As organisations scale IoT, OT, and edge deployments, they are discovering a hard truth: manual security processes do not scale. In 2026, the number of machine identities, devices, sensors, gateways, workloads, and embedded systems, has eclipsed human identities by several orders of magnitude. Machine identity refers to the unique identifiers assigned to non-human entities, such as devices, applications, and servers. Each of these machines must authenticate, communicate securely, and comply with policy, often without human intervention.

This is where machine identity automation becomes essential. Rather than treating identity as a one-time provisioning task, automation manages trust continuously, from the moment a device is discovered to the point it is decommissioned. Machine identities are digital certificates that serve as proof of a machine’s authenticity on a network. For security leaders, it has become the only viable way to secure complex, distributed environments.

The rapid growth of cloud, DevOps, and automation has spurred an explosion in machine identities, creating a critical need for robust management strategies. Organizations must manage all identities, including machine identities, in one place to improve IT efficiency and effectiveness.

What Is Machine Identity Management and Automation?

Machine identity automation is the automated management of cryptographic identities for non-human entities. Digital certificates are the foundation of machine identity, acting as digital passports that authenticate machines and enable secure connections. These identities are typically based on certificates, keys, and hardware-backed credentials rather than passwords.

Automation ensures that identities are issued, rotated, validated, and revoked without manual effort. Certificate management involves tracking every certificate throughout its lifecycle, from issuance to renewal and eventual expiration. Machine identities often have short lifespans and require frequent updates, renewals, or deactivations to maintain security. Automation replaces brittle spreadsheets, static credentials, and ad-hoc scripts with policy-driven workflows that operate at scale.

In IoT and OT environments, automation is critical because devices may be deployed for years, operate continuously, and exist outside traditional IT boundaries. Effective management of machine identities demands secure handling of secrets, such as API keys and certificates, which are essential for authenticating machine communication. Manual management is labor-intensive and error-prone, while automated solutions reduce labor costs and security risks. AI enhances automation in machine identity management by providing the ability to learn, adapt, and predict. Machine credentials, such as certificates and API keys, must be managed securely throughout their lifecycle.

Why Manual Identity Management Fails at IoT Scale

Historically, many organisations relied on manual management or semi-manual processes to handle device identities. Certificates were issued during deployment and then forgotten. Keys were reused across fleets. Expiry dates were tracked inconsistently, if at all.

Manual management is labor-intensive and error-prone, increasing security risks and the likelihood of human error. Poorly managed machine identities can lead to unauthorized access to sensitive systems. At small scale, these approaches appeared workable. At IoT scale, they introduce serious risk. Expired certificates can cause outages and open doors for attackers to exploit vulnerabilities. Compromised keys may go undetected. Revoking access from a single device can take days, if it is possible at all.

Organizations struggle with visibility and control over machine identities, leading to security gaps and potential vulnerabilities. The lack of structured oversight can lead to security blind spots in machine identity management. Manual processes also struggle to support compliance. Auditors increasingly expect evidence of consistent, repeatable controls. Ad-hoc identity management does not meet this standard, highlighting the need for machine identities to be properly managed.

Discovery: The First Step in Identity Automation

Machine identity automation begins with discovery. Before identities can be issued or managed, organisations must understand what devices are actually present. Auditing machine identities is essential for maintaining visibility and compliance, enabling continuous oversight of device credentials and digital certificates.

Discovery in IoT environments goes beyond simple asset lists. It involves identifying devices based on network behaviour, protocols, and communication patterns. This includes devices that are unmanaged, legacy, or deployed by third parties. However, organizations often lack visibility into their machine identities, making management and auditing difficult and increasing the risk of potential vulnerabilities.

Effective discovery provides a continuously updated view of the device estate, forming the foundation for all subsequent security controls. Centralized management of machine identities and discovery processes is key to maintaining control and reducing vulnerabilities across complex IoT environments.

Automated Onboarding and Identity Issuance

Once a device is discovered, automation enables secure onboarding. Onboarding processes use digital certificates and machine credentials to establish secure connections and secure machine identities, ensuring that digital credentials are protected from the outset. Rather than relying on pre-shared secrets or manual configuration, devices are issued unique cryptographic machine credentials at first connection. Automation tools play a critical role in onboarding and managing credentials at scale, reducing manual effort and enhancing security.

This process establishes trust from the outset. Each device receives its own credentials, tied to policy and usage context. Identities can be bound to hardware, location, or function, reducing the risk of impersonation. Continuous verification and real-time monitoring, often powered by AI, are essential for maintaining trust and detecting anomalies throughout the device lifecycle.

Automated onboarding is especially valuable in environments where devices are deployed remotely or at high volume, such as manufacturing, energy, automotive, and smart infrastructure.

