Originally published on LinkedIn. Lightly edited for clarity.
Zero Trust is appealing because it promises a clean separation of trust and access. Every request is verified. No implicit network trust. Everything is mediated.
The problem is that these promises are only true in a world where identity, authorization, and configuration can update themselves at the speed of change. Without automation, Zero Trust becomes a manual process, and manual processes do not scale.
The thesis: Zero Trust is not a policy. It is an automation strategy.
If you cannot continuously validate identity and enforce access without human intervention, you have not implemented Zero Trust. You have implemented a backlog.
The operational reality of Zero Trust
Zero Trust systems rely on three things happening continuously:
- Identity is current. Users, services, and devices must be known and verified in real time.
- Policy is enforced. Access decisions must be made consistently across every system.
- Context is evaluated. Risk signals like device posture, behavior, and environment must feed those decisions.
Each of these is operationally heavy. In a manual model, identity changes require tickets, policy updates require meetings, and context signals are reviewed after the fact.
That cadence is incompatible with Zero Trust. The system simply changes too quickly.
The gap between policy and reality
Many teams adopt Zero Trust as a strategic goal, but operationally they are still working in a perimeter mindset.
For example, a policy might state that every service-to-service call must be authenticated with short-lived credentials, but the actual system relies on long-lived API keys because rotation is too painful. The policy exists, but the system does not.
Zero Trust without automation often produces three outcomes:
- Exception overload. The number of exceptions grows because policies are hard to enforce manually.
- Shadow pathways. Teams build side channels to move faster, bypassing the policy layer.
- Stale identity. Accounts linger, devices drift, and the access graph is wrong.
These are not minor flaws. They are structural failures of the model.
Example: service identity without provisioning
A mid-stage company decided to implement Zero Trust for its microservice architecture. The design mandated mutual TLS with short-lived certificates for every internal call.
The identity system was solid. The failure happened at provisioning.
Service owners were required to request certificates manually, wait for approval, and roll them out on a quarterly schedule.
On paper, the identity system existed. In reality, certificates were treated like precious resources. Teams built shared service accounts to avoid provisioning work. Within six months, more than half of internal services were using the same credentials.
Zero Trust broke, not because the cryptography was wrong, but because the operational workflow made the secure path too expensive.
The fix was simple but non-trivial: automate certificate issuance, integrate it with deployment pipelines, and enforce rotation on a short cadence. Until that automation existed, the Zero Trust system was a myth.
Automation is the control plane
In practice, Zero Trust needs a control plane that connects identity, policy, and enforcement. That control plane is automation.
It includes:
- Provisioning pipelines that create and decommission identities automatically.
- Policy-as-code that version-controls access rules and applies them consistently.
- Continuous validation that checks whether enforcement matches intent.
- Drift detection that surfaces when systems move outside their expected posture.
When these are in place, Zero Trust becomes feasible.
Without them, the model is held together by people who are already overburdened.
What automation changes
Automation changes the economics of security. It reduces the cost of doing the right thing and increases the cost of deviation.
It turns policy into infrastructure rather than a document. It also gives leaders real-time visibility into whether the system still reflects its design.
This is why I describe Zero Trust as an automation strategy.
The tooling is not a supporting act. It is the primary mechanism that makes the model real. Your security posture is only as strong as your automation.
Common automation pitfalls
Automation does not magically create trust. It can fail in subtle ways:
- Automating the wrong layer. Teams often automate approvals but not provisioning, which keeps the bottleneck alive. The real goal is reducing time-to-identity, not digitizing ticket forms.
- Partial coverage. A Zero Trust control that covers 80 percent of services still leaves a large untrusted surface. Exceptions grow around the gaps.
- Fragile pipelines. If the automation fails regularly, engineers will route around it. Reliability is part of the security model.
A useful checkpoint is to ask whether your automation makes the secure path the fastest path.
If the answer is no, the system is still relying on heroic effort. Automation should feel boring. When it is noisy or unreliable, it becomes its own source of risk.
Actionable takeaways
- Inventory every identity source. If you cannot list your identity authorities, you cannot automate them.
- Automate provisioning and deprovisioning first. This closes the gap that creates long-lived credentials.
- Treat policy as code. Version it, review it, and deploy it like any other critical system.
- Build drift detection into operations. Zero Trust needs continuous validation, not quarterly audits.
- Make the secure path the default path. If automation is optional, Zero Trust becomes optional too.
Zero Trust succeeds when it becomes invisible. That invisibility is created by automation.
Without it, the model collapses under its own operational weight.
2026 Perspective
The tooling for identity and policy-as-code has matured, but the hardest part is still operational discipline.
Zero Trust efforts stall when automation is treated as a project rather than a control plane. The teams that succeed make identity and policy changes feel as routine as deploys.