Navrina Singh

Absolutely, Corey.

You know, at the end of the day, when you're using very powerful systems like artificial intelligence, what becomes paramount is can you trust them?

Can you actually have the confidence that they are going to behave the way that you expect them to behave?

So at the end of the day, how do you build that trust?

Governance is a set of policies and process and organizational structures and toolings that basically makes that trust a reality.

So governance is, you know, the oversight and accountability across your entire AI lifecycle to make sure that you're doing three things really well.

The first is aligning your AI systems to the objectives you as an organization or as an individual have so that the AI systems actually goes and does that, meets that goal.

Second is understanding the risk within these AI systems and mitigating those risks so that, again, you can have confidence in the deployment of these systems.

And third is really around compliance to not just regulation, but standards and company policies, again, to make sure that within the guardrails and the value you as an organization has established, is this AI system actually going to meet those guardrails?

Yeah, Grant, great question.

And I think the answer is simpler than it might sound.

The answer is literally starting with figuring out where you are in your AI governance maturity.

So at Credo AI, we have built an AI governance maturity model, which basically looks at a couple of key tenants, including how much third party AI are you actually buying?

Are you embedding a lot of AI in your first party applications?

Do you actually have an AI governance and AI security team which is responsible for making sure that there is oversight and accountability of these AI systems?

And do you have actually the budget authority and the right tooling to make this happen?

So based on some of these tenants, Credo AI can very quickly map where you are in your AI governance maturity model.

Now, if you're earlier in that AI governance maturity, that means either you're not buying a lot of AI or you're not using a lot of AI.

Having a very comprehensive standardized tooling really does not make sense.

However, if you are on the maturity spectrum,