Aug 17, 2026 · 1 hr 2 min · 12 segments
"People assume any AI launch is a rocket. It looks more like a kitchen remodel, with inspectors watching behind you." Mounika Paruchuri sets AI strategy inside a regulated US bank, so she has a very…
Mounika ParuchuriGuest
Shamil MalachiyevHostAnd you've been basically part of the heavily regulated side of the tech industry as well.

So, yes, I've been working in the regulatory industry for 10 years and AI just enhanced the need for regulation.
So does it make your job a lot harder? Because I know that the more regulations you have in the company regarding AI, the more you have to pay attention to compliance, to the legal, to the risks, because you have like all the banking data going through your systems.
And does that actually like stop the innovation because people are more kind of scared to try? Or how do you go about actually allowing for that innovation to happen, even though it's heavily regulated industry?

And 100% you're right that the importance of the governance and guardrails has just become higher on the strategy with the AI models in place.

So people assume that any AI-based product launches sort of like a rocket or something, but essentially it looks more like a kitchen remodeling.

for lack of a story, because there is the inspectors watching behind you and you have to finish the kitchen remodeling in the right way.

And the drift that happens once you deliver and the loops that need to be happening to keep in check for the drift, the hardness, and all of that, which comes under the governance and guardrails is the most important part.

Governance is like teaching the people on what to do, what not to do, how you set your pathways, like your seam logging, your, you know, your, tracking and all that.

But guardrails is more of let's protect beyond the human because we want our people not to tiptoe around.

We want them to feel free and fully empowered and empowered to go and implement the solutions.

And hence the guardrails is the most important part that an AI strategy leader is going to be involved in because once they create those paved pathways that I'm talking about, it's very easy for people to feel secure enough to go implement solutions.
And can you talk a bit more about the actual guardrails? So for example, if we take, for example, a company with all different departments, and I guess your role is to make sure that, you know, the finance department uses this AI model, let's say the harness with certain tools, but these tools don't interact with HR systems, like that maybe don't have access.

So let me just simplify a little bit about harness, right? What we call harness in AI is essentially an integrated unit testing, your runway testing, and what that would be of older software technology.

So we are constantly evaluating the decisions made by the AI as to be fitting certain criteria.

And so, as you aptly described, harness would mean different things in different domains.

So a harness on the business side example and underwriting model is also about our proprietary knowledge staying in-house and not getting leaked out.
And you've been basically part of the heavily regulated side of the tech industry as well.

So, yes, I've been working in the regulatory industry for 10 years and AI just enhanced the need for regulation.
So does it make your job a lot harder? Because I know that the more regulations you have in the company regarding AI, the more you have to pay attention to compliance, to the legal, to the risks, because you have like all the banking data going through your systems.
And does that actually like stop the innovation because people are more kind of scared to try? Or how do you go about actually allowing for that innovation to happen, even though it's heavily regulated industry?

And 100% you're right that the importance of the governance and guardrails has just become higher on the strategy with the AI models in place.

So people assume that any AI-based product launches sort of like a rocket or something, but essentially it looks more like a kitchen remodeling.

for lack of a story, because there is the inspectors watching behind you and you have to finish the kitchen remodeling in the right way.

And the drift that happens once you deliver and the loops that need to be happening to keep in check for the drift, the hardness, and all of that, which comes under the governance and guardrails is the most important part.

Governance is like teaching the people on what to do, what not to do, how you set your pathways, like your seam logging, your, you know, your, tracking and all that.

But guardrails is more of let's protect beyond the human because we want our people not to tiptoe around.

We want them to feel free and fully empowered and empowered to go and implement the solutions.

And hence the guardrails is the most important part that an AI strategy leader is going to be involved in because once they create those paved pathways that I'm talking about, it's very easy for people to feel secure enough to go implement solutions.
And can you talk a bit more about the actual guardrails? So for example, if we take, for example, a company with all different departments, and I guess your role is to make sure that, you know, the finance department uses this AI model, let's say the harness with certain tools, but these tools don't interact with HR systems, like that maybe don't have access.

So let me just simplify a little bit about harness, right? What we call harness in AI is essentially an integrated unit testing, your runway testing, and what that would be of older software technology.

So we are constantly evaluating the decisions made by the AI as to be fitting certain criteria.

And so, as you aptly described, harness would mean different things in different domains.

So a harness on the business side example and underwriting model is also about our proprietary knowledge staying in-house and not getting leaked out.
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