The digital landscape has undergone a seismic shift. While organizations once worried primarily about managing employee access to systems, today's reality is far more complex. The explosive growth of AI-powered SaaS tools has introduced a new challenge: securely and efficiently managing both human and non-human identities across an ever-expanding ecosystem.
As organizations adopt automation to streamline operations, the boundaries between human-operated accounts and system-driven identities have become increasingly blurred. Marketing teams deploy AI-powered content generators that need access to brand assets. Sales departments rely on chatbots that pull sensitive customer data from CRMs. Engineering teams create service accounts with broad permissions to enable CI/CD pipelines. Each of these scenarios creates new identity types that exist outside traditional IAM frameworks.
This evolution demands a fundamental rethinking of identity management. To operate securely at scale in today's AI-powered landscape, organizations need a comprehensive approach that addresses the full spectrum of identities, ranging from employees to contractors to machine learning algorithms. This is precisely where SaaS Management Platforms like Josys make their most significant impact, providing the visibility, control, and automation needed to manage identities across the modern technology stack.
The New Identity Landscape in AI-Driven SaaS Workflows
Traditional Identity Management
For decades, identity management focused almost exclusively on human users. The formula was straightforward: provision accounts for employees based on their roles, manage password policies, implement single sign-on, and deprovision access when people leave the organization.
This human-centric approach worked adequately when most access was directly tied to individual employees. IT teams could map organizational charts to permission structures, conduct periodic access reviews, and maintain reasonable security through role-based access control (RBAC).
However, as SaaS adoption accelerated and automation became central to business operations, this model began showing significant limitations. The traditional focus on human identities left critical gaps in how organizations managed the growing number of non-human actors in their environments.
Rise of Non-Human Identities
Today's enterprise environments are populated by an increasingly diverse array of non-human identities:
- API keys that enable system-to-system communication
- Service accounts that run background processes
- Automation bots that execute routine tasks
- AI agents that make decisions and access data independently
- Scheduled scripts that perform regular maintenance
- Webhooks that trigger actions based on events
These non-human identities perform critical functions across the business. Consider these common examples:
- A customer service chatbot that needs access to your CRM to retrieve customer histories and purchase records
- AI-powered content moderation tools that scan user uploads against sensitive data repositories
- Automated billing scripts that access financial systems to process recurring payments
- Marketing automation tools that pull customer segments from multiple data sources
- Data pipelines that transfer information between applications for analytics purposes
The scale is staggering. Research from Gartner suggests that by 2025, non-human identities will outnumber human identities by at least 5:1 in most enterprises. This isn't just a minor extension of traditional IAM—it represents a fundamental shift in how we must think about identity governance.
The Unique Challenge of Non-Human Identities
What makes non-human identities particularly challenging from a security perspective is their persistence. Unlike human users who log in periodically and have natural usage patterns, machine identities often maintain continuous access. They rarely "log out," seldom change passwords, and frequently have elevated privileges to perform their functions efficiently.
This persistence makes non-human identities especially attractive targets for attackers. A compromised employee account might be detected when the employee notices unusual activity or when the account exhibits abnormal behavior. A compromised service account, however, might continue operating normally while extracting sensitive data or executing malicious code—all without triggering obvious alerts.
The result is an expanded attack surface that many organizations are ill-equipped to monitor and secure. Without specialized tooling designed to manage both human and non-human identities cohesively, security teams face a growing blind spot in their defenses.
Why This Matters Now
Explosion in SaaS App Usage
The average enterprise now uses over 300 SaaS applications, according to recent research from Productiv. Mid-sized companies typically employ between 40 and 60 SaaS tools, while even small businesses regularly maintain 20+ cloud applications. This proliferation creates an identity management challenge of unprecedented scale.
Each application introduces its own identity store, authentication methods, and access controls. Without centralized management, organizations face:
- Fragmented visibility across dozens or hundreds of isolated identity silos
- Inconsistent policy enforcement, as each application implements security differently
- Administrative overhead as IT teams struggle to manually manage accounts across systems
- Security gaps where overlooked applications operate outside governance frameworks
The sheer volume of SaaS applications has made traditional, manual identity management approaches unsustainable.
AI Everywhere: The Multiplication Effect
The rapid adoption of AI tools has compounded this challenge by introducing a new layer of non-human identities. 78% of enterprises now use some form of AI-powered automation in their operations (McKinsey)
This AI revolution has created an explosion of machine identities that need access to sensitive systems and data. Each automated workflow, each integration between systems, and each AI-powered tool introduces new non-human identities that must be secured, monitored, and governed.
