The era of "set it and forget it" IAM is over, says Saviynt as AI reshapes partner opportunity

AI agents are pushing partners beyond one-time IAM deployments toward continuous identity governance, identity security posture management and recurring advisory services.

AI agents and machine identities are forcing enterprises to abandon the traditional "set it and forget it" approach to identity and access management (IAM), creating a new opportunity for channel partners to move beyond one-time implementation projects and deliver continuous identity governance, managed security services and long-term advisory engagements.

“Legacy IAM architectures, built around human users, HR records and periodic access reviews, are unable to govern AI agents, bots and other non-human identities that operate autonomously and at machine speed,” Saviynt’s SVP and managing director, India & SAARC, Nitin Varma, told CRN India.

According to Varma, that shift is reshaping not only enterprise identity security strategies but also the role partners play inside customer environments.

Rather than delivering static IAM deployments, system integrators and managed security service providers (MSSPs) are expected to provide continuous governance, identity security posture management (ISPM) and ongoing visibility into both human and non-human identities.

The adoption of AI is exposing assumptions that have underpinned enterprise IAM for decades. Varma argued that traditional IAM architectures were designed on the premise that every identity belongs to a human employee linked to an HR system.

That assumption begins to fail as organisations deploy an increasing number of AI agents, bots, APIs and service accounts that require autonomous access across enterprise applications.

"Traditional IAM architectures do not just stretch; they fundamentally break," Varma said.

He noted that non-human identities can outnumber human users by as much as 82-to-1, making periodic entitlement reviews and quarterly access certification exercises increasingly ineffective.

The challenge becomes even more evident as AI agents operate at machine speed.

According to Varma, traditional access approval workflows are often the first control to fail because they rely on manual approvals that cannot keep pace with autonomous AI-driven operations.

To maintain productivity, organisations grant AI agents standing or permanent privileged access instead of following just-in-time access principles, inadvertently increasing enterprise risk.

As AI adoption accelerates, he believes identity governance must evolve from periodic compliance exercises into continuous, risk-based governance capable of monitoring access decisions in real time.

AI creates a governance challenge

Beyond introducing new identities, AI is fundamentally changing how enterprises need to think about identity governance.

Rather than simply amplifying existing credential-related risks, Varma argued AI agents create an entirely new attack surface because attackers are targeting trusted machine identities rather than individual user accounts.

"Attackers are now hacking trust models, not just accounts," he said.

Unlike human users, AI agents generate large volumes of system-to-system activity that conventional monitoring tools may interpret as legitimate behaviour, making malicious activity significantly harder to detect.

At the same time, ownership of these identities often remains undefined.

Varma said AI agents are frequently created by DevOps or data science teams without entering formal identity governance processes, leaving enterprises without clear accountability for their lifecycle, permissions or ongoing risk management.

He believes organisations need to recognise every AI agent as a first-class identity with clearly defined ownership spanning security, IT, legal and business functions.

The challenge is further compounded by a common assumption that secure cloud infrastructure automatically translates into secure AI deployments.

According to Varma, enterprises need to recognise that identity, rather than infrastructure, has become the primary security perimeter as AI adoption expands.

Continuous governance becomes the next partner opportunity

As enterprises rethink identity governance, Varma believes the channel opportunity is undergoing a similar transformation.

Rather than signalling the end of IAM services, he said AI is ending the era of static implementation-led projects while creating significantly larger opportunities around continuous governance and recurring managed services.

"The era of 'set it and forget it' IAM is over," Varma said.

Instead, partners are expected to deliver continuous assurance through managed identity governance services that provide ongoing posture assessment, automated access governance and continuous risk remediation.

For channel partners, this creates opportunities to move beyond implementation revenue toward recurring services built around Identity Security Posture Management (ISPM), AI governance and continuous compliance.

The evolution also changes the capabilities partners need to develop over the next few years.

According to Varma, system integrators and MSSPs will increasingly require expertise in ISPM, AI governance, inference architecture design and AI security assessments, while traditional, manually driven role-based access control (RBAC) projects gradually lose relevance.

He argued that recommendation-based, runtime access governance will increasingly replace static role engineering as enterprise environments become more dynamic and AI-driven.

Identity visibility becomes the next strategic services layer

Looking ahead, Varma believes future AI-driven breaches are less likely to expose weaknesses in traditional perimeter security than failures in identity visibility and governance.

He argued that organisations operating fragmented identity environments across human and non-human identities risk creating blind spots that attackers can exploit through compromised AI agents, shadow APIs and entitlement sprawl.

According to Varma, enterprises that establish a unified identity fabric capable of continuously governing both human and machine identities will be better positioned to secure AI-driven environments and meet future audit requirements.

For partners, that evolution extends identity services well beyond implementation projects into long-term governance, continuous assurance and strategic advisory roles as enterprises embed AI deeper into business operations.