What MSPs Get Wrong About Securing AI: 6 Risks Already Sitting in Your Clients' Environments

Artificial intelligence is moving into businesses faster than many security teams can govern it.

OpenText's 2025 Global Managed Security Survey found that AI-driven growth is accelerating across the channel, yet only around half of MSPs feel fully prepared to guide customers through AI adoption. At the same time, AI expertise has become one of the most important attributes customers look for in a service provider.

Similarly, OpenText's 2026 Threat Report found that phishing attacks jumped 206% year over year in 2025, while a single data breach can cost $4.4 million.

The challenge is that many organizations are already using AI, whether IT knows about it or not. Employees are experimenting with AI assistants, uploading documents to public tools and connecting AI services to business applications. In many cases, the risks are already present before a formal AI strategy exists.

Here are six AI security risks MSPs frequently overlook—and which may already exist within customer environments.

1. Shadow AI Is Growing Faster Than Governance

What is shadow AI?

Shadow AI refers to employees using AI tools without formal approval, oversight or security review.

Much like shadow IT, it often emerges when users discover tools that help them work faster and begin using them independently. The problem is that organizations may have little visibility into what information is being shared, where data is stored or how outputs are being used.

Common examples include:

Many organizations focus on approved AI projects while missing the AI activity already happening across the business.

2. Sensitive Data Is Being Shared With AI Tools

Why is data exposure a major AI risk?

AI systems are only as safe as the information users provide them.

Employees may unknowingly upload customer records, financial information, intellectual property or confidential business data into AI applications. Once information leaves a controlled environment, organizations can lose visibility over how it is stored and processed.

MSPs should help customers assess:

The biggest AI security problem often isn't the model itself, but the data being entered into AI applications.

3. Permissions Problems Become AI Problems

How does identity affect AI security?

AI tools can only access what users already have permission to access.

That sounds reassuring until organizations discover years of excessive permissions, poorly managed file shares and inconsistent access controls. AI can make information easier to find and surface, exposing governance issues that previously remained hidden.

Before scaling AI, organizations should evaluate:

Many AI security challenges are actually identity and governance challenges in disguise.

4. AI Adoption Is Outpacing Security Training

Are employees prepared for AI-enabled attacks?

Not always.

Threat actors are increasingly using AI to create more convincing phishing emails, fraudulent communications and social engineering attacks. OpenText's 2026 Threat Report found that phishing attacks rose 206% year over year in 2025, reflecting how quickly attackers are scaling volume and precision. OpenText's Managed Security Study also notes that AI is improving the realism, quality and personalization of phishing campaigns, making them harder to detect.

Security awareness programs should now cover:

As AI improves attacker capabilities, employee education becomes even more important.

5. Organizations Focus on Productivity But Ignore Resilience

What happens when an AI-dependent process fails?

Many AI discussions focus on efficiency gains while overlooking operational resilience.

As organizations embed AI into workflows, customer service processes and business operations, disruptions can have broader consequences. Security, backup and recovery planning must evolve alongside AI adoption.

That gap is already visible in ransomware readiness. OpenText's 2026 Threat Report found that while 95% of companies believe they can recover from ransomware, only 15% actually do. For MSPs, that creates a clear advisory opportunity around realistic recovery planning, testing and managed resilience services.

Resilience considerations include:

Customers increasingly care about continuity and recovery, not just prevention.

6. Too Many Tools Create New Security Gaps

Can AI increase complexity?

Yes.

Many organizations are introducing AI capabilities alongside existing security, data protection and management platforms. Without consolidation, this can increase operational complexity, reduce visibility and create governance challenges.

In fact, MSPs in the 2026 Cybersecurity Insiders’ Report identified fragmented tools, limited visibility and lack of integration as the biggest obstacle to effective security operations.

MSPs can help reduce risk through:

The easier an environment is to manage, the easier it becomes to secure.

As AI adoption accelerates, partners that address these challenges early will be better positioned to protect customers while creating new advisory, security and managed services opportunities.