AI governance: a checklist for the board and the CIO
AI governance is the set of rules, owners and records that gives a company control over how it uses AI. See what the board and the CIO should check.
AI governance is the set of rules, roles and records that lets a company know where it uses artificial intelligence, who is accountable for each use and how to prove what the AI did. It does not exist to slow AI down, but to let the company use it in important processes with confidence. In practice, the board sets the risk appetite and the CIO turns it into controls that work day to day.
Many companies already use AI across several areas, but governance is still scattered among IT, legal, security and the business. This checklist organizes the questions the board should ask and the controls the CIO should have, in plain language. For regulatory points, always confirm with your company’s legal team.
What is AI governance and why is it a board topic?
AI governance answers three questions: what is AI doing in the company, under which rules and who is accountable for it. When AI only suggested text, these questions seemed like technical details. When it starts running processes, handling customer data and influencing decisions, they become matters of risk, reputation and results.
That is why the subject reaches the board. The board does not need to understand every model, but it does need to know whether the company has visibility into its AI uses, whether the relevant risks are mapped and whether someone is accountable for them. It is the same role the board already plays in information security and data protection.
There is also the regulatory landscape. In Brazil, the LGPD, the country’s General Data Protection Law, is in force with the ANPD as the authority, and regulated sectors follow rules from bodies such as Bacen, CVM, ANS and Anvisa. PL 2.338/2023, the bill for Brazil’s AI legal framework, was approved by the Senate on December 10, 2024 and, as of October 2026, was still under analysis in a special committee of the Chamber of Deputies, with the vote postponed until after the elections. The text may change, but the direction is a risk-based approach with human oversight, transparency and records.
AI governance checklist for the board
1 · Do we have an inventory of AI uses? The board should receive a consolidated view of where AI is used, what it is for and which areas own each use.
2 · Do we know which uses are most sensitive? Ask for a risk classification that highlights uses affecting decisions about people, sensitive data or critical processes.
3 · Who is accountable for AI? There should be named owners, with clear roles across the business, IT, legal, security and privacy.
4 · How do we measure value and risk? Governance should show both the results AI delivers and the incidents, exceptions and reviews, with regular reports to the board.
AI governance checklist for the CIO
1 · Least access. Each AI agent or tool should access only the data and systems it needs for the task, following the same permissions that apply to people.
2 · Data inside the perimeter. Define in which environments AI may process company data, under which contracts, and offer corporate alternatives so no one needs to use tools on their own.
3 · Audit trail. Record what data the AI accessed, which rule it applied, what the result was and who approved it. Without records, there is no way to explain a decision.
4 · Human oversight. Define which decisions AI makes on its own, which it suggests for a person to decide, and how reviews work when someone challenges a decision, including the review of automated decisions provided for in the LGPD (article 20).
5 · Vendors and contracts. Review with legal what each AI vendor offers in records, data protection and transparency, and who keeps the context and rules built in the operation.
How to start AI governance without stalling innovation
The most common mistake is trying to write the perfect policy before knowing what exists. Start with the inventory and the most sensitive uses. Governance proportional to risk lets simple uses move fast while critical ones get more control.
It also helps to build governance into the operation rather than next to it. When rules, permissions and records are part of the workflow itself, teams do not have to fill in separate controls. Governance stops being a brake and becomes the normal way of working.
Finally, treat governance as something alive. Regulation is still being debated, AI uses change and the company learns. Review the inventory and risk classification often and adjust with your legal team once the law is approved.
A good rule of thumb is to separate three levels. Low-risk uses, such as summarizing internal documents, proceed with general guidance. Moderate-risk uses, such as supporting customer service, call for access rules and records. Sensitive uses, which influence decisions about people or critical processes, require defined human oversight, periodic review and legal follow-up. That way, the control effort goes where the risk actually is.
How Semantix builds governance into the operation
At Semantix, AI agents handle the volume and specialists handle the judgment, and you choose how far Semantix goes: the platform, building with your team or running the operation with outcomes in the contract. Safetix, part of the Semantix AI Suite, governs that operation: it applies rules and permissions, grants access only to what is needed and traces every execution, with human approvals recorded. Personal data is masked before it reaches the model, and the client chooses where the models run, including in Brazil or in its own environment.
We operate with ISO 27001, ISO 27701, PCI-DSS and SOC 2 Type II certifications and follow the discussions of ABRIA and PL 2.338/2023. For leaders shaping their strategy, the starting point is a diagnostic that shows where the risks and the value of AI sit in your operation.
That is how Semantix, The Enterprise AI Company, builds enterprises that learn.
“When rules are part of the workflow itself, governance stops being a brake and becomes the normal way of working.”
Insights
Frequently asked questions
What is AI governance?
It is the set of rules, owners and records that lets a company know where it uses AI, who is accountable for each use and how to prove what the AI did. It makes it possible to use AI in important processes with control.
Who is responsible for AI governance in a company?
The board sets the risk appetite and monitors results, and the CIO turns that into controls. The business, legal, security and privacy teams also have defined roles, because AI cuts across all of these areas.
Is AI governance mandatory in Brazil?
The LGPD, Brazil’s data protection law, already applies whenever AI processes personal data, and regulated sectors have their own rules. PL 2.338/2023, Brazil’s AI bill, is still under debate and the text may change. Confirm the obligations for your case with your legal team.
Where should AI governance start?
With an inventory of AI uses and a risk classification that highlights the most sensitive ones. From there, define owners, least access and decision records.