After US, India ranks 2nd globally in enterprise AI usage; security risks loom

New Delhi: India has emerged as a global powerhouse in artificial intelligence (AI) adoption, ranking second only to the United States in enterprise AI/ML transactions, according to a report by cloud security major Zscaler.

The findings, released in the ‘Zscaler ThreatLabz 2026 AI Security Report,’ come a week ahead of the high-stakes India AI Impact Summit 2026.

The summit, expected to be a gathering of global tech leaders, policymakers, and innovators, is slated to be held in the national capital from February 16-20 and will see global tech leaders in the likes of NVIDIA CEO Jensen Huang, OpenAI CEO Sam Altman, Google CEO Sundar Pichai, Anthropic CEO Dario Amodei, and Qualcomm CEO Cristiano Amon.

Zscaler pointed out that despite strong momentum in AI adoption in India, significant security challenges persist. These include the weaponisation of agentic AI and a critical gap between innovation and security measures.

The report, drawing on an analysis of nearly one trillion AI and machine learning transactions on the Zscaler Zero Trust Exchange platform from January to December 2025, indicates that enterprises have reached a tipping point where AI is shifting from a productivity tool to a primary vector for autonomous, machine-speed conflict. The study examines AI and ML traffic together, as enterprise AI systems depend on machine learning models to function at scale.

According to the report, Indian enterprises logged a staggering 82.3 billion AI/ML transactions between June and December 2025. This volume accounts for 46.2 per cent of all AI activity in the Asia-Pacific (APAC) region, comfortably placing India as the regional leader.

“India’s growth aligns with continued government-backed digital transformation efforts in 2025, alongside major public and private investment in AI infrastructure and skills development. An expanding AI-enabled workforce, combined with cloud-first architectures that enable fast, scalable deployment of AI services, likely contributed to the country’s outsized growth relative to prior years,” the report noted.

AI activity in India was driven primarily by the Technology & Communication (31.3 billion transactions), Manufacturing (15.7 billion), Services (12.6 billion), and Finance & Insurance sectors (12.2 billion).

Despite this momentum, the report highlights a key shortfall: many organisations lack even a basic inventory of their active AI models and embedded features, leaving them unaware of exactly where sensitive data is exposed.

India’s scale of enterprise AI adoption is accelerating faster than most organisations’ ability to govern it, said Suvabrata Sinha, CISO-in-Residence, India at Zscaler.

“With AI now embedded in everyday business applications and workflows, the security priority for Indian enterprises is clear: understand where AI is being used, inspect the data being shared, and enforce the right controls consistently. A zero-trust approach with strong data protection and continuous visibility is essential to secure AI-driven transformation at the speed the market now demands,” he said.

A key theme at the India AI Impact Summit is around the rise of "Agentic AI"—autonomous systems that can plan and take actions independently. The report warns that this technology is already being weaponised.

Zscaler researchers revealed that when enterprise AI systems are tested under real adversarial conditions, they break almost immediately. In controlled scans, critical vulnerabilities surfaced in minutes, not hours.

The median time to first critical failure was just 16 minutes, with 90 per cent of systems compromised in under 90 minutes. In the most extreme case, the defence was bypassed in a single second.

“As more evidence of AI-driven attacks by cybercriminals and nation-state espionage groups is uncovered, ThreatLabz warns autonomous and semi-autonomous 'agentic' AI will increasingly automate cyberattacks, with AI agents assuming responsibility for reconnaissance, exploitation, and lateral movement. Defenders must assume that attacks can scale and adapt at machine speed, not human speed.

Data loss remains a massive concern. Globally, over 18,000 terabytes of data were funnelled into AI applications in 2025 – roughly equivalent to 3.6 billion digital photos.

This massive data influx has turned tools such as Grammarly, with 3,615 terabytes of traffic, and ChatGPT, with 2,021 terabytes, into the world's most concentrated stores of corporate intelligence.

ChatGPT alone was tied to 410 million Data Loss Prevention (DLP) policy violations, involving the attempted sharing of sensitive information such as source code and medical records. As these repositories grow, they are becoming high-priority targets for cyber espionage.

“AI is no longer just a productivity tool but a primary vector for autonomous, machine-speed attacks by both crimeware and nation-state. In the age of Agentic AI, an intrusion can move from discovery to lateral movement to data theft in minutes, rendering traditional defences obsolete. To win this race, organizations must fight AI with AI by deploying an intelligent Zero Trust architecture that shuts down the potential paths for the attackers of all kinds,” said Deepen Desai, EVP Cybersecurity at Zscaler.