AI’s Hidden Identity Risk for MSPs

Organizations are rapidly integrating AI into everyday business operations. Teams are using Microsoft Copilot and Gemini to summarize meetings, developers are accelerating software delivery with coding copilots and customer service teams are deploying AI-powered chatbots to improve response times. While these initiatives are viewed through the lens of productivity and innovation, they are also reshaping organizations’ identity environments in ways that frequently go unnoticed.

Every AI deployment relies on trusted access to business systems. Whether an AI assistant connects to Microsoft 365, Salesforce, SharePoint or an internal knowledge base, it authenticates, retrieves information and performs actions using credentials and permissions that must be granted and managed. Therefore, every deployment introduces another identity that must be secured. 

Across client meetings and executive discussions, AI conversations typically revolve around productivity gains, governance policies and acceptable use. There is limited focus on the identities created to support these technologies. 

So, what new identities are we creating in the process?

The answer has implications that extend far beyond AI adoption. 

How AI is expanding the identity attack surface for MSPs

Let’s consider what happens when a business deploys a new AI tool:

A marketing team connects an AI writing assistant to SharePoint. The sales team enables an AI-powered CRM assistant. A customer service manager launches a chatbot connected to internal documentation. Operations automates repetitive workflows using AI-driven orchestration. 

Each deployment appears to be an isolated productivity enhancement. From a security perspective, however, the implications run much deeper.

Every one of these solutions requires trusted access to perform the tasks it’s designed to execute. Some authenticate through OAuth connections, while others rely on API keys, service accounts, machine credentials or access tokens. Each receives permission to retrieve information, interact with business applications and execute actions on behalf of users. Individually, these identities rarely attract much attention. Collectively, they begin expanding what many organizations never measure: their identity attack surface.

The rapid expansion of AI across the enterprise is making this challenge difficult to ignore. According to Microsoft’s 2025 Work Trend Index, 82% of business leaders say this is a pivotal year to rethink core aspects of strategy and operations through AI. The report also found that 46% of organizations are already using AI agents to fully automate workflows or business processes, illustrating how quickly AI is moving from experimentation into day-to-day operations. 

Those numbers illustrate more than increased AI use.

They point to a growing number of applications, workflows and automated processes requiring trusted access across enterprise environments.

Why Non-Human Identities (NHIs) create hidden risks

Traditional identity programs were built around people. An employee joins the organization, receives an account, is granted access to the appropriate systems and eventually has that access removed when the employee changes positions or leaves the company. While that process isn’t always seamless, it follows a predictable lifecycle with defined ownership.

AI doesn’t.

An AI assistant may authenticate through an OAuth token. A workflow automation platform may rely on multiple service accounts and API keys. An autonomous agent may access several business applications using machine credentials that operate continuously without direct human interaction. Unlike employee accounts, these identities are often created instantly during application setup or by individual administrators, developers and business users connecting AI tools to existing systems.

Many of these identities exist outside the processes organizations already have in place to govern employees. Some remain active long after they’re needed because removing them can interrupt workflows or break integrations. Over time, organizations accumulate hundreds or even thousands of identities that aren’t tied to a person, yet possess legitimate access to key business systems.

Security professionals collectively refer to these as Non-Human Identities (NHIs): digital identities used by applications, services, workloads and automated processes rather than employees. While the term may be unfamiliar to some organizations, the concept is not. Every API key, OAuth connection, service account, machine credential and AI agent acting on behalf of a user represents another identity with privileged access that must be managed throughout its lifecycle. 

The number of NHIs isn’t standing still. Every new AI deployment, automated workflow and system integration introduces credentials, service accounts and machine identities that require governance. As more applications, workflows and systems become interconnected, maintaining visibility becomes increasingly difficult. 

This isn’t simply an inventory problem. It’s a visibility and control problem.

Organizations can’t effectively secure identities they don’t know exist, regularly review permissions they can’t see or remove access they don’t realize has been granted.

Unfortunately, attackers don’t have to worry about that limitation.

Why attackers target unmanaged machine identities

Cybercriminals don’t distinguish between human and machine identities. They’re simply looking for the fastest path into valuable systems and sensitive data. 

For years, phishing campaigns and credential theft primarily targeted employees because user accounts represented the most direct route into an organization’s environment. That reality hasn’t changed, but the number of potential entry points has.

