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

Explore how AI is reshaping the consulting landscape in this episode of Tech-Driven Business. Mustansir Saifuddin sits down with Shashank Paritala for a candid, real-world conversation on how AI is transforming the economics of consulting—especially in the data and analytics space. From shifting skillsets to accelerating delivery timelines, this episode breaks down what’s changing, what still matters, and where firms can truly differentiate.

If you’re leading or supporting digital transformation, this is a must-listen. Shashank shares perspective on what’s becoming commoditized—like code generation and refactoring—and what’s increasing in value, including architecture, business context, and the ability to reduce ambiguity upfront. The conversation also explores how AI is impacting project cycles, why strong requirements and design are more critical than ever, and the risks of rapidly building disconnected “point solutions” without a cohesive data and AI strategy.

Tune in for practical insights on how consultants and organizations can adapt—by focusing less on selling hours and more on delivering outcomes, building reusable solutions, and leveraging AI to move faster with greater precision.

Shashank Paritala has worked across the SAP data and analytics space for over a decade, including Accenture and Avvale, where he led the Data & Analytics practice. His background includes analytics strategy, enterprise data architecture and has been involved with SAP Datasphere since the early days - helping clients turn data into business outcomes.

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Episode Transcript:

[00:00:00] Mustansir Saifuddin: Welcome to Tech- Driven Business, brought to you by Innovative Solution Partners. I'm excited to have Shashank Paritala 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, and 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.

[00:00:39] Hello, Shashank. How are you?

[00:00:46] Shashank Paritala: Hey Mustansir, I'm doing well.

[00:00:48] Mustansir Saifuddin: I'm excited to have you on our show. 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 consulting work

[00:01:00] from a workforce perspective. I like to keep a little bit more focused 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.

[00:01:11] 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?

[00:01:23] Shashank Paritala: Yeah, absolutely. I've run a data and an ML sort of practice focused around SAP, but also other things. Chat GPT came out a couple years ago. It started to arrive. I think people were feeding in snippets of code, getting out outputs.

[00:01:38] In the past few months it's blown up. It's 10 X. 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 and buckets of hours. It can do that stuff. That realization has clicked. 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 on the scene, data lake houses and all of that. But I think a lot of customers are still in the space where they're looking to do data modernization. That used to be a huge part of the consulting work that a lot of consulting firms did. hey, you're on platform X and we're gonna move you to this newer platform Z and here's a couple hundred thousand dollars bill, et cetera.

[00:02:28] That was a big part of the business and I think a lot of that 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 doing. It's very interesting.

[00:02:47] There's two aspects to 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.

[00:03:02] A large bucket of the work of just moving refactoring old code and migrating over data, et cetera. And that part is the one that's being impacted. So I think it's a pretty meaningful disruption. As somebody who's been 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 with AI just coming in and changing the game.

[00:03:29] Mustansir Saifuddin: 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 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 two.

[00:03:49] The human aspect of it, and then the whole AI component to the work, work that you're doing and how customers are looking at it from their perspective.

[00:03:59] Let's [00:04:00] 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?

[00:04:18] Shashank Paritala: 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'm anxious about what's happening, but, oh boy, there's also an opportunity out there with what's happening and the tools that are coming out, and I'm in that space. Both thoughts live in my head every day. Let's just talk about some of the things that are commoditized. I write x and y sets of code when I'm given a spec and I deliver that code. I refactoring code or writing code from scratch even really given if you have a really strong specification and my job is to go write the code. I don't think that anyone's gonna deny that's become far less valuable. I think that's just easier to do with the tools that are out now. 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 planning these sprints in a way that is very effective. You're able to wrap up a project that would've taken eight sprints in 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 powerful. I think there's gonna be this 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 gonna be valuable. Another one is architecture probably.

[00:06:03] Mustansir Saifuddin: I think this is a good segue into architecture and all that because that's where the real value comes in when you are looking at these projects and how they get stood up and then get implemented. The whole nine yards, it all depends on overall set up and the design.

[00:06:18] And of course, the architecture piece is one of the important component of this conversation. You mentioned, how do you shape up your projects, especially when you are 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

[00:06:40] 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.

