New Delhi:

Companies can generate $460 billion in incremental profit if they improve data practices, trust in advanced artificial intelligence (AI) and integrate AI with business operations, according to new research by Infosys.

Satish H C, executive vice-president, and co-head, Delivery, Infosys, said: “Companies that don’t trust their data risk a vicious cycle of ‘pilot purgatory’ and only use data and AI to solve small problems. Data management combined with trust in AI are the dual solutions to increase business capability and financial rewards”.

The financial services industry has the strongest satisfaction with data and AI uses, followed by retail and hospitality, healthcare, and high-tech, according to the study by Infosys Knowledge Institute, thought leadership and research arm of the company.

The research found that 81 per cent of respondents had deployed their first AI system in the past four years.

Most companies (85 per cent), however, have not achieved advanced capabilities, and most AI models (63 per cent) are still driven by humans. “Compounding this, outcomes are middling at best: users are highly satisfied with their data and AI results only about a quarter of the time,” the report, titled ‘Making AI Real: From Data Science to Practical Business,” said.

Infosys Knowledge Institute surveyed 2,500 AI practitioners for the study.

Businesses can no longer think of their data as oil that is valuable when refined. Data today is more like currency, and it gains value when it circulates, the research noted: “In our study, companies that shared data in and out of their organisation were more likely to have higher revenue and use AI better.”

Although three out of four companies want to operate AI across their companies, most businesses are new to AI and face daunting challenges to scale.

The study found that 81 percent of respondents deployed their first true AI system in only the past four years and 50 per cent in the last two years.

It also said that 63 per cent of AI models function only at basic capability. They are driven by humans, and often fall short on data verification, data practices, and data strategies.

“Only 26% of practitioners are highly satisfied with their data and AI tools. Despite the siren song of AI, something is clearly missing,” the research said.