AI Adoption Among Indian Enterprises

Summary

In 2022 the share of AI professionals in Indian enterprises stands at an average of 4.1%.
At 65%, the BFSI sector shows the highest rate of AI adoption.
More than 74% of Indian AI enterprises have adopted Deep Learning.

AI Adoption Among Indian Enterprises

The section presents the adoption of AI and its use cases across sectors in India - the share of AI professionals across Indian enterprises, the extent and the stage of AI adoption by different sectors.

#1. Share of AI professionals among Indian enterprises

One in eight (12.8%) of mid-to-large size organisations in India have employed a tenth of their workforce with AI professionals.

#2. Share of AI professionals across sectors

A high demand for automation combined with emerging technologies like IoT, digital twins, etc., that enable it has led traditional industries like Manufacturing & Production and Infrastructure & Transport to invest significant budgets in AI.

#3. AI adoption across sectors

With increasing digitisation, the risks of fraud in the BFSI sector have increased, and so have the concerns regarding data security and privacy. Besides offering solutions for better customer experience and reduced operational costs, AI has huge potential to address fraud detection and data safety issues.

The adoption of AI in the Pharma & Healthcare sector is predominantly driven by the focus on preventive healthcare, drug discovery, and precision medicine.

#4. Stage of AI adoption across sectors

Sectors such as Pharma & Healthcare and Retail & FMCG have a high share of Leaders and Early Stage adopters due to the existing digitisation within the ecosystem. This has enabled them to develop state-of-the-art applications to solve complex real world problems.

The share of BFSI First-stage adopters is high despite the digitisation as public-sector banks are catching up slowly on the AI hype.

#5. AI capabilities among Indian enterprises

The immense popularity of deep learning among AI enterprises is due to its ability to reveal hidden properties, patterns, and relationships within data that might not even be apparent to humans.

It has immense potential to execute multiple tasks with various data sources while reducing human interference. DL is set to penetrate further among all enterprises with the gradual unfolding of its efficiency.

#6. Adoption of AI use cases

Among all use cases, Service operations optimisation is most popular among AI enterprises due to the immense business value it generates by enabling firms to strike the right balance between retaining customers while simultaneously optimising resources and maximising productivity.