Policy-Based Access and Zero Trust Enforcement

With identities in place, automation allows organisations to enforce Zero Trust principles consistently. Access controls and access management are used to enforce policies for both human and machine identities, ensuring that access is granted based on verified identity and policy, not on network location or implicit trust.

Policies can define what a device is allowed to access, how it may communicate, and under what conditions trust should be re-evaluated. Managing privileged access and implementing controlled access are critical to prevent privilege escalation and exposure of secrets, especially as compromised machine identities can lead to significant security risks. Effective governance of identity and access for both human and machine identities helps restrict access automatically if a device deviates from expected behaviour or fails validation checks.

This approach replaces static network rules with dynamic, identity-driven controls that adapt to risk in real time.

Lifecycle Management: Rotation, Renewal, and Revocation

One of the most critical aspects of machine identity automation is lifecycle management. Certificate lifecycle management is essential for tracking every certificate throughout its lifecycle, from issuance to renewal and eventual expiration, to ensure full visibility, automation, and compliance. Automating the machine identity lifecycle, including the issuance, rotation, and revocation of certificates and keys, is vital for maintaining security and operational efficiency in complex environments.

Machine credentials, such as digital certificates and cryptographic keys, must be managed securely to prevent outages and vulnerabilities. If certificates expire, they can cause service outages and create opportunities for attackers to exploit vulnerabilities. Storing, rotating, and managing these credentials centrally ensures they are managed securely and reduces the risk of misuse or breaches.

Automation handles these processes transparently. Credentials are renewed in the background, ensuring continuity while maintaining strong cryptographic hygiene. When devices are retired, compromised, or repurposed, identities can be revoked immediately.

This capability dramatically reduces both security risk and operational overhead.

Supporting Compliance Through Automation

Regulatory frameworks increasingly emphasise continuous control, auditability, and risk management. Machine identity automation directly supports these requirements by providing clear, verifiable processes. Auditing machine identities is essential for compliance, as automated oversight ensures that device credentials and digital certificates are continuously monitored for vulnerabilities and policy adherence.

Automated systems can generate evidence of identity issuance, policy enforcement, and lifecycle events. This makes it easier to demonstrate compliance with frameworks such as NIST guidance, the Cyber Resilience Act, and sector-specific regulations. Identity security is a key component of meeting regulatory requirements, helping organizations manage and protect both human and machine identities within a unified framework. Unmanaged machine identities can lead to compliance violations and regulatory issues, highlighting the need for robust automation and oversight.

Rather than treating compliance as a periodic exercise, automation embeds it into everyday operations.

Agentless Automation for Constrained Environments

Many IoT and OT devices cannot support agents or frequent updates. Machine identity automation addresses this challenge through agentless approaches that manage identities externally, which is especially critical in dynamic environments where physical machines, mobile devices, and other assets are constantly changing and scaling.

By operating at the network and infrastructure level, automation can secure devices without modifying them. This is essential in environments where safety, certification, or uptime requirements limit what can be installed on devices. Protecting machine identities and managing non-human identities—including those of physical machines, mobile devices, and other constrained or agentless devices—ensures robust authentication, compliance, and security across the entire infrastructure.

Agentless automation extends identity-based security to the parts of the estate that traditional tools cannot reach.

Business Benefits Beyond Security

While security is the primary driver, machine identity automation also delivers measurable business benefits. By improving operational efficiency and aligning with business requirements, it streamlines the management of machine identities and automates complex processes. This not only reduces the time and effort required to deploy new devices, supports faster incident response, and lowers the risk of outages caused by expired credentials, but also helps strengthen the organization’s security posture.

For organisations pursuing digital transformation, automation provides the confidence to scale IoT initiatives without proportionally increasing risk or cost. As the proliferation of machine identities expands the attack surface, automated identity management is essential for reducing vulnerabilities and improving the overall security posture.

Final Thoughts

In 2026, machine identity automation is no longer optional. It is the foundation upon which secure, scalable IoT and edge environments are built. A comprehensive identity strategy for managing machine identities is essential in today’s distributed IT environment, where digital certificates, credentials, and devices span clouds, edge, and on-premise systems.

By automating discovery, onboarding, policy enforcement, and lifecycle management, organisations can move from reactive security to proactive control. Security teams play a critical role in implementing machine identity security, ensuring secure machine to machine communication, and supporting Zero Trust architectures. AI can transform traditional identity management processes into a continuous feedback loop, creating a living, learning identity fabric. Identity becomes a living system, continuously adapting to change rather than lagging behind it.

Platforms developed by companies such as Device Authority exemplify this approach, enabling organisations to move from fragmented device security to unified, identity-driven protection.