India excels in Cloud, AI, and ML: 85% of Indian businesses use Cloud providers

India demonstrates remarkable resilience in the face of a challenging global landscape, according to the World Bank. Robust domestic demand, public infrastructure investments, and the strengthening of the financial sector collectively contribute to India’s performance.

As a testament to this resilience, a staggering 77% of business leaders surveyed maintain a positive outlook for the upcoming year. These findings emerge from a comprehensive study conducted by Forrester Consulting, commissioned by Experian, a global information services leader.

The study also explores the profound impact of AI on analytics, risk assessment, and customer experience. Notably, India demonstrates impressive AI and Machine Learning (ML), adoption rates, reaching 49% in customer service and 40% in identity verification.

The study highlights India’s leadership in the EMEA and APAC regions, with 85% of surveyed Indian businesses using external cloud providers for analytics. India’s adoption outpaces countries like Germany (66%), New Zealand (70%), and Spain (58%), solidifying its position as a front-runner in cloud, AI, and ML utilization.

The report delves into the transformative potential of AI, the biggest risk priorities, and underscores how AI plays a pivotal role in fortifying resilience. Data privacy (59%) and cybersecurity (53%) emerge as the top risk concerns for the upcoming year, followed by ESG risk (47%) and credit risk (41%).

Effectively mitigating these risks depends on improving the predictiveness of models and unlocking value from a wide variety of data sources. In this regard, AI, particularly ML, stands out as an instrumental tool with immense potential.

Achieving AI success requires large volumes of data and the right data infrastructure. Despite an increase in new data sources, the biggest data-related challenge (for 48% of respondents) pertains to the difficulty in effectively sharing data at a large scale while ensuring trust and security.

As a result, 86% of business leaders are prioritising investments in new data sources to better understand risk and affordability.

The research shows that the biggest analytics-related challenge for nearly half of respondents (55%) is the ability to seamlessly connect different data assets in a data warehouse that can adequately support AI/ML use cases.

To address this issue, 86% are prioritising investments in cloud technology for seamless data integration with 63% agreeing that externally hosted cloud services are the best way to avoid data silos and aggregate data sources.

There are multiple ways in which AI can improve productivity, efficiency, and service delivery. Many organisations are actively exploring AI use cases, with a diverse range of possibilities, including enhanced underwriting with ML-based models, proactive and early identification of vulnerable customers, improved fraud prevention and faster customer service. More than half (65%) of those already using AI find that their productivity gains have offset the initial cost – a clear indication of positive ROI from AI adoption.