How self-governing identity infrastructure can streamline policy enforcement [Q&A]

Managing identity is one of the more challenging cybersecurity tasks and can soak up a good deal of time and resources.

We spoke to Raz Rotenberg, co-founder and CTO of Fabrix Security, to discuss the rise of self-governing IAM systems that don’t just enforce policy — but continuously adapt, reason, and remediate access in real time.

BN: What does ‘self-governing’ actually mean in the context of identity infrastructure, and how is it different from traditional automated policy enforcement?

RR: Self-governing identity infrastructure goes far beyond automated policy enforcement. Traditional automation executes static rules: ‘if X happens, do Y’. But policies alone cannot keep up with the complexity and velocity of today’s environments.

Self-governing means the system understands context, reasons about risk, and adapts dynamically, just as a seasoned security leader would. It’s not just enforcing policies; it’s continuously learning from activity, aligning access with intent, and making intelligent decisions right where and when decisions should be made to reflect organizational goals and security posture.

BN: As IAM systems become more autonomous, how can organizations ensure that continuous adaptation doesn’t introduce new risks or unintended access patterns?

RR: Autonomy must be paired with governed intelligence, this is why we believe that humans should always be in the driver’s seat. Continuous adaptation is powerful, but left unchecked it can drift into dangerous territory. Organizations must demand systems that reason transparently, AI agents that simulate the downstream impact of decisions before executing them and constantly validate access against policies, usage, and risk models.

The safeguard isn’t limiting autonomy, it’s embedding explainable reasoning loops, evidence-backed decisions, and human-defined guardrails to ensure the system evolves responsibly while eliminating excess risk.

BN: What role does explainability play in making self-governing systems trustworthy, especially in high-stakes sectors like finance, healthcare, and critical infrastructure?

RR: Explainability is the currency of trust. In high-stakes sectors, a decision without rationale is not a decision, it’s a liability. Self-governing IAM must not only act but show its work; why it granted or revoked access, what evidence supports the decision, and how it aligns with the organizations’ policy. This transparency transforms AI from a “black box” into a collaborative partner, empowering auditors, CISOs, and regulators to trust outcomes while moving faster than human-driven workflows ever could.

BN: How should security teams rethink their operational oversight when IAM decisions are being made in real time by AI agents rather than through human approval workflows?

RR: Operational oversight shifts from manual, repetitive review to strategic supervision. Instead of drowning in approval queues, and resolving some of them by guessing since there’s not enough visibility and context, security teams will focus on setting policies, monitoring reasoning quality, and investigating actual risk flagged by AI.

The mindset change is: humans no longer process access requests, they govern the intelligence that processes them. This allows scarce security talent to scale impact, ensuring oversight at the policy and strategy level while AI agents execute at machine speed and scale.

BN: What are the most significant technical and organizational barriers enterprises face in moving from static IAM to a dynamic, reasoning-based approach—and how can they overcome them?

RR: The biggest barriers are:

• Fragmented identity data – spread across countless systems, making reasoning impossible without consolidation.
• Cultural inertia – where organizations are comfortable with “checkbox compliance” even if it leaves blind spots.
• Trust gaps – as leaders hesitate to hand over critical decisions to AI.

Overcoming these requires:

• Unifying identity intelligence – into a single fabric that spans human and non-human identities.
• Demonstrating early wins – with AI agents that clean up toxic permissions and streamline reviews.
• Embedding explainability and control – so decision-making is transparent and auditable from day one.

Enterprises that embrace this shift will move from static and reactive governance to truly adaptive and proactive security, where identity not only supports the business but actively protects it.

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