Inside Insights: How AI is Disrupting Traditional Consulting Models with Shashank Paritala

Welcome to Tech-Driven Business brought to you by Innovative Solution Partners. I'm excited to have Shashan Peretala join me today to unpack how AI is shaping the consulting landscape, especially within data and analytics. We will explore how the economics of consulting are shifting, what skills are becoming more valuable, in how organizations can rethink their approach to architecture, delivery, and value creation as AI moves from a supporting tool to a core driver of how work gets done.

Hello, Sean. How are you? Hey, Lestence here. I'm doing well.

I'm so excited to have you on our show. So today we will be talking about the role of AI. What is the effect of AI and how it is shaping up the whole IT consortium world from a workforce perspective? I like to keep a little bit more focus on data and analytics.

I know that is very near and dear to you and what you have been doing over the course of your career. The whole idea is how do we get this elephant in the room? A lot of questions coming up and the economics is changing in this space. Let me just start with the basics.

How is AI changing the whole economics of consulting? Yeah, absolutely. Run a data and ML sort of practice focused around SAP, but also other things. Chatshake came out a couple years ago.

It started to arrive. I think people were feeding in snippets of code, getting out outputs. In the past few months, it's blown up. It's 10x.

I think people see that it's really arrived. It can really handle what would be major portions of work that we would sell as consultants in terms of hours and bags of hours, buckets of hours. It can do that stuff. And that realization has.

Let's just dive in a little bit deeper into the data and analytics space. Data warehouses have been around for a long time. Data lakes have started to appear out as the data lake house events and all of that. But I think a lot of customers are still in the space where they're looking to do data modernization.

And that used to be a huge part of the consulting work that a lot of consultants say, you're on platform X and we're going to move you to this new platform Z. And here's a couple hundred thousand dollar bill, et cetera. That was a big part of the business. And I think a lot of back work was refactoring old code, rebuilding data models, which honestly is the part that right now the agents that are available, the tools that are available have become very capable of.

It's very interesting. There's two aspects of this work that is sold. Number one, you go into the customer and say, how should you modernize? And there's a whole bunch of strategy and there's a whole bunch of really valuable stuff that you do for the customer.

But really, you're doing all that valuable stuff. A large bucket about the work of just moving, capturing old code and migrating over data. And that part is the one that's being impacted. So I think it's a pretty meaningful disruption.

As somebody who's bid on so many projects, who's been part of so many RFPs, many of them not one. I can tell you that entire space is quite confusing now. AI just coming in and really changing again. And I think that's interesting how you summed it up with saying that it's just how it was in the past versus what is happening in the past year or even just a few months.

Things have been really accelerated in this space in a good way, right? But there are, of course, challenges and the whole navigation of how do you merge these to a human aspect of it and then the whole AI component to the work that you're doing and how customers are looking at it from their perspective. Talk about the skills now. Consulting skills, there are some that are becoming more like commodity.

There are still other skills which are highly sought after and it does make a difference. How do you categorize them? What is your view on that? That's a really good way to put it.

Some things are now commoditized or less valuable, and some things are actually more valuable and more meaningful to customers I think we can have both thoughts in our head which is I anxious about what happening but oh boy there also an opportunity out there with what happening and the tools that are coming out And I in that space Both thoughts live in my head every day Let just talk about some of the things that are commoditized. I write X and Y sets of code when I'm given a batch and I deliver that code.

I factor in code or writing code from scratch even. Give it if you have a really strong specification and my job is to write the code, I don't think that anyone's going to deny that's become far less valued. I think that's just easier to deal with the tools that are out. However, getting that specification right from the customer has actually become really valuable.

If you can deliver so fast now that you have these tools, it's really important that you get to that customer and you get that spec or that you're rapidly prototyping and getting something in front of the customer and avoiding ambiguity and like planning these sprints in a way that is very effective. You're able to wrap up a project that would have taken eight sprints and maybe four. A consultant using these tools for doing the right things, getting to that customer, figuring out what they want, helping them reduce ambiguity, and then clicking the go button and getting that project going.

