Indian enterprises scale AI-led security, but identity gaps persist, says Zoho

Enterprises increase AI investments and security budgets, yet a lack of Zero Trust, access control, and identity visibility continues to expose structural vulnerabilities.

Indian enterprises are showing confidence about the use of AI in cybersecurity and considering it as a core layer for threat detection, response, and automation. Organisations are increasing budgets and prioritising AI-driven tools to handle rising volumes of threats and expanding digital environments.

At the same time, foundational gaps in identity and access management continue to persist. A significant share of organisations operate without Zero Trust frameworks, while visibility into user identities and system access remains limited.

As AI expands across business applications, these gaps create conditions in which risks scale with investments.

“While 93 percent of Indian businesses believe AI will enhance security, one in three does not have a Zero Trust strategy in place,” according to the State of Workforce Password Security Report 2026, conducted by Tigon Advisory Corp. on behalf of Zoho Vault.

Most respondents indicate a high likelihood of adopting AI-driven security solutions, with a majority also planning to increase security budgets over the next five years. The focus is on capabilities, including real-time threat detection, user behaviour analytics, and automated access control.

These investments reflect a shift towards adaptive security operations with AI systems help analyse large volumes of data, identify anomalies, and respond to threats in near real time.

However, this shift is not matched by progress in core security controls. Many organisations continue to underinvest in credential management, access governance, and authentication frameworks. AI systems depend on structured identity data and clearly defined access rules to operate effectively. In their absence, AI tools act as detection layers rather than preventive controls.

"As AI becomes an integral tool at work, organisations need to guard against the new threats emerging in the workplace security landscape. While Indian businesses are keen to adopt AI, they still have blind spots, namely lack of Zero Trust, lack of visibility into their critical systems, and threats from internal sources,” said Chandramouli Dorai, chief evangelist, cyber solutions & digital signatures, Zoho Corp.

“This reflects an urgent need for stronger protection within the perimeter. The survey shows clearly that an AI 'bandaid' on these structural gaps will make the situation worse in the long-term. Businesses need sturdier foundations with strong credential management, access controls, and multi-factor authentication," Dorai added.

Identity environments are becoming complex as enterprises adopt cloud services and business applications. Employees interact with multiple platforms daily, each requiring separate credentials and access permissions. This increases the number of entry points that need to be secured.

A substantial share of organisations has only partial visibility into who can access critical systems. This limits the ability to enforce consistent policies and monitor access across environments.

In such scenarios, AI tools may identify suspicious activity, but preventing escalation becomes difficult when access to sprawl is already in place. The lack of visibility into identities and privileges continues to be one of the most critical gaps in enterprise security.

Insider risks grow amid weak access controls

The threat landscape is also shifting inward. Organisations identify malicious insiders as the leading security risk, ahead of ransomware and human error. This reflects a change in how threats emerge within enterprise environments.

Weak access controls and excessive privileges increase the likelihood of misuse. Once access is compromised, attackers can move laterally across systems, especially in environments where identity governance is inconsistent.

Nearly half of the organisations surveyed report experiencing cyberattacks. While most express confidence in their ability to respond, the response strategies rely heavily on detection tools rather than preventive measures.

Adoption of basic controls remains limited. Only a small share of organisations prioritise strong password policies, multi-factor authentication, and access management. Endpoint security adoption also remains low compared to investments in detection capabilities.

This imbalance creates environments where threats can bypass initial controls and escalate into larger incidents. Detection improves visibility, but without strong access controls, containment becomes more difficult.

Despite these gaps, organisations describe their security infrastructure as future ready. A large majority expect to adopt Zero Trust strategies within the next few years.

However, legacy systems continue to act as constraints. Older infrastructure limits the ability to implement modern identity frameworks and integrate advanced security controls.

Operational challenges also play a role. Organisations cite the cost of security solutions, the pace of evolving threats, and shortages in skilled talent as key barriers. These factors make it easier to invest in AI-led tools that offer immediate gains rather than undertaking structural changes to identity architecture.

Opportunities in identity-led security transformation

For enterprise security leaders, the shift highlights the need to balance innovation with fundamentals. AI can improve detection and response, but it cannot replace the need for strong identity governance and access control.

This creates opportunities in identity-led security transformation for channel partners and service providers. As organisations look to address gaps in visibility and access, demand is expected to grow for Zero Trust implementation, identity and access management programmes, and ongoing governance services.

Enterprise security is moving towards AI-enabled operations. However, the effectiveness of these systems depends on the strength of the underlying identity frameworks.

As organisations expand AI across their security stack, the focus is shifting from adopting new tools to fixing structural gaps. Without stronger identity foundations, AI-driven security risks operate on incomplete data and inconsistent controls, limiting their ability to deliver long-term outcomes.