Artificial intelligence (AI) spending in India is set to grow at 35 per cent annually, reaching $9.2 billion by 2028, a report showed on Tuesday.
This emphasises the need for better data quality, governance, and cloud migration to maximise AI’s potential, according to the report by Qlik while releasing a new research paper by International Data Corporation (IDC).
About 51 per cent of Indian enterprises host AI solutions in the cloud, but poor data quality remains a challenge.
The report highlighted data quality as a major barrier, with 54 per cent of Indian organisations citing it as a challenge, surpassing Australia at 40 per cent, ASEAN at 40 per cent, and the APAC average of 50.4 per cent.
Additionally, 62 per cent of Indian organisations recognised the need to improve data governance and privacy policies, while 28 per cent struggled with AI data bias, more than ASEAN at 21.8 per cent and Australia at 20 per cent, the report mentioned.
To overcome these challenges, Indian enterprises are investing in data integration, ML deployment platforms, and analytics to establish AI-ready data strategies. Strengthening data integrity, transparency, and compliance is key to successful AI adoption.
“Indian organisations see cloud adoption as a critical step toward AI success,” said Varun Babbar, Vice President, India, Qlik.
“To scale AI-driven innovation, businesses need a strong, scalable data infrastructure that supports high-performance AI applications,” he added.
The ‘IDC InfoBrief’ report found that with 36 per cent of enterprises using GenAI and 46 per cent planning investments within 12-24 months.
India is on par with Australia and New Zealand, with 20 per cent of organisations possessing advanced AI capabilities, though it lags behind ASEAN, where 27 per cent have reached this stage.
“GenAI is transforming industries in India — from compliance in retail to fraud prevention in finance and predictive maintenance in manufacturing,” said Deepika Giri, AVP, Big Data Analytics, Blockchain, and Web3 Research, IDC Asia/Pacific.
However, to unlock its full potential, organisations must prioritise trusted data, robust governance, and infrastructure readiness to scale AI effectively and responsibly, she mentioned.
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