Identity Mirage: The Real Risk Behind C-Suite Optimism on AI Agents
Identity Mirage: The Real Risk Behind C-Suite Optimism on AI Agents
Publish Date: 2026-06-27 02:15:00
Source Domain: www.cybersecurity-insiders.com
Using an unordered list, summarize the following article with between 4 and 8 key points.
Organizations are racing to adopt agentic AI. IDC predicts that 45% of companies will orchestrate AI agents at scale and embed them across business functions by 2030. But in the race to adopt this technology, a critical gap is emerging between executive expectations and operational reality, and this gap is quietly expanding the attack surface for organizations.
C-suite leaders tend to have a rosier outlook when it comes to how these AI agents are being treated from a security standpoint – one that often conflicts with what’s actually happening in an organization. If the right governance isn’t put into place, these conflicting views can create unmanaged identities, inconsistent access control and an illusion of Zero Trust readiness.
The rise of AI agents and machine identities
Increased adoption of AI agents also means a rise in non-human or machine identities, each of which must have a unique identifier. Non-human identities now outnumber human identities in most organizations, often by factors of 50:1 or more, yet ownership and accountability are distributed across multiple teams.
Human identities are what most organizations are the most familiar with – the employees, contractors and even some partners or customers who need access to corporate networks, apps and data. These are the types of identities that traditional identity governance was built for.
Organizations must manage these machine identities effectively so that they can authenticate and validate machine-to-machine interactions and prevent unauthorized access to the company’s crown jewels. The rise of generative AI and agentic AI creates a new realm of security challenges related to the digital identities of AI agents.
That said, organizations are taking identity security seriously amid this changing landscape – and they think they are advancing their identity security. At Omada, we recently conducted a survey on the state of identity governance administration (IGA) in which 76% of participants strongly agreed that identity security is a core cybersecurity strategy.
This perspective demonstrates true focus and investment. Organizations recognize the strategic role identity plays, leading to more mature programs. Yet confidence is often a perception rather than a reality.
Mind the gap
As Omada’s report found, organizational leaders understand the need for strong identity security, especially amid this changing landscape, but they don’t always have an accurate perception of what’s happening within the organization.
The report finds that credential management practices for agentic AI vary widely across organizations. Many respondents report using stronger practices such as rotating short-lived credentials and assigning unique identities to AI agents. At the same time, a significant portion rely on static credentials or shared accounts, indicating inconsistent application of governance controls.
And what’s more, there’s a difference between executive and non-executive responses. C-level respondents are more likely to report the use of stronger practices, such as rotating credentials and unique identities (48%), than the overall respondent population. However, responses across the board reveal that such practices have yet to be consistently applied across organizations.
These disconnects matter because the consequences can be serious. In instances where leaders’ perception differs from the reality of daily operations, governance blind spots can expand without detection. The stakes for identity controls are rising as autonomous AI agents are entering production environments, acting continuously and at scale.
Thus far, governance has not matched the pace of adoption. Though companies see the risks and want strong controls, many of them are still trying to adapt identity models, oversight mechanisms and ownership structures that can address autonomous behavior. It’s a standard pattern for new technology: adoption is enthusiastic and rapid, but governance is lagging due to uncertain accountability and legacy processes.
Structural risk is the result. Because autonomous agents can create and change access apart from human direction, governance maturity falls behind. This enables small gaps in control to continue and expand unseen.
Tighter identity governance is needed
Identity governance is approaching an inflection point. Identity is no longer a periodic control but an ongoing, machine-driven operating layer that underpins Zero Trust, automation and AI-enabled workflows. Visibility must shift from activity to exposure.
Fragmentation is undermining control. Identity data remains dispersed across platforms, limiting unified oversight, while ownership of non-human identities is often distributed across teams. Companies need to treat identity governance as a strategic control surface. Organizations that establish clear ownership, consistent integration and executive-level visibility will be better positioned to manage this shift.
It’s also important to move beyond tooling toward operational coherence. Those relying on fragmented tooling or incomplete reporting will find it increasingly difficult to explain, manage or trust the access decisions that agents are making.
Companies must govern at the speed of automation. The next phase of identity governance won’t be characterized by whether identity is important; it will be defined by whether governance can match the speed and scale it operates at now.
Overcoming the identity governance mirage
As organizations rush to adopt agentic AI, a critical gap is emerging between executive expectations and daily operations that could quietly expand the attack surface. According to new survey data, the bulk of C-suite leaders believe each AI agent is assigned a unique identity, but the practitioners don’t always agree. The divide widens around credential hygiene. This misalignment reveals a dangerous overconfidence at the top and a lack of shared standards in practice.
This scenario leads to slipshod access control, unmanaged machine identities and a pretense of Zero Trust. Use the best practices discussed above to take the governance, automation and verification steps necessary to align AI identity management with real-world security needs before agentic systems scale beyond safe oversight.
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