India Leads in GenAI Ambitions, Information Complexity Remains a Challenge: Report 46 per cent of Indian enterprises already embed AI in business strategies, yet weak data foundations and cyber risks could slow India's AI advantage.

Indian enterprises are among the fastest adopters of Generative AI (GenAI) but gaps in information readiness are making it difficult to secure, govern, and scale AI across business, according to a latest report titled "The Challenges to Ensuring Information Is Secure, Compliant and Ready for AI" conducted by the Ponemon Institute for OpenText.

The study revealed that 48 per cent of Indian enterprises have already embedded AI into IT and business strategies, one of the highest adoption rates globally. Yet only 15 per cent feel confident in measuring return on investment from securing and managing the information that underpins these initiatives. The survey covered almost 1,900 senior IT and security leaders worldwide, including 337 in India.

Indian organisations are also ahead of global peers in prioritising digital transformation (54 per cent vs. 44 per cent globally), reflecting a future-forward approach that complements their rapid AI adoption. Yet information complexity, driven by unstructured data, security risks, and lack of governance safeguards, remains a critical roadblock for enterprises seeking to scale AI responsibly.

Moreover, the survey highlights that companies in India are more alert to the risks of AI than many global counterparts. For example, 46 per cent of Indian respondents flagged bias in AI models as a top concern versus 32 per cent globally, while privacy infringement was cited by nearly half of Indian leaders. At the same time, adoption of advanced capabilities like Agentic AI is growing, with 18 per cent already deploying and another 20 per cent planning adoption within six months.

"India is fast emerging as a global leader in AI adoption, with enterprises showing remarkable ambition and enthusiasm," said Saurabh Saxena, Regional Vice President, OpenText India. "With 59 per cent of Indian boards and CEOs rating AI as extremely important, higher than peers in the UK and France, the ambition is clear. The opportunity now is to leapfrog global counterparts by closing gaps in information readiness. The success of AI will depend on how well organisations address information readiness gap, simplifying complexity, securing sensitive data, and embedding responsible governance practices. By investing in strong information foundations today, Indian enterprises can unlock AI's full potential with speed and confidence."

When it comes to GenAI, India leads in mission-critical use cases, with 46 per cent of organisations using it for security operations and 44 per cent for business reporting, both significantly higher than global averages. This signals that Indian enterprises are embedding GenAI directly into operational and strategic decision-making.

Cybersecurity adds to the challenge. Just over half of Indian organisations reported a breach or cyber incident in the past two years, averaging three incidents each. Ransomware and insider threats remain the most pressing risks, even as organizations improve monitoring across hybrid environments.

Despite strong digital ambitions, gaps in information governance remain the missing link in India's AI readiness. Only 41 per cent of Indian leaders are confident in measuring ROI on information security investments, slightly below the global average. Notably, 55 per cent of organisations in India expect to demonstrate ROI within 6-12 months, showcasing the urgency from boards and CFOs to see fast returns. At the same time, GenAI adoption is constrained by challenges such as copyright risks, lack of in-house expertise, and regulatory uncertainty. Budget constraints and shortage of skilled AI professionals were also cited as significant barriers, slowing the ability to scale.

To realise the true potential of AI, Indian enterprises must first strengthen information governance. This includes enhancing cybersecurity to reduce both external and insider risks, as well as investing in infrastructure that supports digital transformation and prepares for advanced AI workloads.