According to research studies published by Indian IT businesses, implementing generative artificial intelligence presents a number of privacy, security, and usability problems.

Major barriers to the adoption of AI

In  an Infosys study, about half of the participants identified data difficulties as the main barrier to the application of generative AI. According to the study, using generative AI that relies on public data carries significant inherent risks, including hallucination and intellectual property infringement. Because of this, a lot of companies want to develop tools unique to their company that are trained on internal rather than external data.

When artificial intelligence models provide false or misleading information, it is a phenomenon known as hallucinations.

Insufficient data to monitor progress

Similar tendencies have also been observed by other IT organisations. According to a survey by LTIMindtree, the primary challenge to the adoption of Gen AI was identified by 78% of respondents in the UK and Continental Europe as problems with data availability or quality.

 The report said, Enterprises that have not yet started their Gen AI journey face significant obstacles, such as operational costs, data availability and quality issues, and the requirement for accurate use case identification.

“A staggering 79 percent of leaders cite ethical, security, or regulatory issues as barriers to the successful adoption or scaling of Gen AI, while 78 percent identify a lack of suitable skills, expertise, or knowledge as their greatest challenge,” it added.

Concerns relating to accuracy and privacy

According to the study, adoption of Gen AI is now delayed by concerns over accuracy and privacy, particularly in sectors like healthcare.

The survey stated that despite the healthcare industry's considerable use of new technologies like big data, machine learning, and artificial intelligence, only 9% of Gen AI leaders are located in this sector.

Regulatory barriers

Furthermore, the study noted that regulatory barriers also exist for the adoption of innovative technology.

“Regulatory barriers, concerns over the safeguarding of sensitive patient information, and the complexity of health data contribute to the cautious adoption of Gen AI in healthcare,” the study explained.

Similarly, the banking and finance sector, another highly regulated industry, made only 17 per cent of Gen AI adopters in the same survey.