Lack of skilled researchers, big data plague AI companies: NASSCOM study

Another challenge faced by AI companies is data protection laws in foreign countries. These laws increase their expenses further.
For representational purpose (Express Illustrations)
For representational purpose (Express Illustrations)

HYDERABAD: Dearth of high-skilled researchers in the field of Artificial Intelligence, lack of big data is proving to be a challenge for companies in this field, according to findings of a NASSCOM study done on 13 AI companies, which includes some from Hyderabad.

The study which was done as part of its larger report called the ‘Implications of AI on the Indian Economy,’ analysed 13 AI companies and its total workforce. While there were three companies from Hyderabad, there were many from Bengaluru, Chennai and other cities.

“Most of the companies which constituted our case studies noted that AI ecosystem in India requires high-skilled researchers and those with experience in the field of AI. Several companies also noted the need for a greater provision of graduate level courses in applied AI,” the study said.

Another challenge faced by AI companies is data protection laws in foreign countries. These laws increase their expenses further.

“The emergence of data privacy and data protection regulations, most prominently the European General Data Protection Regulation (GDPR), may lead to additional costs and constraints in the production of data-intensive solutions,” it added.

In the data sphere, the other major problem is that of collecting data, which is a necessity for AI firms as data is needed in troves to train algorithms. “Several firms reported the challenge of collecting data, particularly those firms whose solutions rely on problems of the social sector and which depend on publicly available data,” it said before pointing out the problem Vassar Labs, a Hyderabad-based AI firm, was facing in this area.

“In response to data scarcity, Vassar Labs, which provides last-mile decision support for governance structures and agriculture, reported deploying sensors and generating their own data to train their algorithms,” the case study said.

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