So much more power. I think this is going to be the give and take where different parts of the space get squeezed, but then other parts of it become more valuable and the people who can do that are going to be. Another one is architecture, probably. I think this is a good segue into architecture and all that, because that's where the real value comes in when you're looking at these projects and how they get stood up and then get implemented the whole nine years.

It all depends on overall setup and the design. And of course, the architecture piece is one of the important components of this conversation. You mentioned how do you shape up your projects, especially when you're looking at, you mentioned two things. One was, if you're doing a sprint in the past, if it was taking you eight sprints to do something, then the whole cycle is either slashed in half or cut down to a more digestible chunk.

But it very well depends on how is that requirements gathered from the customer and how is that requirements put into a design where anyone who is looking at it, if you're using agents, are able to build the code you want or your developers are taking the help of the AI tools available at their disposal. How do you take this conversation into an architecture perspective? What's your take on that of an overall design? Right now, when you look at where a customer is and think about an ideal consultant, this is somebody that knows your business and you know them and they know you and they know your business users and they know all these little things that if only you could put them all in writing, you could feed it to a model and perhaps it would do a great job.

But the reality of it is that the consultant that really knows all of those stakeholders, which business users want, those all become critical. And also where you're trying to go. Hey, I'm trying to acquire to grow in the next decade. All of these pieces of context help you say, this is probably the platform you want.

This is probably how you want to structure your data where Data Lake house or Data Lake and whatever. Here's the tools you want in play. Here's how you should be thinking about this. These are all important conversations that happen before any of the build phase starts.

I'd say that's probably the way you are an ideal consultant. You know so much about that customer that you're able to sort of give that feedback. And also maybe you know that customer, but you also know that industry it brought. All of that comes into play when I guess we can just call it instinct, judgment, business context.

All of those, you know, super valuable before clicking the go button and just building something. I think it makes sense because especially, like you said, the whole laying the foundation is the key to having a good build. build and the build is where the real value of AI is taking off and is helping speed up the implementation part which kind of gets us into this discussion right When we talk about enterprise applications in this AI first world everybody looking at AI and say I got SAP I got some other ERP system in my environment and I looking at having this AI enablement How do you justify that?

How do you deal with it? Especially let's bring it back to data analytics, maybe Datasphere and some of these cloud data warehouses. there are a lot of things that goes behind it, especially when you're dealing with enterprise-level data. What happens in this AI-first world?

First off, I think part of what you're talking about is probably security and what's happening in that context, right? Governance. Customers are realizing if you don't give AI tools to your employees, they will find a way to still use them. This is number one.

I think that's probably the biggest reason that people need to get going on these tools and getting them deployed and applications. But I'll go broader just around the implementation of solutions and what I've seen, which part of it is like giving me a little bit of deja vu, because I think it's being led by a lot of Fobo, et cetera. An example of how I'm seeing AI solutions deployed is here's a bot that you can feed some input into, we have a contract with OpenAI or whoever.

So that's one kind of usage and that's fine. And then when you think about applications being deployed with generative AI and intelligence and you're trying to use enterprise data, you're trying to make these generative AI applications. What I'm seeing is a lot of point solutions, okay? I'm seeing things be built like, ah, we wanted a generative AI app for this specific thing and we're going to get that deployed in two weeks or whatever.

Actually, this is leading to some silos and things like this, which we have both seen in data all the time. So there's agents everywhere. There's agents in your SAP system and your Salesforce system and your X system, your Y system. And none of those agents really know what's going on with the other agents and your business users are feeding context back and forth.

So I think that's a really incredibly important space for customers to think about and us as consultants to think about what's going on here. Everyone's trying to build something with AI. I've never seen so much interest in my life. Being in data and analytics, getting the time of a C-suite executive was so difficult, right?

Because they were worried about other stuff. Now they're just on call. Two directors, VPs, everyone's sitting on call, fully engaged. So I think people are kind of doing things.

And I think this is a moment of thinking, how can we build these systems so that you don't have context silos, data silos, et cetera, which is the conversation I had with some customers and other ones are faster and just building points. That's a great way to look at it. It has to be context driven and the context sometimes can be so narrow that you forget about the larger impact of that. And I think that you hit on the head with this one, like folks who are trying to run faster, which is what everybody is trying to do right now.