[00:06:58] Or your developers are taking the help of the AI tools available at their disposal. How do you take this conversation into into an architecture perspective? What's your take on that of an overall design?

[00:07:12] Shashank Paritala: 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 a consultant that really knows all of those, your stakeholders, what your 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 wanna be on. This is probably how you wanna [00:08:00] structure your data warehouse data lakehouse 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 would say that's probably the way you are an ideal consultant is you know so much about that customer that you're able to give that feedback. And also maybe you know that customer, but you also know that industry. All of that comes into play when, I guess we can just call it instinct and judgment business context, all of

[00:08:35] those, super valueable before you even clicking the go button and building something.

[00:08:42] Mustansir Saifuddin: I think it makes sense because especially, like you said, the whole laying the foundation is the key to having a good 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?

[00:08:58] When we talk about enterprise applications in this AI first, world, everybody's 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?

[00:09:15] Especially, let's bring it back to data and 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.

[00:09:28] What happens in this AI first world?

[00:09:33] Shashank Paritala: First off, I think part of what you're talking about is probably security and what's happening on that context, 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 there, that's probably the biggest reason that people need to get going on these tools and getting them deployed, and applications deployed. 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 dejavu of, because I think it's being led. Fomo, et cetera. An example of how I'm seeing AI solutions be deployed is here's a bot that you can feed some input into.

[00:10:20] We have a contract with open AI 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 in and you kind of use enterprise data, make these generative AI applications.

[00:10:36] What I'm seeing is a lot of point solutions. Okay. I'm seeing things be built like we wanted a generative AI app for this specific thing and we're gonna 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 or so difficult, right? Because they're worried about other stuff. Now they're just on calls, two directors, VPs, everyone's sitting on call, fully engaged.

[00:11:38] So I think people are trying to do things, and I think this is a moment of thinking, how can we build these systems so that you don't have these context silos, data silos, et cetera. Which is a conversation I've had with some customers, but other ones that moving faster and just building point solutions.

[00:11:54] Mustansir Saifuddin: That's a great way to look at it. It has to be context driven and the context sometimes can be so narrow [00:12:00] that you forget about the larger impact of that. And I think that you hit on the head on with this one, like folks who are trying to run faster, which is what everybody is trying to do right now.

[00:12:10] Do not forget that, hey, if you don't have the right context, 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.

[00:12:24] I know you worked 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 world?

[00:12:41] Shashank Paritala: 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 are able to just get rid of the ambiguity. And I think if there was 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 to have a 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, 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.

[00:13:30] And obviously you're always gonna 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'm just gonna talk about, these are arduous journeys.

[00:13:46] There's so much ambiguity, you start with this blurry idea that's not the same in everyone's head. Then you are 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 of and helping the customer make these decisions before you click the go button. 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. I threw 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.

[00:14:23] Mustansir Saifuddin: I think that's the real value add like you said. This is where the customers get the most value. Take out that unknowns upfront 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

[00:14:38] 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

[00:14:50] to leave with our listeners?

[00:14:54] Shashank Paritala: 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 gonna change, right? I think we are probably the industry where we unfortunately sold hours. That's the thing that's being hit.

[00:15:12] 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 creation of things that you build that are proprietary to you and you can deploy to help customers and customers will find value in it. A lot of consulting companies. If you really think about the modes that they have, it's really nothing, right?

[00:15:37] It's either you're really large and you have a bench, which is a great mode or was a great mode, and then number two, you have a bunch of slideware that speaks about methodologies, which are just derived from a agile or whatever. Reality is now there's a real way to build things that are gonna be valuable to customers and have that be your thing, your mode, you go in [00:16:00] and you help a customer and you serve a customer. So I think as consultant, think about the things you're doing at customers and see what you can build, I'm just figuring it out myself right now.

[00:16:09] Mustansir Saifuddin: 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.

[00:16:32] 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 you can do those things. I think that, that was a great way to sum this conversation up.

[00:16:51] I really appreciate your time. Thank you for coming on and look forward to seeing you again.

[00:16:57] 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.

[00:17:29] 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.

[00:17:50] And schedule a free consultation. Visit isolutionpartners.com and don't forget to subscribe to our YouTube channel so you never miss an episode. Details are in the show notes.