Security Risks: The Identity Blind Spot
The combination of SaaS proliferation and AI adoption has created several critical security risks:
Overprivileged Accounts
Non-human identities frequently receive excessive permissions due to convenience or technical limitations. A developer might grant a service account full database access rather than crafting limited permissions, creating unnecessary risk. Research from the Ponemon Institute found that 63% of organizations have experienced security incidents related to overprivileged machine identities.
Lack of Visibility
Most organizations struggle to maintain an accurate inventory of which systems have access to what data. This problem becomes exponentially more complex when machine identities enter the picture. According to a recent survey by the Identity Defined Security Alliance, only 34% of organizations can identify all machine identities in their environment.
Compliance Gaps
Regulatory frameworks like GDPR, HIPAA, SOC2, and ISO 27001 all require comprehensive identity governance—including non-human identities. Organizations that fail to properly manage machine access face significant compliance risks and potential penalties.
Business Risks: Beyond Security
The implications extend beyond security concerns. Organizations with poor identity management across human and non-human users face:
- Operational disruptions occur when critical automated processes lose access unexpectedly
- Inefficient resource utilization occurs when abandoned but still-active machine identities consume licenses and computing resources
- Delayed innovation is slowed by security concerns about machine identities, which slow the adoption of new technologies
- Increased technical debt as temporary access solutions become permanent without proper governance
The bottom line: In today's AI-powered SaaS environment, comprehensive identity management isn't just a security best practice—it's a business imperative that directly impacts operational efficiency, compliance posture, and innovation capacity.
Core Challenges in Managing Both Human and Non-Human Identities
Lack of Centralized Visibility
The most fundamental challenge organizations face is simply knowing what exists. Without specialized tooling, IT and security teams struggle to answer basic questions:
- How many service accounts exist across our SaaS ecosystem?
- Which APIs have active keys, and who created them?
- What permissions do our automation tools actually have?
- Which machine identities can access sensitive data?
This visibility gap is exacerbated by shadow IT—the unsanctioned applications and services that teams adopt without formal IT approval. While shadow IT has long been a challenge for human identities, it's even more problematic for machine identities, which often emerge organically as teams build automations and integrations.
The typical enterprise has 20-40% more machine identities than they're aware of, according to research from CyberArk. These unknown identities represent a significant blind spot that can't be secured or governed effectively.
Lifecycle Management Gaps
Human identities follow relatively predictable lifecycles. Employees join the organization, change roles, and eventually leave. While executing these transitions perfectly remains challenging, most organizations have established processes for managing human identity lifecycles.
Non-human identities, however, typically lack similar governance. Consider these common lifecycle management gaps:
Inconsistent Onboarding
When developers create new service accounts or API keys, they rarely follow standardized processes. Each team might take a different approach, leading to inconsistent documentation, permissions, and security controls.
Missed Offboarding
When projects end or systems change, the associated machine identities often remain active indefinitely. Unlike human departures, which trigger clear offboarding workflows, the "end of life" for machine identities is rarely formalized or tracked.
Poor Credential Rotation
Best practices dictate regular credential rotation for sensitive systems. While human users are increasingly protected by MFA and modern authentication methods, machine identities often rely on long-lived secrets that may remain unchanged for years.
Orphaned Accounts
When the humans who created machine identities leave the organization, knowledge of those accounts often leaves with them. This makes "orphaned" machine identities that continue operating without clear ownership or oversight.
A study by the Ponemon Institute found that 53% of organizations have experienced security incidents related to orphaned machine identities—making this one of the most significant practical risks in modern environments.
Access Control Complexity
Managing appropriate access for human users is challenging enough. For machine identities, the complexity increases substantially:
- Role-Based Access Control (RBAC) limitations: Traditional RBAC models work reasonably well for human users but often break down for machines, which may need highly specific or unusual permission combinations.
- Attribute-Based Access Control (ABAC) complexity: More flexible ABAC approaches can better accommodate machine needs but introduce significant implementation complexity.
- Just-In-Time access challenges: While modern security practices favor providing access only when needed, many machine identities require persistent access to function correctly.
- Principle of least privilege difficulties: Determining the minimum necessary permissions for a complex automated process is often more art than science, leading to overprivileged accounts.
These challenges often lead to a problematic compromise: broad permissions granted to machine identities to ensure functionality, at the expense of security.
Audit & Compliance Burden
Demonstrating compliance requires comprehensive visibility into who—and what—has access to sensitive systems and data. For organizations with significant numbers of machine identities, this creates substantial challenges:
- Incomplete identity inventories: Without specialized tools, most organizations cannot produce a complete list of all machine identities.
- Poor attribution: Determining who created or is responsible for specific machine identities often requires manual investigation.
- Limited activity logging: While human activity is typically well-logged, machine identity actions may be recorded inconsistently across systems.
