India is emerging as one of the most aggressive adopters of artificial intelligence in the Asia Pacific region, but a lack of trust in data could become a major obstacle to realising its full economic potential.
New research from Veeam Software, unveiled at VeeamON London, found that 93% of Indian organisations are already using or piloting agentic AI systems, compared with 88% globally. Of these, 44% have already moved such systems into production.
The study, based on a survey of 600 senior executives across financial services, healthcare, manufacturing, retail and technology sectors worldwide, highlights a widening gap between rapid AI adoption and the governance frameworks needed to manage it effectively.
Indian executives appear particularly optimistic about AI’s commercial potential. Nearly half (49%) believe trusted, secure and compliant data could unlock revenue growth of more than 25%, while the average expected uplift stands at 31%, the highest among all markets surveyed.
However, confidence in AI is being tempered by concerns around trust, governance and security. An overwhelming 98% of Indian respondents said data-related challenges had already slowed their AI initiatives.
Governance gap emerging
The findings suggest that India’s AI ambitions are racing ahead of the controls needed to support them.
While 64% of organisations report maintaining a reliable inventory of AI systems deployed across their operations, 42% cite risks arising from autonomous agent behaviour and decision chaining as one of the biggest challenges slowing AI progress. This is the highest such reading across the Asia Pacific region.
Cybersecurity is another growing concern. More than half (53%) of Indian executives identified increased cyber risk as the biggest threat posed by unauthorised or “Shadow AI” usage. Meanwhile, 51% said ensuring personal data is not misused within AI systems is their foremost compliance concern.
India’s evolving regulatory environment is also shaping corporate AI strategies. With the rules under the Digital Personal Data Protection Act, 2023 being finalised and the Rs 10,372 crore IndiaAI Mission accelerating domestic AI infrastructure development, organisations are increasingly focusing on responsible AI deployment.
Reflecting India’s close business ties with European clients, particularly through the IT services sector, 78% of Indian executives said the EU AI Act had already influenced their AI investment strategy over the past year, compared with 61% globally.
Trust is the next phase of AI
“Most organisations don’t have an AI adoption problem; they have an AI trust problem,” said Anand Eswaran, CEO of Veeam.
“The first phase of AI was defined by infrastructure investment, experimentation and acceleration. The next phase will be defined by trust. With the widespread adoption of autonomous AI agents operating at machine speed, the question shifts from whether you can use AI to whether you can ensure all your data is secure, governed, compliant and resilient.”
He added that organisations must also be prepared to recover quickly and accurately when AI systems fail, without creating additional operational or reputational risks.
CEOs and technology leaders
The research also uncovered significant differences in perception between senior management and technology teams.
While 65% of CEOs believe they have a complete inventory of AI systems deployed across their organisations, only 48% of technical leaders agree. Similarly, 52% of CEOs believe they actively lead data initiatives, compared with 41% of chief information security officers and just 38% of chief information officers.
At the same time, 83% of CEOs reported feeling pressure to accelerate AI and data capabilities.
When AI fails
The report argues that future AI failures are unlikely to resemble traditional technology outages. Instead, risks will increasingly arise from data-level errors that are more difficult to detect, explain and contain.
Among organisations currently using AI, only:
- 29% could quickly identify which systems an AI agent had accessed;
- 25% could determine what actions it had taken;
- 24% could establish which decisions it had influenced; and
- 22% could identify the data it had used.
Only 40% of leaders said they were highly confident in their ability to isolate and precisely reverse the impact of an agentic AI failure.
Shadow AI becomes mainstream
Unauthorised use of AI tools has become widespread within organisations.
The survey found that 95% of organisations had experienced unauthorised AI use, while 93% considered it a significant risk. Yet only 25% provide employees with approved alternatives, suggesting many companies are attempting to restrict AI usage rather than govern it effectively.
Externally, regulatory scrutiny is intensifying. Nearly half (47%) of respondents identified maintaining audit trails for AI-driven decisions as their biggest compliance challenge.
Clear ownership delivers better outcomes
According to the study, fragmented ownership remains one of the biggest barriers to successful AI deployment.
Organisations where chief information security officers hold direct responsibility for AI agent risks are 24% more likely to detect rogue AI behaviour. By contrast, businesses relying on shared ownership models are 47% less likely to identify such risks.
The findings suggest that trusted data requires more than executive sponsorship. It demands clear accountability across governance, security, privacy, compliance and resilience functions.
AI readiness separates leaders from laggards
The study concludes that organisations able to align AI ambition with governance and visibility are already seeing tangible benefits.
Among companies classified as fully AI ready, 97% reported measurable business gains from data and AI investments, compared with just 48% of organisations overall.
As enterprises accelerate AI deployment, Veeam argues that trust, rather than technology alone, will become the defining factor separating winners from laggards in the next phase of the AI era.
Veeam: Building the data and AI trust layer
Veeam is addressing this challenge by combining data resilience, security and governance to help organizations see what data AI uses, govern how it’s accessed by humans and agents, and recover clean, trusted data with precision when incidents occur.
“The findings here leave no room for doubt. When 95% of executives say data challenges are already slowing their AI progress, the bottleneck isn’t the model – it’s trusted, governed, recoverable data,” added Eswaran. “Veeam is building the Data and AI Trust layer to give enterprises the visibility, control and precision recovery needed to scale AI safely and deliver real business value.”