Today’s attackers are increasingly exploiting API keys, service accounts, access tokens and machine credentials because these identities often operate with broad permissions, persistent access and much less oversight than traditional user accounts. Unlike an employee account, a service account won’t question an unexpected request, an API key won’t report suspicious activity and an AI agent can’t recognize that it’s interacting with a malicious system. If these identities are compromised, they often provide attackers with exactly what they need: legitimate access.

According to Red Canary’s 2025 Threat Detection Report, identity attacks increased by 850% from 2024 and accounted for 53% of overall detection volume in 2025, underscoring attackers’ growing reliance on credential theft and identity-based attack techniques. 

Each new AI deployment introduces another machine identity, service account or credential into the environment. 

The challenge isn’t simply that more identities exist. It’s that many receive permissions that exceed what’s necessary, remain active longer than intended or operate without continuous monitoring. Individually, these issues may appear insignificant. Together, they create an expanding collection of trusted identities that attackers can exploit.

The more organizations choose to automate, the more critical it becomes to understand not only who has access to critical systems, but also what has access.

Why AI identity security matters for MSPs

For most organizations, managing this growing identity ecosystem isn’t just a technical challenge; it’s a visibility challenge.

Many businesses simply don’t know how many NHIs exist across their environments, what systems they can access or whether those permissions are still necessary. AI initiatives are often driven by individual departments, developers or business units focused on solving immediate challenges. Long-term identity governance is rarely part of the conversation. 

For MSPs, this is where expertise becomes differentiation. 

Historically, MSPs have helped customers secure endpoints, manage infrastructure and deploy cybersecurity solutions. As clients continue integrating AI into their operations, they will rely on trusted advisors to help govern the credentials, permissions and machine identities these technologies introduce.

Helping clients navigate this shift begins with a different set of questions: 

• What AI applications currently have access to critical business systems?
• Which service accounts and API keys are still actively required?
• Who owns each machine identity?
• Are permissions aligned with least-privilege principles?
• How are credentials rotated, monitored and protected?

By initiating these discussions and revisiting them as AI environments evolve, MSPs elevate their role from technology provider to strategic advisor. By helping clients govern AI-related identities, MSPs can minimize long-term risk while enabling responsible AI adoption. 

How KeeperMSP can help clients build a secure AI foundation 

Understanding the problem is only the first step. Helping clients address it requires the right identity security foundation. 

For MSPs, that means helping clients implement a framework capable of governing privileged access consistently across both human and machine identities. It means securing credentials, enforcing least-privilege access, protecting secrets, monitoring privileged sessions and maintaining visibility throughout the identity lifecycle. 

Rather than treating AI-related access as a separate security challenge, MSPs should encourage clients to incorporate it into their broader identity security strategy. Whether access belongs to an employee, an application, an AI agent or an automated workflow, the same core principles should apply: verify access, enforce least privilege, protect credentials and continuously monitor activity. A unified approach reduces complexity while ensuring clients maintain consistent security controls as their environments continue to evolve. 

KeeperMSP was built with these challenges in mind. Through its zero-knowledge security architecture, enterprise password management, Privileged Access Management (PAM), secrets management and secure remote access capabilities, Keeper enables providers to help clients secure the credentials, secrets and privileged access pathways that attackers love to target. Instead of relying on disconnected tools, MSPs can manage both human and machine identities through a single platform built on zero-trust principles and continuous access governance.  

For MSPs, the value extends well beyond technology. It provides the visibility, control and scalability needed to help clients embrace AI without allowing their identity attack surface to outpace their security strategy. 

Every AI deployment creates new identity security risks

Every AI deployment expands an organization’s identity ecosystem, and with it, the responsibility to govern every new identity with the same rigor as its human counterparts. Organizations that recognize this connection early on will be better positioned to innovate without unnecessarily expanding their attack surface. 

For MSPs, helping their managed companies understand and govern these identities represents far more than another technology deployment. It places MSPs at the forefront of one of the most significant shifts in cybersecurity since the move to cloud computing. By helping clients navigate the challenges created by AI, MSPs can reinforce their role as indispensable advisors while enabling organizations to keep pace with innovation without compromising visibility or control. 

Because every AI deployment introduces more than a new capability. It introduces another identity to secure.

Explore the Keeper MSP Partner Program and how it helps MSPs address AI’s growing identity footprint.