- Access certification difficulties: Regular access reviews become exponentially more complex when hundreds or thousands of machine identities must be evaluated.
These challenges create significant friction during audits and can lead to compliance findings even in otherwise well-governed organizations.
How SaaS Management Platforms Like Josys Solve the Problem
Comprehensive Visibility
The foundation of effective identity management is complete visibility—you can't secure what you can't see. Modern SaaS Management Platforms (SMPs) like Josys address this challenge by providing a unified view across your entire SaaS ecosystem.
Josys specifically offers:
- Automated discovery of all SaaS applications in use, including shadow IT
- Identity mapping that catalogs both human and non-human users across applications
- Relationship visualization showing which identities have access to which resources
- Permission analysis reveals what actions each identity can perform
- Usage monitoring, tracking how identities interact with systems
This comprehensive visibility creates a single source of truth for all identities—human and machine alike. Rather than piecing together information from dozens of isolated admin consoles, security teams gain a holistic view of their identity landscape.
Lifecycle Automation
Managing identity lifecycles manually across hundreds of SaaS applications is practically impossible. Josys solves this challenge through intelligent automation that addresses both human and machine identities:
For Human Identities:
- Automated provisioning based on HR system changes
- Role-based access assignment using predefined templates
- Self-service access requests with appropriate approval workflows
- Immediate deprovisioning when employees change roles or leave
For Machine Identities:
- Structured creation processes with mandatory documentation
- Automatic expiration dates for temporary access
- Regular credential rotation on configurable schedules
- Ownership tracking to prevent orphaned accounts
- Automated decommissioning when associated projects end
By integrating both human and machine identities into a single lifecycle management framework, Josys eliminates the governance gaps that typically exist between these identity types.
Role & Policy Enforcement
Consistent policy enforcement across hundreds of SaaS applications has traditionally been nearly impossible. Josys addresses this challenge through centralized policy management that extends to both human and non-human identities:
- Unified policy framework that applies consistently across all applications
- Least privilege templates for common machine identity types
- Continuous policy verification to detect and remediate drift
- Contextual access controls that adapt based on risk signals
- Automated remediation of policy violations
This approach ensures that all identities—regardless of type—adhere to organizational security standards and compliance requirements.
Credential Governance
Machine identities often rely on persistent credentials like API keys, service account passwords, and certificates. Josys provides specialized capabilities to secure these critical assets:
- Centralized credential inventory tracking all machine identity secrets
- Automated rotation schedules based on sensitivity and compliance requirements
- Secure distribution of updated credentials to dependent systems
- Usage analytics to identify unused or suspicious credential usage
- Emergency revocation capabilities for incident response
By bringing machine credentials under governance, organizations can eliminate one of their most significant security blind spots.
Audit-Ready Reporting
Demonstrating compliance requires comprehensive, accurate reporting on access controls. Josys transforms the audit process through:
- Pre-built compliance reports aligned to common frameworks (SOC2, ISO, GDPR, etc.)
- Unified access logs across all applications and identity types
- Historical access records showing changes over time
- Attestation workflows for access certification
- Evidence collection that simplifies audit preparation
By unifying reporting across human and machine identities, Josys eliminates the fragmented, manual processes that typically plague compliance efforts.
AI-Optimized Security
Beyond basic management, modern SMPs like Josys leverage AI to enhance security across all identity types:
- Anomaly detection identifies unusual access patterns
- Risk scoring for both human and machine identities
- Predictive analytics to forecast potential security issues
- Automated remediation recommendations based on best practices
- Continuous monitoring for suspicious activity
These AI capabilities are particularly valuable for machine identities, which often operate according to predictable patterns that make anomalies easier to detect.
Conclusion
The New Identity Imperative
As we've explored throughout this article, the modern SaaS landscape demands a fundamental evolution in how we think about identity management. The traditional focus on human identities is no longer sufficient in environments where machine identities often outnumber human users by 5:1 or more.
In the age of AI-driven SaaS workflows, managingall identities—not just human ones—has become essential for security, compliance, and operational efficiency. Organizations that fail to address this new reality face increasing risks from overprivileged accounts, orphaned identities, and inadequate governance.
The good news is that solutions like Josys now provide the comprehensive visibility, lifecycle automation, and governance capabilities needed to manage identities holistically across the modern technology stack. By bringing both human and machine identities under unified management, organizations can close critical security gaps while simultaneously reducing administrative overhead.
Take the Next Step
Ready to transform how your organization manages identities across your SaaS ecosystem? Josys offers a complete solution for both human and machine identity management, designed specifically for the challenges of modern, AI-enhanced environments.
Book a free demo to see how Josys can help your organization:
The future of identity management is here—and it encompasses everyone and everything that accesses your systems. Is your organization ready?
