Artificial Intelligence's Foothold in Today's Industries
Rajsekhar Aikat is the Chief Technology & Product Officer at iMerit. Raj has over 18 years of technical & product experience across multiple verticals, including automotive, IoT, robotics, and telecom. Rajsekhar joined iMerit from Qualcomm, where he was Senior Director of Product Management. Before Qualcomm, he was the Director of Product at Brain Corporation, where he was responsible for scaling BrainOSTM, an autonomous mobile robot platform & ecosystem, as well as overseeing the development and commercialization of commercial cleaning and delivery robots globally.
Insights on AI and Big Data
The AI industry has matured significantly, not just in India but globally. The problem statement has moved from AI research and training neural networks and deploying and influencing that to a data problem. There are lots of analysts giving multiple different numbers; at least for India, the Mass communication data published by the industry will get about 7 billion US dollars by 2030. There are a couple of things happening with data. What we have yet to touch today is the tip of the iceberg. From a neural network perspective, it is perfect accuracy. However, from a part of human society, it is entirely unacceptable. But there are other different technology pieces. So, it provides a whole suite of tools for different use cases. In some places, accuracy is critical. Depending on that, we are leveraging the tools and AI analysis once.
AI Scope in India
India is one of the top five leading markets, one from NASSCOM that granted you an SOE in India and was released a few months ago. India has primarily followed the previous path of incorporating AI into consumer items. In other words, a significant quantity of money has been invested. But it already has a multibillion-dollar industry. It will expand at a CAGR of 35 to 40% during the following five to ten years, even if it exceeds that by order of magnitude. If you saw AI, it's entering the large-scale law market where India has many humans today. So, if you go into consumer verticals, you quickly get hundreds of millions of consumers in their everyday lives. It is creating this vast data at scale. The Indian ecosystem is trying to cater to that. And that is maturing the AI industry in India much faster than the big hubs we discussed, but it is China and the US. If the enterprise is what the consumer wants, India is moving much quicker than the US at scale. There are some tools we are using in data generation. So, what is the market of those tools you are thinking of soon in India.
Expectations on the Marketplace
According to market research reports, the market is already about a billion dollars for data annotation tools. So that market is already existing. The problem these tool companies will face is how to make these tools provide an end-to-end customized solution because the market is moving fast toward generic tools. That's where technology comes into play because giving a human the means to draw polygons and other things like time rotation is no longer adequate. These amputation companies will have to think about how to provide end-to-end customized solutions. Technology is the tool We are tools agnostic and a platform where you can quickly add tools from other companies. For example, if a client says, "We have worked with these two companies; please use the flow we have built according to it; please use that tool; we are going to do it," we can quickly add that tool to the platform. But the tool most differentiated for us is number one; the tools that help you track the productivity of human intelligence shall be visualized in different ways. So, our education ticketing and analysis platform that we do internally, providing insights to the client and helping the client create virtual test cases simulation cases.
Expectations from India in terms of Business and Clientele
One is that we have begun to enter the consumer realm as our tools and approaches advance. India is primarily a consumer market, whereas China was an enterprise first, entering low volume, high revenue, and high profitability markets before moving into the latter. The reason why we observe that. You want to test it out on people with a more significant pain threshold or sophisticated clients in corporate industries like autonomous vehicles or medical AI. As a result, we have already started communicating with a few clients in South Asia and India. On the other hand, we have business enterprise companies in this area that have embraced AI ML. Additionally, we have already begun working on significant projects with government and non-government organizations. Therefore, it is true that India's market currently generates less revenue than the North American market. India is undoubtedly an increasing market, and we need to scale nonlinearly; it has become increasingly crucial.
Taking Advantage of AI to Ease Tasks
AI acts as a second set of eyes. And if you think about it that way, it does not replace human consciousness or people; rather, it helps them be more productive or freeze them up from risky, boring, and dirty tasks. So, right now, before we go to the future, conferencing is the first of the three domains where businesses employ AI most frequently. That has grown to be a huge issue. Since everyone has become more distant over the past two or three years, mostly due to COVID exactly. However, we have adapted to be a more remote civilization. AI acts as a second set of eyes. And if you think about it that way, it does not replace people; instead, it helps them be more productive or freezes them up from risky, tedious, and dirty tasks. So, before we go to the future, conferencing is the first of the three domains where businesses employ AI most frequently and has grown to be a huge issue. Everyone has become more distant over the past two or three years, primarily due to COVID precisely. However, we have adapted to be a more remote civilization.
The Role of AI in Business
Almost every department begins with a different department as a client. Every time the second department leaves, the third department appears and approaches us about how data operations and ML operations might help them increase their output or their ability to generate revenue. For instance, if we visit an e-commerce website and want to make a purchase, we see suggestions for that item. These are once more highly repetitive duties. Furthermore, if you had a tool, it might be based on deterministic analytics or artificial intelligence. Thus, the world is developing in these ways. However, I can think of many other applications, such as sales leads and skill matching. It would be a fantastic platform for AI believers, application engineers, and other people interested in the AI sector in India because it is likely one of the largest conferences with a strong data ops focus.