Suyash Awasthi on Turning AI Investment into Measurable Enterprise Value

Jeff Kavanaugh:

Hi, I'm Jeff Kavanaugh at Infosys Connect here in Los Angeles. Today I'm joined by Suyash, president of Simplus, one of Infosys' subsidiaries. Good to see you, Suyash.

Suyash Awasthi:

Good to see you, Jeff, and thanks for the opportunity.

Jeff Kavanaugh:

Absolutely. Well, let's talk about the world of Salesforce and also what you're seeing in the ecosystem. How are your companies, your clients, trying to unlock AI value?

Suyash Awasthi:

So very good question. From an unlocking AI perspective, I think there's a lot of focus right now towards the value. So what we're seeing the customer…

Jeff Kavanaugh:

Not just buying something, but actually getting something measurable from it.

Suyash Awasthi:

Absolutely, and the enterprise objectives and values are becoming more critical because the investments are huge. And that's what's driving, right? What's the return on investment? And the unlocking of value right now is starting with a lot of new process reinventions, understanding a lot of prospects, and penetrating new markets, bringing new revenue opportunities that did not exist in the past.

Jeff Kavanaugh:

So, it's the efficiency part and it's also the innovation part.

Suyash Awasthi:

Absolutely. So from a whole aspect, right, they're giving them the possibilities that they'd not even know, right? Which markets to penetrate, which territory to focus, where should I get the biggest bang for my buck? How can I optimize my processes to reduce the costs? Some of those aspects were there, but with AI, it's giving you those decisions now and then also a whole roadmap to execute.

Jeff Kavanaugh:

What's a recent example of a client who came in wanting to maybe simplify or get more productive and then found one of these nuggets of wisdom coming out of it?

Suyash Awasthi:

One of our customers, it's one of the top two or top three networking equipment manufacturers based in the San Francisco Bay area, and as they're reimagining their whole channel revenue cycles, or partner relationship management, one of the things we started to do was… One of the big fours already did the whole strategy for them but it was not executable. They gave them a PowerPoint. Sitting with the chief automation officer, it was not even vibing. It was opening one of our platforms like Topaz Fabric and talking to them, creating a prompt and then identifying a lot of those asks. Because see, the uniqueness of these companies is the assets, the AI assets that they have, right? So just like us, like our assets are Topaz Fabric, but also built on the back of 50 other…

Jeff Kavanaugh:

It's not some shiny new model, it's what you already have in context.

Suyash Awasthi:

Absolutely. So they ran the same prompt on their own internal GPT version. And then we ran it, and what came out was the areas of focus that they should, like, immediately get some — define an MVP. Not just here's a strategy, 30, 60, 90 day, two year, three year plan, but an MVP, and then also created one very important aspect of even onboarding partners. How do you do due diligence? How do you assign a risk? And what we were able to tell…

Jeff Kavanaugh:

So you got down to the job to be done, the actual activity and the job.

Suyash Awasthi:

And defining an MVP, what we gave them as an outcome of this whole session…

Jeff Kavanaugh:

So it wasn't the PowerPoint, they actually could execute it.

Suyash Awasthi:

It was not a PowerPoint. 95% of the partner onboarding could be very quickly automated with AI and the cycle will go down from today, which is like 16 to 20 days, to hours.

Jeff Kavanaugh:

No way. Hours?

Suyash Awasthi:

Hours.

Jeff Kavanaugh:

Because partners, they don't come and go, but you want the ability to change them out when you need to.

Suyash Awasthi:

Absolutely, absolutely. And then the other thing is which partners they should not be doing any business with. That's another very important aspect.

Jeff Kavanaugh:

You're seeing leading indicators then, pattern recognition then of maybe why you shouldn't continue with a partner.

Suyash Awasthi:

Absolutely, absolutely. So see, this is AI value in action. You reduce the onboarding time by up to 95%, moved it from days to hours. The other aspect was fast tracking your time to remedy. Because when the partner comes in, you can enable them, you can enable the right partner in the channel to kind of drive that revenue through them. So that's a real use case. There's many more, about three, four others in the communication, technology space that they're working, in financial services, specifically banking. We're seeing a lot of this reinvention going on.

Jeff Kavanaugh:

Does tech get in the way because you're doing the MVP, you're putting the prompts in, you're getting good information back, but you do have to at some point connect to an ERP system or some kind of foundational. Any issues there?

