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ZINNOV PODCAST   |   Business Resilience

Harnessing AI For Transformative Tech Solutions

Vijay Guntur & Pari Natarajan
Vijay Guntur Chief Technology Officer (CTO) and Head - Ecosystems & Practices HCLTech
Pari Natarajan CEO Zinnov

In this insightful episode of the Zinnov Podcast Business Resilience Series, Pari Natarajan, CEO of Zinnov, and Vijay Guntur, Chief Technology Officer (CTO) and Head – Ecosystems & Practices at HCL Technologies, explore the transformative impact of AI on the engineering landscape. The conversation delves into how AI is reshaping various sectors and driving innovation across industries.

Key highlights:
• The importance of ecosystem partnerships in the AI era
• Real-world use cases of AI in e-Commerce, Healthcare, and Software Engineering
• Innovative approaches to talent development and the future of AI literacy

This episode offers valuable insights for tech leaders, innovators, and anyone interested in understanding how AI is revolutionizing engineering and business processes. Discover how companies are navigating the AI revolution, simplifying complexity for customers, and preparing the workforce of tomorrow.


Timestamps

00:00Intro
01:32Opportunities for Service Providers in Generative AI
04:51What are some customer use cases that you cater to?
10:15The future of tech services
12:00Partnering across layers, amidst innovation
15:45Managing Talent across geographies

PODCAST SUMMARY

Pari: Welcome to a new episode of the Zinnov Podcast, Business Resilience Series. I’m Pari Natarajan, CEO of Zinnov. Engineering is undergoing a major shift with the rapid rise of artificial intelligence. Generative AI is set to become the new normal, revolutionizing collaboration, optimizing workflows, and boosting productivity. This isn’t just speculation—75% of over 250 patents filed since 2021 have already been granted, signalling a fast shift towards AI-driven collaboration.
Today, we’ll explore the intersection of AI and engineering and how it’s transforming industries. Our guest is Vijay Guntur, CTO and Head of Ecosystems at HCL Technologies. Congratulations, Vijay, on your new role. Vijay now leads next-gen technologies, including Gen AI, data engineering, and cloud, while driving innovation with ecosystem partners like hyperscalers, tech OEMs, and semiconductor companies. Welcome, Vijay.

Vijay: Hi Pari, thank you for having me. Glad to be back and excited to talk with you and your audience.

Pari: Let’s dive in. With nearly 35 years in R&D, you’ve seen major technology shifts, especially in software development. Generative AI is revolutionizing businesses with benefits like efficiency, creativity, and better decision-making. What opportunities do you see for a tech services provider like HCL Tech as generative AI becomes more widespread?

Vijay: The opportunity is unprecedented, with an impact estimated at $2 trillion, possibly up to USD 4 Trillion in the next few years. We’re already seeing firms excelling by leveraging this technology, and HCL Tech has extensive capabilities across the generative AI stack.
The stack spans from innovations in semiconductors, where firms like NVIDIA, Intel, and AMD are leading, to tech OEMs and hyperscalers building the infrastructure. We see massive opportunities there, and we’re doing significant work at both the semiconductor and data center levels. Once the infrastructure is in place, data readiness is key, and our partnerships and AI Foundry are focused on this.

Beyond that, we have opportunities in fine-tuning LLMs, SLMs, and building applications. With our expertise in engineering, data, and digital services, we’re positioned to capitalize across the entire stack. Additionally, business transformation is a major focus—our BPO services are reimagining customer experiences. This wave could surpass the digital engineering and transformation we’ve seen over the past decade.

Pari: Interesting. HCL has always been known for strong infrastructure, semiconductor, and embedded software capabilities, along with a robust BPO business. It seems like there are opportunities across these areas. While these are service lines, customers are focused on solutions and use cases. They aren’t just asking for a chip; they want to know how it will boost productivity, reduce risk, or create new revenue. What are some of the key use cases where customers are seeking help?

Vijay: While some customers are indeed asking us to build chips, that’s just a small portion, mostly in the tech sector. For end enterprises, the focus is on business outcomes. Let me share a few use cases.
In terms of revenue impact, e-commerce is a key area where we’re seeing growth. With generative AI, content can be automatically generated, and personalization is now down to a “person of one,” greatly improving customer satisfaction and driving revenue across industries like retail, CPG, and travel.

For customer experience, especially in life sciences and healthcare, we’re innovating significantly. For example, we’ve reduced the time patients spend in initial hospital interactions from 45 minutes to just a few minutes using a generative AI engine. This tech is improving scalability and reach, and we see similar applications across service industries where agentic technology enhances the customer journey, resulting in both productivity gains and higher satisfaction.

Finally, for productivity, especially relevant to tech companies, we’ve developed AI Force, a patented solution that enhances the entire software engineering lifecycle—testing, deployment, and maintenance. It goes beyond tools like GitHub Copilot, driving efficiency across our operations and enabling us to deliver faster, better services. This is transformative for us and will create new services, benefiting both us and our customers.

