Securing the Use of AI

What is AI governance?

AI governance is the set of policies, processes and controls a company adopts to use artificial intelligence safely, legally and responsibly. It defines what is allowed, which data can be used, who approves each tool and how everything is recorded, turning AI use from an invisible risk into a program you can demonstrate to auditors, clients and the board.

Zamak TechnologiesUpdated on July 11, 2026

How an AI governance program works

AI governance is not a document you file away, it is a living cycle that follows the adoption of the technology. In practice, it rests on four repeating moves:

See the real usage

It all starts with discovery: which AI tools the company actually uses, in which departments and with what data. You cannot govern what you cannot see.

Set the rules

An AI use policy states what is allowed, what data can never be exposed and who approves a new tool. It is the clear boundary that was missing.

Approve and record

Each tool goes through an approved-tools catalog; each risk goes into a register. The company gains evidence that it decided, not that it ignored.

Review continuously

New tools and new risks appear every week. Periodic reviews adjust the policy and keep the program alive, instead of a snapshot that ages.

Source: official AI governance frameworks (NIST AI RMF and ISO/IEC 42001).

The pillars of an AI governance program

AI use policy The written rule: what is allowed, what is forbidden and who decides. It is the foundation that guides everything else.
Data classification Defining what information can go to an AI and what can never leave the company. Without it, the policy is a dead letter.
Approved-tools catalog A living list of what the company has authorized, with a simple process to assess each new tool before releasing it.
Risk register and auditable evidence The record of decisions, accepted risks and applied controls. It is what you show an auditor, a client or the board.
Reference frameworks Official structures like the NIST AI RMF and ISO/IEC 42001 give the common language and the roadmap to prove governance is serious, not improvised.

Why AI governance became urgent

63%

of breached companies have no AI governance policy or are still building one (IBM 2025)

34%

of those with a policy audit for unsanctioned AI use (IBM 2025)

89%

of executives worry about security risk when adopting generative AI (NTT DATA)

AI adoption ran ahead of the rules. Most companies still have no AI governance policy, and it is exactly that vacuum the numbers expose: 63% of breached organizations had no policy or were still building one (IBM, Cost of a Data Breach 2025). The cost of that gap shows on two fronts. In security, data leaking through an ungoverned AI adds hundreds of thousands to a breach (IBM 2025). In compliance, the company cannot prove to a regulator, a client or an insurer that it knows where AI touches sensitive data. AI governance is what turns we think it is fine into we can prove it, in the face of data protection laws such as LGPD and GDPR.

How to start governing AI in your company

An AI governance program is not born finished, nor does it need to be born perfect. What matters is to start with visibility and evolve in stages:

Run the AI exposure diagnosticDiscover which tools each department uses and where data is leaving. The real picture is the starting point of any policy.
Write the AI use policyClear, short rules people can follow, tied to the company's data classification.
Adopt an official frameworkAnchoring the program on the NIST AI RMF or ISO/IEC 42001 gives structure and a recognized way to prove maturity.
Keep it alive with periodic reviewReview the policy and the catalog in regular meetings. Governance that does not update becomes bureaucracy without effect.

In practice

Start with the question every board will ask: if a client or auditor asked today which AIs the company uses and with what data, would you have the answer in writing? If not, that is where governance begins.

How Zamak delivers AI governance

Zamak Technologies structures AI use governance as a living program, alongside the internal team: it starts with an AI exposure diagnostic, writes the use policy, builds the approved-tools catalog and keeps a risk register and auditable evidence under official frameworks. It is Governance and Compliance in the Zamak Method, which documents and proves responsible AI use without blocking productivity.

Frequently asked questions about AI governance

What is AI governance?

It is the set of policies and controls that define how a company uses artificial intelligence safely and legally: what is allowed, which data can be used, who approves the tools and how everything is recorded for proof.

What is the difference between AI governance and AI security?

Governance sets the rules and the proof (policy, approval, auditable evidence). Technical security applies the blocking (preventing data leaks, protecting AIs against attack). They are complementary layers: governing documents and proves; technical defense enforces.

Which frameworks guide AI governance?

The two main ones are the NIST AI RMF, a roadmap for AI risk management, and ISO/IEC 42001, the international standard for an AI management system, analogous to ISO 27001 for information security.

Is AI governance only for large companies?

No. Any company whose employees use AI already has the risk. A program proportional to size, with a clear policy and a usage diagnostic, protects both the small business and the large organization.

Where do I start with AI governance?

With discovery: an AI exposure diagnostic shows the real usage using the company's own data. From there, write the policy and adopt a reference framework.

Does AI governance hurt productivity?

On the contrary. Done well, it enables safe use instead of banning. Migrating to managed corporate accounts keeps the time savings and removes the leakage risk.