Do not forget that, hey, if you don't have the right contacts or if you're not looking at the bigger picture, you may create a bunch of small monsters around you. And then you have no control on those agents and how everything is working together. Let's look from a different angle. I know you work with larger firms and more specialized SAP environments.

from your perspective, what has most shaped your view of where consultants actually create value for clients? How do you do that going forward in this AI? If I really think about consultants and oh my God, that went really great versus any firm could have done this kind of work. I feel it's when you're able to just get rid of the ambiguity.

And I think if there's a metric I could tie this to, and by the way, I'm not saying this as someone who's done it all right. I'm talking as somebody who's done it wrong and having scar tissue and all this stuff. It's the idea, like how many change orders did you take to get to the finish line, right? I think that matters.

And the reason it matters is because, yes, it might be the customer that by the terms on the contract did ask for a change that wasn't in the original contract. But the real question is, why didn't they know to ask that when you were writing the original contract And obviously you always going to have minor changes across the board in every project I think that a lot of projects specifically in the SAP space but probably everywhere but I just going to talk about the SAP space These are arduous journeys.

There's so much ambiguity. You'd start with this blurry idea that's not the same in everyone's head. Then you start creating this image and it's getting clear only at the end of it. There's a lot of pain in that.

So I think coming in and having really an authoritative voice and helping the customer make these decisions before you click the go-on. I probably think that's the most valuable. And honestly, it's been the times in my career where I said, ah, okay, I did something there. Do a nugget of wisdom because I did it wrong over there.

And now I'm doing it right. And I guided this customer in the right path. It's probably the highest value. I think that's the real value.

Like you said, this is where the customers get the most value. Take out that unknowns up front because you're not spending too much time in the build. Because now we have the capability to automate some of these build steps and spend more time on the requirements and design. And then making sure that change orders are minimized.

That's the whole goal, right? Do it right the first time and keep on doing that. I know we are over our time. What is the one key takeaway that you want to leave with our listeners?

I think that at the moment, it's probably a pretty scary, anxious slash exciting time. It's both at the same time. I think consultants, I think things are going to change. I think we are probably the industry where we unfortunately sold ours.

That's the thing that's being hit. It's really a hard time in that context. However, I think the opportunity is huge. The workflows, the things you understand having been at so many customers can lead to the creation things that you build that are proprietary to you and you can deploy to help customers and customers will find value.

A lot of consulting companies, if you really think about the moats that they have, it's really nothing, right? It's either you're really large and you have a bench, which is a great boat or was a great boat. And then number two, you have a bunch of slide where that speaks about methodologies, which are just derived from agile or whatever. The reality is now there's a real way to build things that are going to be valuable to customers and have that be your thing, your mode.

You go in and you help the customer and you share what else. So I think as a consultant, think about the things you're doing at customers and see what you can build. I'm just figuring it out myself now. I think we all are.

I think, and that's the key, right? how you keep on upskilling yourself and keeping up with what is possible with automation, what is possible with generative AI. At the same time, how do we bring down the cycles, especially when you're doing implementations and make it a little bit more robust and in a way bulletproof so it's able to sustain changes in a way that you can still manage it. Those change orders can be minimized.

and at the end, the value is given to the customer and they see what is possible and how quickly do those things. I think that was a great way to sum this conversation up. I really appreciate your time. Thank you for coming and I look forward to seeing you again.

Thanks for listening to Tech Driven Business brought to you by Innovative Solution Partners. As AI continues to reshape consulting, the shift is clear. Value is moving away from ours and toward outcomes. Shashank's key takeaway?

The opportunity is real for those willing to evolve. Focus on clarity, move faster with purpose, and start building solutions that scale beyond a single project. Because when AI is paired with the right strategy and insight, organizations can accelerate delivery, reduce friction, and create meaningful, lasting value. We would love to hear from you.

Continue the conversation by connecting with me on LinkedIn or X. To learn more about Innovative Solution Partners and schedule a free consultation, visit isolutionpartners.com. And don't forget to subscribe to our YouTube channel so you never miss an episode.

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