teams must prevent data leakage by isolating sensitive financial logs from public generative AI models.

Главный комплайенс-урок

Employees—even at the executive level—frequently bypass internal confidentiality agreements out of convenience, leading to massive Shadow AI leakage. Corporate training materials and intellectual property must be protected from leakage via third-party AI models. Standard NDAs and IT policies must explicitly address the use of public generative AI. Compliance Audit Standards: For detailed verification audits, this case maps directly under Sarbanes-Oxley Act (SOX) Section 404 & AICPA SOC 2 Type II Safeguards. Systems deploying similar AI features must maintain dynamic security logs and hold systematic compliance records.

Пошаговый план внедрения регламентов

• 1Strict AI NDA policies: Enforce a strict, legally binding policy prohibiting the input of any proprietary corporate materials or client data into public generative AI interfaces.
• 2Deploy secure enterprise AI: Provide secure, internally hosted enterprise AI platforms (white-listed environments) that guarantee prompt data is not used for model training.
• 3Automated network logs audits: Deploy automated network logs auditing to detect and flag unauthorized transfers of corporate documents and files to public AI domains.
• 4Regular Partner ethics training: Conduct regular compliance training and mandatory security testing for all partners and staff on the secure, ethical use of generative AI.
• 5Deterministic Audit Trail: Generate complete, cryptographically signed, and chronological audit trails for every automated transaction analysis.
• 6Vpc Network Isolation: Restrict all corporate ledger evaluations to network-isolated Private Virtual Clouds (VPCs) without public internet hooks.
• 7Leakage Monitoring: Configure active data loss prevention (DLP) alerts to immediately block the paste or upload of proprietary files to external LLM APIs.