Suyash Awasthi:

We are — what we are seeing now is a heavy emphasis. See, models — a lot of the organizations are focusing on models, Anthropic, all the frontier models, not to name anybody. But that's not where you start. Models are just one of the seven layers of AI, right? And where we come in and play, so tech can get in the way. If you are not looking at the holistic picture, like you start with defining your goals and objectives as we start and you work your way backward, technology also will participate if they see the value, and this is new. They want to play, they do not want to become a roadblock in this reimagination that we are going through. And tech modernization actually is becoming a big thing, as our chairman talked about it. There's $11.8 trillion, you know, addressable market, just on legacy modernization. So there's a lot of work. So tech will not get in the way. We'll be partnering with them to drive some of this. And the value we bring in is our engineering expertise, how you integrate. See, you don't fix what's not broken.

Jeff Kavanaugh:

Well, you're solving the whole technical debt burden.

Suyash Awasthi:

Absolutely. Not just technical debt. It's your process debt, it's your data debt, it's your strategy debt, and it's also your tech debt. So it's not just one aspect.

Jeff Kavanaugh:

We've got to have this whole thing on digital bankruptcy, avoiding digital bankruptcy, yeah.

Suyash Awasthi:

So it's exciting time. And the other thing, one of the other aspects that you're seeing on the same topic of, is tech — or this business or tech, you know, kind of tussle that we have seen. And then the top-down, bottoms-up approach. What I've seen now happen is a mandate from top down, right? Which is very critical, but also bottoms up on adoption. Otherwise it's just theatrics, it's just slideware, conversation. Customers want to see an experience versus being presented to.

Jeff Kavanaugh:

People already wanted to experiment. They have their own personal versions of all these things.

Suyash Awasthi:

So, these experiments have gone in for two years now. Now we are able to deliver actual working apps and solutions within days and weeks, not months and years.

Jeff Kavanaugh:

Let's talk about people for a second. The tech, the process, the strategy. How do you keep humans both in the loop and in the building?

Suyash Awasthi:

Yeah, very good question. See, today it's not just about a company coming in and taking over. Coding is just one aspect, right? Using frontier models, some of these coding platforms, vibe coding platforms, you can automate that. But still, on the decisioning — there's still a lot of sycophancy and hallucinations on the model. You cannot rely on it today. And I don't think it's gonna change even. AI will give you predictions, it's gonna give you projections, it's gonna give you the data, but ultimately the same prompt, if you use on another model, it could give you a little bit of a nuance.

Jeff Kavanaugh:

Absolutely. That's the whole deterministic, non-deterministic problem we're facing.

Suyash Awasthi:

So it's moved from deterministic to indicative to realistic, right? In the form of the decision-making culture.

Jeff Kavanaugh:

As long as AI doesn't tell us it depends.

Suyash Awasthi:

Absolutely. No, today models are not telling it depends. Today the model's saying, well, excellent question, let me — and they will answer what you want to hear.

Jeff Kavanaugh:

They'll boldly say it incorrectly, yeah.

Suyash Awasthi:

So it's a very interesting time, Jeff, and I think we're living it.

Jeff Kavanaugh:

What do you think is the one thing to look for in the next 6 to 12 months that's going to help companies kind of get to that next level?

Suyash Awasthi:

I see, and we are living obviously, being in the Bay Area, we get exposed to a lot of these new tech companies. See, number one is customers are being thrown. Go back to the dotcom or the cloud days. A lot was throwing, everything was as a service. Similar onset we're seeing with AI now. Companies are being thrown too many solutions, too many AI-native point solutions as well, or models. Every day new thing is coming. I think choosing the right partner and right AI stack is going to be very important. So look at a holistic strategy of partnership. Look at your own objectives and goals, right? And redefine. So those are the two main things. And then focus on the data, cause garbage in and garbage out. And this is where you cannot take human out of the loop. You definitely need data scientists, you need experts that can view those things and come back with, this is my AI strategy for the next 12 months. So partnerships are very important. That is where we also play, as you know, as being Simplus, Salesforce partners. But we need to expand, we need to think through of how the right partnership model can be leveraged. And the human and AI in the loop is gonna be pretty critical to it, to achieve those goals.

Jeff Kavanaugh:

Well, speaking of partnering, I know you have a lot of people at this conference to speak with, so thank you so much for your time.

Suyash Awasthi:

Thank you, Jeff, and it's always a pleasure.

Jeff Kavanaugh:

Yeah, you bet. Thank you. I'm Jeff Kavanaugh, and until next time, keep learning and keep sharing.