EXL’s Journey from Capabilities to Rapid Solutions in the Gen AI Era with Deepti Kalra

In this exclusive interview with AIM Media House, we sit down with Deepti Kalra, an AI leader with 14 years of experience in establishing and scaling AI practices including strategy, product development, and consulting. Deepti, the Vice President and Chief to the CEO currently driving data and AI-led vision for the company, previously led AI solutions for Insurance Analytics practice at EXL. She has been instrumental in developing industry-leading AI solutions and strengthening market positioning with external stakeholders. Her extensive experience spans across insurance, financial services, media, and healthcare sectors, where she has focused on solving key industry problems and leading large-scale transformation programs for Fortune 500 organizations.

Deepti shares her insights on the evolution of EXL from focusing on capabilities to becoming a solutions company, the impact of Gen AI on service demand, and the journey of building a robust data and AI practice. She discusses the pivotal role of data management, the importance of domain knowledge in AI implementations, and the strategies for talent acquisition and technology partnerships that have driven EXL’s success. Deepti also highlights the leadership qualities that inspire her and the emerging trends that will shape EXL’s future in the AI era.

AIM Media House: Can you describe the evolution of your company from focusing on capabilities to becoming a solutions company, and how the advent of Gen AI has influenced the demand for your services?

“We are seeing a rapid change in the demand for our services focused on engineering and faster outcomes. Clients now expect us to deliver outcomes and value in  weeks, rather than months.”

Deepti Kalra: It has been a wonderful roller coaster ride for sure. Since I joined, there have been numerous experiences that I can count on. I have seen the company evolve from focusing on core capabilities to delivering comprehensive solutions. i.e. addressing specific client needs more effectively and driving greater value and building repeatable assets to deliver value to clients quickly. Now, with the advent of Gen AI, We are seeing demand for data management and engineering surge. Clients now expect us to deliver outcomes in just a few days or weeks, rather than months. This evolution is something I have witnessed firsthand, and I continue to learn every day. 

AIM Media House: When did you first establish the data team at EXL and how long did it take to grow the team to 10,000 members?

“We kept expanding that practice significantly across different verticals.”

Deepti Kalra: Back in 2006, we acquired a company called Inductis. That’s when we started our data analytics practice. We kept expanding that practice significantly across different verticals – insurance,  banking, retail, and CPG, covering all industry verticals with our analytics practice. In 2015-16, we set up our digital team, consisting of specialized engineers focusing on embedding digital & AI into operations. This digital team, together with our data analytics practice, has grown exponentially over the years, now reaching over 10,000 plus members.

AIM Media House: You’ve been integral to EXL’s rapid growth and pivot to becoming an AI-first organization, working closely with the CEO. Can you share how this conversation started, the leadership’s thought process, and the key boardroom discussions that led to this decision?

“With the advent of Gen AI, we recognized a new segment, the AI services segment, which significantly increased our target addressable market by threefold—from $350 billion to $950 billion.”

Deepti Kalra: We have a history of making strategic business pivots ahead of time. Long back, we realized that data is absolutely critical. While we had a data analytics practice, we understood that without a solid foundation of data and proper data management practices, implementing any technologies and integrating them into workflows to achieve desired outcomes would be impossible. 

In 2021,we pivoted from being a digital organization to becoming a data-led organization. Of course, we had been implementing AI solutions, but data became the core of everything we were doing. We ensured that we had our foundational data management practice  set up.

With the advent of Gen AI, we recognized a new segment, the AI services segment, which significantly increased our target addressable market by threefold—from $350 billion to $950 billion. We had strategic conversations and realized well that we are uniquely positioned to capitalize on this expanded market due to our strong data capabilities, industry processes knowledge, and data ontologies derived from our domain experience. By combining our data expertise and domain knowledge with AI algorithms, we could deliver much more tangible value to our clients. This realization necessitated our shift to being a data and AI-led organization.

AIM Media House: Can you explain what data ontology is and why it uniquely positions your organization in the AI era? How has being a data-led organization helped you build robust AI practices and adapt to decentralized AI implementations?

“If you have a great understanding of data ontologies and processes, such as the claims process, you can significantly enhance the quality of AI outputs.”

Deepti Kalra: Let’s understand what has changed in this AI era for a minute. The definition of business transformation has evolved. Now, businesses are adopting AI by embedding AI-powered applications and solutions directly into their workflows via APIs without having to redesign the tech platform first. This leads to decentralized rather than centralized transformation. With decentralized transformation, AI implementations are happening more frequently, allowing organizations and businesses to launch solutions much faster than ever before.

Understanding the domain and processes has become more critical for AI algorithms to produce high-quality outputs. If you have a great understanding of processes, such as the claims process, you can significantly enhance the quality, accuracy and latency of AI outputs. For example in a claims adjudication process, data ontologies include information related to diagnosis, prior loss histories, , provider details and more. The relevant loss Embedding this contextual knowledge and data relationships into AI algorithms, enhances AI outputs significantly.

The second critical aspect is our ability to manage data modernization and management at scale and speed. We are uniquely positioned because we have been focusing on scaling data management practice for the last few years. We understand that if your data is not properly managed, you cannot deliver efficient outputs. Our ability to combine domain, process, and industry knowledge with the right data management and cloud modernization practices, and integrate it with the right AI algorithms, helps organizations in this decentralized AI implementation era.

