India, meanwhile, is late to the game, and will probably not dominate in the field except in a few areas, experts said.
IDC’s Sharma said the country needs to resolve some issues first: “India stands a chance to compete at a global level, provided the hurdles are overcome.” Challenges, she said, include poor data quality and integrity, as well as a lack of expertise.
Those critiques would not be news to New Delhi.
“The most important challenge in India is to collect, validate … distribute AI-relevant data and making it accessible to organizations, people and systems without compromising privacy and ethics. Data is the bedrock of AI systems and reliability of AI systems depends primarily on quality and quantity of the data,” the government report said.
Milan Sheth, a partner at EY covering intelligent automation, added: “There is a need to reskill a large number of people in a short span of time. It will take a couple of years, but tech developments will also take that same amount of time. To keep pace with adoption, that is the challenge.”
While India is unlikely to be able to fully compete anytime soon, it can still aim to be a leader in a few areas such as industrial electronics, Sheth said.
“It will make a bid for dominating in a few areas but can’t compete with the U.S. or China on academic investment,” he said, adding that very few companies in India are getting sufficient funding for research.
India’s GDP could reach $6 trillion in 2027 because of its digitization drive, according to a previous forecast by Morgan Stanley. That would make India the third-largest economy in the world — behind the U.S. and China, which recorded $18.5 trillion and $11.2 trillion in 2016 GDP, respectively.