Pari: You mentioned productivity, but there’s also a concern that it could cannibalize overall revenue for the tech services industry. How do you see that playing out?

Vijay: That’s true to some extent. There will be cannibalization, but also growth opportunities. If we don’t act, someone else will, so it’s better to embrace this shift and get to market faster. The goal is to grow the business beyond the initial cannibalization.

Pari: Understood. This shift could also change how services are delivered, with more customers seeking outcome-based offerings. HCL Tech has been a pioneer in this space, taking on risk with customers, which seems like a natural advantage for you, given your business model.

Vijay: Absolutely. We’re already transforming our business towards outcome-based services, where we’re measured and paid based on the results we deliver. Customer satisfaction is a key metric, alongside obvious ones like revenue uplift and productivity gains. We’ve experimented with this model before, but generative AI is driving much more interest now.

Pari: You mentioned various service lines and the innovation happening across the stack—from chips to LLMs to research on what’s next. There’s innovation at every level: semiconductor companies, hyperscalers investing billions, and your customers building their own infrastructure. As a system integrator and engineering provider, how do you bring all of this together? How do you partner across these layers? I’d love to hear your perspective.

Vijay: Partnerships are key. No one company can deliver across the entire value chain, so we collaborate with semiconductor companies like Nvidia, Intel, and AMD, as well as tech OEMs like Dell, IBM, and HP. For instance, in our digital workplace services, there’s growing demand for AI PCs, making these partnerships critical for us to deliver those services effectively.

The proliferation of LLMs, both open-source and proprietary, also requires us to partner and adapt quickly. We collaborate with hyperscalers and companies like Hugging Face to build and adopt this technology. Relationships with domain experts and consulting firms are equally important—they’re at the forefront of business transformation, and we work with them to realize that change.

Lastly, we’ve built strong ties with universities in the U.S., India, and soon Europe, to stay ahead of what’s next in the tech space and contribute to that future. Our ecosystem includes tech OEMs, chip companies, hyperscalers, LLM developers, universities, and strategy firms. We’re also expanding to include startups, which is another area we plan to mature further.

Pari: It seems like HCL Tech acts as a glue, integrating various aspects of the ecosystem to provide what’s relevant to customers, especially since things are evolving so rapidly. Customers may not have the expertise to keep track of everything, but you seem to have stitched together partnerships that help deliver value at the right time. To achieve all this, talent is critical. You have teams across the U.S., Europe, Japan, and India. How is your talent prepared to drive both your transformation and your customers’?

Vijay: Before addressing talent, I want to touch on how we simplify complexity for customers. They care about the value AI can drive and at what price point. To support this, we have generative AI labs—cloud and AI labs—in London, New York, and Noida, with a West Coast lab coming soon. These labs serve as the first point of interface for customers, helping them prioritize based on their readiness, especially around data. We recently launched our AI Foundry solution to help customers prepare their data, as without data, there’s no AI or business benefit. These labs allow customers to experiment and identify key use cases with clear ROI.

Now, on talent: It’s limited in this space, but we’ve faced similar challenges during the digital transformation. Generative AI offers a chance to build new talent pools. We have a TechBee program, where we train college grads in new technologies. We’ve integrated AI and data concepts early into this program, and within a year, participants can contribute to projects. This program is a key pipeline for us to develop talent ready to work with AI.

Looking ahead, I see schools introducing data science and AI concepts at a younger age, which is crucial because AI won’t just be for specialists. Everyone will need to know how to use it, making AI literacy as essential as math. Even basic AI skills like prompt engineering will be necessary, and high school students are already adapting. This skillset will be key for future workers to be more productive and creative in their roles.

Pari: Very interesting. Some people believe that leveraging AI requires advanced experience, but you’re suggesting something counterintuitive. Even high school students or junior engineers can add significant value using AI, provided they’re trained properly. If they understand how to use these tools, they can contribute to greater efficiency and productivity.

Thanks a lot, Vijay. We covered a lot in a short time—how AI is impacting different service lines, how customers are already focusing on mission-critical, revenue-generating, and efficiency-improving use cases, and how you’re simplifying this complex ecosystem through your labs.
You’re helping customers experience AI and innovation in real time by setting up labs close to them and ensuring they can navigate this ever-changing landscape. Additionally, you’re not only preparing your current talent pool but also proactively shaping the next generation of talent.
It’s super exciting to see where this is headed. I’m sure next time we speak, you’ll have made even more progress, and we’ll have more insights to discuss. Thanks again, Vijay.

Vijay: Thank you, Pari, for this opportunity. It’s always great talking to you.

Pari: Stay tuned as we continue to bring you thought-provoking conversations with esteemed industry leaders in our upcoming episodes. Until next time, thank you for joining us. This is Pari Natarajan signing off.

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