ChatGPT, an example of generative AI, can produce various types of content, including audio, imagery, text and synthetic data. The recent buzz around generative AI has been driven by the simplicity of new user interfaces for creating high-quality graphics, videos and text in a matter of seconds.
But the panellists at Business Standard said that this could well be an opportunity when it comes to job creation.
“Today, I can produce photos and paintings using Midjourney (an AI programme and service) that are so real and it is amazing. That is fed from real paintings and photographs. If you want to have that kind of data to have true Indian faces, that is an opportunity. Then, there are the opportunities related to high-end algorithms as well.”
“It opens up a plethora of opportunities for all of us to build applications just by using conversations with the system,” said Jain. He added, “Earlier, you had to be properly trained and have the right skills. That barrier would wane off as more and more generative AI models come to the fore.”
This is because there are issues like copyright, trust and privacy that need to be addressed.
“Then, there are other parameters about how safe and trusted it is going to be and how transformative it is going to be,” said Pargaonkar.
“At this point, I would say it is still a question mark and that would evolve over the next six months and beyond,” said Gupta.
“4G is a good example. Each one of them has sprouted a new business model, which would not have existed in the absence of such technologies. Ride-hailing apps like Uber and Ola would not have been there without 4G and Cloud together. So, there is a huge generative AI opportunity, but if you ask us to pinpoint where exactly that opportunity is, we don’t know that. And, that is the fun part of it and it is unexplored. That excites all of us.”
Overall, to implement AI technology among enterprises, Gupta of Dell said the biggest challenge is data, which one has to create, protect and govern.
Jain said there are challenges even inside the organisations to share the data with software development and operations teams, due to concerns around data privacy and information security. “The biggest challenge is how do you gather that data and curate it,” said Jain.
Katragadda said that his AI firm wanted to work 100 per cent for Indian customers and did 80 per cent of the proof of concept for them.
However, awareness about technologies such as AI and the importance of data and changing processes are growing inside organisations.
Ramaswamy said, on another end of the spectrum, there are manufacturing and retail sectors, which are not highly regulated compared to banking.
However, there are challenges related to the democratisation of high-end technologies such as AI and Cloud by large tech companies and making them accessible to small businesses.
He said that tech firms are making efforts to reach out to small businesses and are even creating plug-and-play products and solutions, which are relevant to them.
He said to democratise technology at the grass-roots level, there is a need to build an ecosystem.
IBM is already doing this. Ramaswamy said there is a client engineering unit inside IBM, which actually takes up the business problem of a client and solves it.
Mazumder said there is a hunger within smaller organisations to leverage technology.
He said TCS is scaling up in industries like e-commerce, especially vendors working with firms such as Amazon and Flipkart. However, there is a gap in industries like manufacturing for technologies and that is a huge opportunity.