Reading calendars, sending email, changing records or calling APIs are actions. When an agent can execute them, autonomy becomes an operational permission.
Essential controls for tool-using AI agents: separate identities, least privilege, scoped permissions, parameter validation, human approvals, limits, sandboxing, secrets, logs and kill switches.
When a system recommends, ranks, prioritizes or drafts, organizations should be able to explain where machine suggestion ended and human decision began.
A practical model for documenting AI-supported decisions, including context, sources, model or service version, meaningful human review, overrides and final accountability.
An AI text box may receive contracts, customer records, strategies and entire documents. The risk starts before the answer: it starts with what was submitted.
Why prompts, attachments and conversation history belong in data governance, including minimization, anonymization, retention, enterprise accounts and model-training settings.
Reading calendars, sending email, changing records or calling APIs are actions. When an agent can execute them, autonomy becomes an operational permission.
Essential controls for tool-using AI agents: separate identities, least privilege, scoped permissions, parameter validation, human approvals, limits, sandboxing, secrets, logs and kill switches.
When a system recommends, ranks, prioritizes or drafts, organizations should be able to explain where machine suggestion ended and human decision began.
A practical model for documenting AI-supported decisions, including context, sources, model or service version, meaningful human review, overrides and final accountability.
An AI text box may receive contracts, customer records, strategies and entire documents. The risk starts before the answer: it starts with what was submitted.
Why prompts, attachments and conversation history belong in data governance, including minimization, anonymization, retention, enterprise accounts and model-training settings.
As AI connects to documents, APIs, databases and internal systems, security can no longer depend only on model quality. Access design and control become central.
A pillar guide to corporate AI security covering identity, least privilege, data classification, RAG, API keys, prompt injection, logs, model changes, vendors and incident response.
After mapping Shadow AI and assessing vendors, organizations need clear rules for approved tools, data, human review, accountability and incident reporting.
An internal AI policy does not need to be long to work. It should define approved tools, prohibited data, human review, accountability, evidence, training and incident response.
Not every use of artificial intelligence requires the same level of control. The key is recognizing when data, impact, autonomy, scale and reversibility turn an ordinary task into a critical decision.
A practical framework for classifying corporate AI use by risk, considering data sensitivity, impact on people, autonomy, scale, reversibility and reliance on AI output. The matrix helps organizations decide when basic guidance is enough and when approvals, human review, logs, testing and stronger controls are required.
Executive and practical analysis of ai vendor due diligence: clauses, data, models and accountability before contracting, connecting digital law, governance, security, data protection and business operations.
This article translates ai vendor due diligence: clauses, data, models and accountability before contracting into business risks, controls, accountability and practical actions.
Executive and practical analysis of shadow ai in companies: discovering and governing tools adopted outside it, connecting digital law, governance, security, data protection and business operations.
This article translates shadow ai in companies: discovering and governing tools adopted outside it into business risks, controls, accountability and practical actions.
Executive and practical analysis of corporate responsible ai program: policy, inventory, risk, contracts and evidence, connecting digital law, governance, security, data protection and business operations.
This article translates corporate responsible ai program: policy, inventory, risk, contracts and evidence into business risks, controls, accountability and practical actions.
Executive and practical analysis of age assurance under brazil's eca digital: protecting children without turning privacy into surveillance, connecting digital law, governance, security, data protection and business operations.
This article translates age assurance under brazil's eca digital: protecting children without turning privacy into surveillance into business risks, controls, accountability and practical actions.
Executive and practical analysis of digital platforms and new obligations: structuring transparency, fraud prevention and duty of care, connecting digital law, governance, security, data protection and business operations.
This article translates digital platforms and new obligations: structuring transparency, fraud prevention and duty of care into business risks, controls, accountability and practical actions.
Executive and practical analysis of brazil's digital child and adolescent statute under enforcement: what the discord case teaches about platform duty of care, connecting digital law, governance, security, data protection and business operations.
This article translates brazil's digital child and adolescent statute under enforcement: what the discord case teaches about platform duty of care into business risks, controls, accountability and practical actions.
