Managed service providers are used to helping customers tackle Shadow IT. Employees signed up for unsanctioned file-sharing platforms, collaboration tools and cloud applications without involving IT, creating security risks that often went un-noticed until something went wrong. Most MSPs responded by helping customers improve visibility, establish governance and regain control over their technology estates.
That challenge has not disappeared. But it has evolved.
Unmanaged AI applications are an increasingly common source of technology risk. Employees are connecting AI-powered meeting assistants to Microsoft 365, using generative AI tools to draft documents, summarise reports and analyse spreadsheets, installing browser extensions that promise productivity gains and authorising AI applications to access corporate email, calendars and cloud storage. In many organisations, these tools are in use long before security teams have an opportunity to assess the risks.
The result is Shadow AI, which is a significant new visibility challenge for organisations. Unlike Shadow IT, organisations are dealing with both standalone AI applications and AI capabilities embedded within existing SaaS platforms. The pace of innovation means adoption often happens organically, so IT teams are trying to catch up with what is already being used across the business.
Employees are not trying to bypass security policies or create unnecessary risk. They are simply looking for ways to work more efficiently. Generative AI can help write emails, automate repetitive tasks, analyse information, create presentation s and improve customer communications in seconds. For organisations under pressure to improve productivity, these benefits are difficult to ignore.
However, technology adoption is moving far faster than governance. By the time many organisations begin evaluating approved AI platforms, employees have often already adopted consumer AI assistants or enabled AI features within existing business applications. Many security teams have little understanding of how many AI-powered tools are already connected to the organisation, what permissions they have been granted or what business data they can access.
That lack of visibility is a big problem. Every AI application connected to a business environment introduces new questions that organisations need to answer. What information can the application access? Has it been granted permission to read emails, calendars or files? Is sensitive customer information being uploaded to external services? Could confidential intellectual property be retained outside corporate controls? These are even more important in highly regulated sectors where organisations must demonstrate how sensitive data is being protected.
The issue is not that AI is inherently insecure. Many enterprise AI platforms include robust security controls, auditing capabilities and governance features. The greater risk comes when organisations do not know which AI applications are being used, who has authorised them or how they interact with critical business systems. Without that visibility, it is difficult to apply consistent security policies or identify potentially risky behaviour before it leads to an incident.
This changing landscape is a significant opportunity for MSPs. Customers increasingly expect their service providers to deliver proactive security rather than simply respond when something goes wrong. According to WatchGuard’s 2026 MSP Cybersecurity Trends Report, 75% of organisations experienced a cybersecurity incident in the past year, while 44% say they are willing to pay more for AI-driven detection and response, and 47% value 24/7 monitoring and faster response enough to pay a premium. Shadow AI sits squarely within those expectations, creating another area where customers are looking to their MSP for guidance before a security issue develops into a business problem.
Rather than asking customers whether they are using AI, MSPs are in a position to demonstrate exactly where AI is already present within their environments. Identifying connected applications, reviewing OAuth permissions, monitoring cloud identities and highlighting governance gaps allows providers to have much more meaningful discussions with customers. Instead of talking about hypothetical risks, they can present evidence of real activity and recommend practical steps to reduce exposure.
Rather than telling customers not to use AI, MSPs can help organisations to use AI securely. Helping customers adopt AI with appropriate visibility and governance helps businesses to reap the productivity benefits while reducing unnecessary security and compliance risks.
As AI adoption accelerates, cloud visibility is an essential layer of modern managed security. Understanding which AI-powered applications are connected, identifying risky OAuth permissions, monitoring cloud identities and detecting emerging SaaS threats will enable MSPs to support customers as they embrace AI without losing sight of security.
Solutions that provide continuous visibility across cloud environments are valuable because manually tracking AI adoption is not practical. New AI assistants, integrations and SaaS capabilities are appearing almost every week, making automated discovery and monitoring essential if organisations are to maintain an accurate understanding of their cloud environment.
AI is already embedded within many customer environments. For MSPs, that presents an opportunity to deliver proactive security, strengthen customer trust and build higher-value managed services around one of today’s fastest-growing cloud risks.
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