This combination not only ensures higher quality outputs but also optimizes costs and reduces latency. These are important considerations, as organizations today must balance the trade-offs between quality output and optimized computing costs, which can sometimes be difficult to manage.

AIM Media House: How did you enable the necessary pivots in processes, technology partnerships, and talent acquisition as an organization, and what was your role in this transformation while working closely with the CEO?

“What we have realized for a services company like ours is that there are two types of talent; those who work with AI and those who work on AI.”

Deepti Kalra: There are a lot of changes and pivots that we, as an organization, are making, and I’ll start with the talent aspect. What we have realized for a services company like ours is that there are two types of talent; those who work with AI and those who work on AI. We need very different strategies for both types of talent.

For people who work with AI, we must ensure they have the right training and sandbox environments to experiment with AI technology, build solutions at scale and speed, and stay at the forefront of technological innovation. For those who work on AI, we need a different strategy to ensure they have the necessary training to work on various AI systems we will be building. Therefore, we are developing two types of training programs and different strategies for both types of talent.

Regarding technology, one thing we have realized is that we cannot rest on our laurels. While our unique position of combining domain expertise, data, and AI gives us a competitive edge, the pace at which technology is evolving requires us to continually innovate. We must ensure that we are partnering with the best in the industry. We’re partnering with Nvidia, and are also partnering with hyperscalers like Amazon, Microsoft, and Google, as well as data platforms like Databricks and more.

Our thinking is that we should do whatever enables us to deliver outcomes for clients at scale and speed. We are trying to bring in all the best practices and collective strengths of these companies to embed AI into clients’ processes.

AIM Media House: How do you translate collaboration among leaders into actionable strategies for data teams at all levels? Can you share your experience and journey working with the CEO and other leaders at EXL?

“Working with the leadership has been amazing, ensuring that we stay ahead of the industry and that this forward-thinking approach permeates every level of the organization.”

Deepti Kalra: Working with Rohit has been amazing. He’s an amazing leader to work with. You won’t miss a moment of learning something new when you’re with him. This also means there is a lot of continuity.  However, what I really like about working with the leadership at EXL is that we continually strive to stay ahead of market and industry trends.

During COVID, while we were focused on navigating the crisis, we were also thinking about the next evolution or how this is going to shape our industry in future. We realized that investing in data was crucial. Similarly, we started investing in AI a long time ago, and now, with the advent of Gen AI, we have seen integration of data & AI together is must for it to deliver meaningful value. 

Working with the leadership has been amazing, ensuring that we stay ahead of the industry and that this forward-thinking approach permeates at every level of the organization. Everyone understands the importance of embracing AI. For example, we implemented couple of Gens AI applications within our organization. One of the application’s application allows employees to ask questions about say  travel policy or bonus policy and receive immediate responses. In the last few  months, we have not only developed and implemented this solution but are also working to scale it. Among our 55,000+ employees, we want everyone to use it, not just a limited few.

This excitement and passion from the CEO and top leadership ultimately reaches every individual in the organization. This energy excites me and is one reason I have been associated with the organization for so long. I see that passion reflected in every employee at EXL.

AIM Media House: What qualities do you observe in leaders like Rohit Kapoor, Vivek Jetley and others at your organization that inspire you? How do these qualities influence your own career growth?

“Passion leaders have for their work.”

Deepti Kalra: I would say that decision-making is something I learn and refine every day. Ensuring that collective decisions made with executive leadership  are effectively communicated and executed by middle management and every employee in the organization. This is a priceless learning of making and implementing decisions, and seeing those to fruition. 

Another thing I truly admire is the passion leaders have for their work. For example, Rohit is incredibly passionate about scaling this organization to new heights. Every day, he’s thinking of new ways to take EXLto the next level. Vivek, too, has been wonderful to work with. He has taught me a lot about staying ahead of the technology curve and keeping up with industry trends. We are ensuring that we are keeping pace and continually innovating with these changes.

Additionally, I’ve had a similar experience working with Andy Logani, our Chief Digital Officer; his approach and insights have been invaluable in this regard.


AIM Media House: What emerging trends do you believe will define EXL’s journey in the coming years, considering the rapid advancements in technology and the growing enthusiasm from both enterprises and countries to build on this ecosystem?

“AI is going to reframe the game of the services industry—no second thoughts on that.”

Deepti Kalra: First of all, in my view, AI is going to reframe the game of the services industry—no second thoughts on that. This is definitely true; we are seeing that AI is transformative in traditional services driving efficiencies, and enhancing customer experience.

I’ll give you one example of customer experience. Previously, a customer-facing agent would have to scan through all the documents to answer a customer on a call and would not have information about the customer’s prior history. Today, that same agent is armed with real-time intelligence about the customer’s history, previous call transcripts, lifestyle traits from external data, behavioral aspects, and demographics. They can perform sentiment monitoring during the call, provide proactive nudges, and offer personalized recommendations to the customer.

Things are changing not only in the customer experience space but also in improving productivity and the experience of our colleagues. For example, in regulated industries like banking, developers used to help with the conversion from SAS to Python. Now, we have solutions for automated code conversions, automated testing documentation, and metadata management, streamlining the processes.

Emerging AI trends are disrupting and changing the demand for our services. The demand for our services has shifted from FTEs to solution-led; changing our growth model. Client solutions include providing specialized resources with data & engineering skillset, scaling their AI COEs and deploying   our IP and solutions on clients tech stack_ to accelerate value to them. This shift is something we are definitely seeing.