Artificial intelligence (AI) was perceived to deliver increased outcomes when combined with analytics at 37 per cent followed by Internet of Things (IoT) and Cloud Technologies at 19 per cent and 16 per cent respectively, Infosys said in a statement.
The study found 31 per cent of respondents identified the use of data analytics with experience enhancement.
This includes using intelligence generated by listening to internal and external stakeholders to drive extreme personalisation and high quality customer service, the statement said.
As many as 28 per cent respondents were interested in leveraging analytics for risk mitigation -- predicting risk to enable better decision making, and detecting anomalies that could disrupt business effectiveness.
In the study, developing new business models by unearthing the hidden needs of customers and offering innovative products and services was seen as the primary analytics requirement of 23 per cent of respondents.
Revenue and profit maximisation through increasing channel effectiveness and enhancing profitability across processes, channels and stakeholder ecosystems was the analytics priority of 18 per cent respondents.
The majority of respondents in the US (32 per cent) and Europe (34 per cent) stated they would like to use analytics for experience enhancement whereas in Australia and New Zealand about 31 per cent respondents consider it for risk mitigation.
Finance and accounting was found to use analytics the most at 32 per cent, followed by marketing and operations at 20 per cent and 17 per cent respectively.
"We believe that the findings of this survey will help our clients to fast-track their journey into a data-native enterprise by industrialising their analytics capabilities and ultimately monetise data," said Satish HC, Executive Vice President and Head Data and Analytics, Infosys.
The survey found that enterprises in every industry encountered several challenges that prevented them from implementing their analytics initiatives fully.
The biggest challenges stemmed from a lack of expertise in integrating multiple datasets (44 per cent of respondents) and failure of understanding in deploying the right analysis techniques (43 per cent).
This is where enterprises are looking up to their partners to help industrialise their analytics capabilities by creating an analytics strategy, build an operational framework, and define a process for executing and governing analytics initiatives.
"In the world of endless possibilities that data provides, being data native is core for enterprises to being digital," said Satish.
"As enterprises work with limitations of siloed systems, data integration issues, resources and skills, harnessing the possibilities with data will be essential to navigating their next," he said.
(This story has not been edited by Business Standard staff and is auto-generated from a syndicated feed.)