Material AI risks for executive leadership
In conversations with customer CIOs, five risks recur almost word for word. BAGF is structured to address each one. Every risk has at least one technical section in this whitepaper that states how Bizzi mitigates it, with verifiable evidence.
Hallucination in financial reports
AI fabricates figures or aggregates data incorrectly. In accounting, one wrong number leads to an incorrect approval. Bizzi enforces Grounded Reasoning. Every AI output cites a specific source. Contract clause. Invoice ID.
Mitigation: Pillar III §10
Prompt injection via business documents
Attackers inject hidden instructions (white text on white background) into business documents asking the AI to bypass security rules. Bizzi runs Input Guardrails that scan OCR text before it reaches the LLM. The system uses <user_data> context separation so the model distinguishes system instructions from untrusted data.
Mitigation: Pillar V §3
PII leakage through LLM
Personal data on invoices (names, phone numbers) leaks to commercial LLM APIs and persists in their training data. Bizzi applies PII Redaction at the gateway before any data reaches the LLM. Bizzi signs Zero Data Retention with every vendor.
Mitigation: Pillar II §3
Single-vendor LLM lock-in
Dependence on a single LLM provider creates cost, downtime, and legal risk. Bizzi runs an AI Gateway with automatic fallback routing to a backup model when the primary fails.
Mitigation: Pillar IV §9
Compliance drift (Decree 13, EU AI Act)
The AI regulatory environment shifts fast. Decree 13/2023. Vietnam’s draft AI Law. EU AI Act phased rollout through 2027. Bizzi runs a quarterly regulatory review cycle and updates DPIA and ROPA accordingly.
Mitigation: Pillar II
These five risks are not exclusive and not exhaustive. The technical sections describe secondary risks (model drift, excessive agency, denial of wallet) and the matching controls.