What AI governance covers
- Policy: acceptable use, prohibited uses, disclosure
- Accountability: named owners and decision rights
- Risk appetite: which AI uses are acceptable for which data
- Vendor and procurement decisions
- Legal and regulatory alignment, fairness, and transparency
- Oversight: reporting to leadership and the board
What AI security covers
- Identity and authentication for AI tools and agents
- Least-privilege permissions and credential management
- Data protection: what AI can read and where data goes
- Prompt-injection and misuse defenses
- Logging, monitoring, and detection
- Incident response for AI scenarios
Where they meet
| Topic | Governance question | Security question |
|---|---|---|
| Inventory | Which AI uses have we approved? | Which AI systems actually exist and what can they reach? |
| Vendors | Is this vendor acceptable for this use? | Do its terms and controls protect our data? |
| Agents | Should AI be allowed to act here? | Are its permissions, approvals, and logs adequate? |
| Incidents | Who decides on disclosure? | How do we contain and investigate? |
A policy that says "no PHI in unapproved tools" is governance. Knowing which tools employees connected to their mailboxes last month is security. Neither works without the other, which is why FlashTower's ruleset includes both organization-level governance rules and system-level security rules in one assessment.
Who owns what
In larger organizations, governance often sits with a cross-functional committee led by legal, compliance, or risk, while security sits with the CISO. In smaller organizations, one person frequently owns both. Either model works if decision rights are written down: who approves new AI uses, who approves access for AI systems, who can grant exceptions, and who is informed when something goes wrong.
The failure mode to avoid is governance that produces policies no one can verify, or security controls that do not reflect decisions the business actually made. Regular joint reviews of the AI inventory — covering both what is approved and what is actually connected — keep the two aligned.
Frequently asked questions
Is responsible AI the same as AI governance?
Responsible AI usually refers to principles such as fairness, transparency, and accountability. AI governance is the set of processes and decision rights that put those principles — and security, privacy, and legal requirements — into practice.
Where should a small company start?
With the overlap: an inventory of AI tools, an acceptable-use policy naming approved tools, SSO and MFA, and human approval for AI that takes actions.