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Over 80% of our AI agents are built in India, says SAP Labs India MD

Sindhu Gangadharan says AI-led productivity gains, strong GCC growth and responsible deployment will shape the next phase of India's tech industry

Nasscom chairperson Sindhu Gangadharan
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Sindhu Gangadharan – managing director (MD) of SAP Labs India and Nasscom chairperson

Avik Das Bengaluru

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SAP Labs India, the research arm of German software company SAP, says its artificial intelligence (AI) co-pilots are helping drive productivity across enterprises and a significant number of those agents are built in India. In an interaction with Avik Das in Bengaluru, Sindhu Gangadharan – managing director (MD) of SAP Labs India and Nasscom chairperson – talks about the agents and on whether the recent frenzy over AI is a bubble or not, among other issues. Edited excerpts:
 
Do you think India’s technology industry will be able to touch the $300 billion mark as projected at the start of the financial year? Also, what could be the potential changes in the business process management (BPM) industry in 2026?
 
We hope to reach it but there is a slowdown in services as we observe. Given the larger geopolitical aspects and the global realignments that have happened, the target looks a bit uncertain. However, the slowdown will be complemented by the global capability centres (GCCs) and the engineering research and development (ER&D) sectors. I think there will be significant consolidation in the BPM industry because there is no bypassing the wave of AI. That means getting the industry up-skilled on AI is definitely a huge focus. The more we have people upskilled on AI, the projects we'll be able to cover are only going to be better. As we build out products, it is finally the business process outsourcing (BPOs) that have to put that into actual usage. So, upskilling will close the gap.
 
Do you think the adoption of AI at the enterprise level has gone up in the last 12 months and how do you see that evolving next year?
 
For SAP Labs, what we do is focused interventions for our customers and also embed AI across our lines of business. When we look into the success stories where customers are successful, it is where they also have a good understanding of their data because AI is only as intelligent as the data. And, this is also when we are able to look at data sets and train our models on well-defined data sets so that it goes hand in hand in successful AI projects.
 
There was a target to improve productivity gains for clients to 40 per cent from 20 per cent. How has the progress been?
 
It goes across multiple fronts, so for example, both on the customer side and the developer side. That is where our solutions like Joule for developers and consultants come in handy. For example, in Joule for consultants, we have trained the AI co-pilot with over 300,000 articles. This is to really make sure that as you are in a consulting project you're able to guide the customer to the right actions depending on what is the scope of the work which drives up productivity. Also, our target this year was the number of agents that we have across our portfolio which adds to our productivity gains. While Joule is the super-agent today, we have more than 100 agents across the portfolio, compared to just 20 a year ago. And, 80 per cent of those are coming out of India and we are looking at agents not just as digital assistants but virtual co-workers.
 
Are companies justified to spend billions of dollars on AI and superintelligence? Is there an AI bubble round the corner just like the dot com boom?
 
This is different because of the pace at which things are happening. It again goes back to our focus on the trust that we have gained with our customers. And, we've always talked about the three Rs; reliable AI, relevant to the business, and most importantly responsible AI. So, I don't see this as a bubble as the technology is real, it's happening. And, it's quite powerful when you have the right data sets. Hence, I would caution that we as nations and organisations need to be clear on how we use it in the right way. We can debate on the billions of dollars that are being spent on the hardware but this is not equivalent to the dot-com boom. This is because we are seeing things in action as we speak. What took several months is now happening in minutes. So, that's the pace of transformation we are seeing in certain use cases like drug discovery.