Discover
Inventory AI tools, embedded features, use cases, data flows, vendors, and accountable owners.
Use AI. Keep control.
Adopt AI with a clear purpose, protected data, approved tools, human accountability, and governance that can stand up to client, insurer, and leadership questions.
Let’s talk about AI security and governance ↗The service is more than a collection of tools.
AI is already entering most businesses through individual employee choices, built-in software features, and vendor integrations. The opportunity is real, but safe adoption requires visibility, approved tools, clean permissions, protected data, specific workflows, and accountable people.
A strong fit when:
- Employees are using public AI tools without a shared policy or approved toolset.
- Clients, insurers, or leadership are asking how AI use is controlled and documented.
- Microsoft Copilot, Claude, ChatGPT, or another platform is being considered without a data-readiness and permissions review.
- The business wants practical automation while preserving human approval for consequential actions.
What leaders usually ask.
Do we need an AI program if we have not formally deployed AI?
Yes. Employees and software vendors may already be introducing AI into daily work. Discovery establishes what is in use, what information it can reach, and which decisions need governance.
Can AI see everything employees can see?
Some connected tools can surface information the user is already permitted to access, including information that is difficult to find manually. Permissions and data governance should be reviewed before broad rollout.
Does an AI policy block useful work?
A good policy makes approved use easier. It defines acceptable tools, restricted data, review requirements, and a practical exception path instead of relying on a blanket prohibition.
Will automation remove approvals?
Only when that is explicitly appropriate. We design approval points around financial, security, client, legal, and other consequential actions.
Can this align with a recognized framework?
Yes. The program can be mapped to the voluntary NIST AI Risk Management Framework and, where appropriate, the management-system structure of ISO/IEC 42001. Alignment does not imply certification.
Two disciplines. One accountable program.
Protect the systems, identities, and information AI can reach.
PrimeTime reviews permissions, connectors, data exposure, vendor settings, and attack paths around the tools your people use. Controls follow the use case instead of stopping at a written policy.
- Reduce oversharing before broad Copilot or assistant rollout.
- Set data boundaries for public and connected AI tools.
- Prepare people for AI-enabled impersonation and fraud.
Make ownership, acceptable use, and review visible.
Every approved use should have a business owner, defined data access, human oversight, vendor record, and review schedule. The result is evidence leadership can use with clients, insurers, and auditors.
- Maintain an inventory of tools, owners, and business uses.
- Document approvals, exceptions, incidents, and material changes.
- Connect AI decisions to security, privacy, and business risk.
Security has to reach beyond the prompt box.
Open each area to see how PrimeTime turns a broad AI concern into a practical control and a clear business outcome.
RECOGNIZED STRUCTURE
Governance that can map to established standards.
When the business needs formal structure, PrimeTime can organize the program around the voluntary NIST AI Risk Management Framework and the management-system approach of ISO/IEC 42001. The scope and evidence are matched to the organization; alignment does not imply certification.
What is included.
Open any capability for the specific controls, operating work, and business outcome behind it.
Let’s make technology
your advantage.
Start with a conversation about your business.
We’ll work out the technology together.