AI, Identity And The Cybersecurity Risk

Attackers still log in. For years, credential theft through phishing has been one of the most persistent and damaging threats to modern organizations, not because it is sophisticated, but because it works.

Photo by Onur Binay 

Access is rarely gained through a dramatic technical exploit or by “breaking down a digital wall.” More often, an attacker signs in with valid credentials and moves quietly through systems, staying under the radar long enough to find what they need.

Sometimes that access is used directly for data theft and extortion. Other times it is sold on to criminal networks that escalate the attack, encrypt environments, and demand ransom.

Agentic AI has raised the stakes. This is the moment to treat cybersecurity as a core business priority, not a compliance exercise, because the threat model has shifted underneath us.

The Threat Is Automated and Adaptive

Cybersecurity used to focus on preventing break-ins. Increasingly, it is about detecting intent inside activity that looks legitimate.

Every login, permission change, API call, and device posture check generates data. Microsoft processes more than 100 trillion security signals each day. Billions of emails are scanned. Millions of malware attempts are blocked. Tens of millions of identity risks are evaluated. No human team can keep up with that scale, and the volume alone makes manual defense unrealistic.

Attackers are also no longer working manually. Agentic AI enables automated reconnaissance, highly personalized phishing created in seconds, voice mimicry, credential testing across environments, and continuous adjustment when they meet resistance. These systems learn, retry, and optimize for outcomes.

Cybercrime has become a scalable business model. Most serious incidents are financially motivated and revolve around data theft, extortion, and ransomware. Access is the product. Data is the leverage.

When the threat runs on automation, defense has to match it.

Identity Is the Control Plane for Risk

Many major breach investigations converge on the same root cause: identity.

A compromised account. An overprivileged administrator. A token that never expired. A legacy protocol left enabled. A service account no one owns.

Identity is where access begins and where trust can be evaluated in real time. It is not a background IT function. It has become the control plane for risk.

Platforms like Microsoft Entra ID continuously evaluate who is signing in, from where, on which device, and under which risk signals, and then compare that behavior to global intelligence. Risk scoring happens in milliseconds. Conditional access is enforced before a human is ever involved, and that capability is becoming foundational.

When we at Fortytwo speak with leadership teams, we start with a simple question: do you know who has access to what right now, and why? If the answer is unclear, risk is not being managed. It is being assumed.

Hybrid Environments Amplify Exposure

Ransomware and data theft rarely stay contained within a single environment. A growing share of incidents span both on-premises and cloud systems. A single outdated service account on a local server, a synced identity with excessive privileges, or a trust relationship that has not been reviewed in years can be enough to open pathways across the estate.

Attackers increasingly rely on legitimate administrative tools to blend in. They move laterally through hybrid connections. Agentic AI helps them map environments, test pathways, and escalate privileges faster than a human operator could. The exposure is often created by the connections between systems, and identity sits at the center of those connections.

From Alert Overload to Real Insight

Security teams are not lacking data. They are overwhelmed by it.

Thousands of alerts can arrive daily. Many are low risk. Some are critical. Separating noise from real threats requires context, correlation, and speed. This is where AI changes day-to-day operations. It can correlate weak signals across environments, identify patterns that deviate from established baselines, elevate what truly matters, and suppress what does not.

The impact goes beyond technical efficiency. When teams spend less time chasing false positives, the organization becomes more stable. Decisions are grounded in evidence rather than urgency, and leadership conversations shift from reacting to headlines to reviewing risk posture with clarity.

Agentic AI Compresses the Timeline

What makes 2026 feel fundamentally different is the rise of goal-driven attack systems.

These tools are not static scripts. They are given objectives, along with the ability to adapt their methods to achieve them, such as:

• obtaining credentials

• escalating privileges

• extracting data

• monetizing access

They test variations automatically and adjust based on system responses. What once unfolded over weeks can now happen in hours.

That compression changes the defensive requirement. Detection has to happen earlier in the attack chain. Authentication is the earliest consistent checkpoint across nearly every environment. If risk is identified at login, lateral movement and escalation can often be stopped before damage spreads.

The Economics of Identity Discipline

Cybersecurity is often framed as insurance. In practice, it protects margin and operational continuity.

Extortion and data theft account for a significant share of investigated incidents. Overprivileged accounts, unused admin rights, and delayed deprovisioning increase the potential return for attackers. Every unnecessary privilege expands exposure, just as every unmanaged access path extends opportunity.

When identity governance is implemented well, access aligns with role and lifecycle. Joiner, mover, and leaver processes run continuously. Privileges are reviewed systematically. Access expires when it should.

Risk decreases quietly. Operational friction can decrease as well. Security becomes embedded in design, rather than activated during crisis.

Responsible Automation Strengthens Trust

AI in cybersecurity must be implemented deliberately. Risk models need to be explainable and aligned with intent. Policies must reflect business priorities, and exceptions must be visible and traceable.

Automation can scale human judgment, but it cannot replace it.

The most resilient organizations combine automated decision-making with clear oversight. They define acceptable risk levels, monitor outcomes, and refine posture continuously.

What This Means for Leadership

AI is already embedded in cloud services, productivity platforms, and analytics tools. The leadership question is whether it is equally integrated into identity and access management, because that layer determines who can reach data, systems, and customers.

When AI strengthens identity, risk is identified earlier, access becomes more transparent, and response becomes faster. Board discussions shift from speculation to measurable indicators. Audits become less disruptive. Incident response becomes more controlled.

This Moment Requires Clarity

Cybersecurity in 2026 is shaped by automation on both sides. Agentic AI has shifted the balance. Organizations that treat identity as infrastructure will manage that shift. Those that treat identity as a secondary IT service will struggle to see emerging risk in time.

The path forward is straightforward:

• Maintain continuous visibility into who has access, and why

• Verify trust at every authentication

• Automate risk-based decisions in real time

• Reduce privilege intentionally, and consistently

• Build governance into lifecycle processes

When identity becomes intelligent and adaptive, AI used right, strengthens defense instead of amplifying threat.

Security is no longer primarily about building higher walls. It is about understanding behavior as it happens, and acting early enough that damage never gets the chance to spread.