Shadow AI: A Fatal Flaw for Most Organizations

Learn more about ManageEngine

"Shadow AI represents both the greatest governance risk and the biggest strategic opportunity in the enterprise," said Ramprakash Ramamoorthy, Director of AI Research at ManageEngine. "Organizations that will thrive are those that address the security threats and reframe shadow AI as a strategic indicator of genuine business needs. IT leaders must shift from playing defense to proactively building transparent, collaborative, and secure AI ecosystems that employees feel empowered to use."

The Shadow AI Surge in Enterprises: Insights from the US and Canadian Workplace, a report from ManageEngine based on a survey of IT decision makers (ITDMs) and business employees, investigates the rise of shadow AI — unauthorized AI tools used for work — and identifies critical gaps that organizations need to close if they want to reduce the risks of shadow AI and turn it into a strategic advantage.

The rise: 60% of employees are using unapproved AI tools more than they were a year ago, and 93% of employees admit to inputting information into AI tools without approval.

The risks: 63% of ITDMs see data leakage or exposure as the primary risk of shadow AI. Conversely, 91% of employees think shadow AI poses no risk, not much risk, or some risk that's outweighed by reward.

The rewards: Summarizing notes or calls (55%), brainstorming (55%), and analyzing data or reports (47%) are the top tasks employees complete with shadow AI. Generative AI text tools (73%), AI writing tools (60%), and code assistants (59%) are the top AI tools ITDMs have approved for employee use.

Identifying the Shadow AI Gaps

To turn the use of shadow AI from a liability into a strategic advantage, IT leaders need to close the gaps in education, visibility, and governance revealed by the report. Specifically, a lack of education around AI model training, safe user behavior, and organizational impact is driving systematic misuse. Blind spots continue to grow in organizations, even as IT teams move to approve and integrate AI tools as quickly as possible. Meanwhile, shadow AI proliferates due to inadequate enforcement of established governance policies.

  • 85% of ITDMs report that employees are adopting AI tools faster than their IT teams can assess them.
  • 32% of employees entered confidential client data into AI tools without confirming company approval, while 37% entered private, internal company data.
  • 53% of ITDMs say employees' use of personal devices for work-related AI tasks is creating a blind spot in their organization's security posture.
  • Only 54% of ITDMs report their organizations have implemented clear, enforced AI governance policies and actively monitor for unauthorized use, while 91% have implemented policies overall.

Pivoting to Proactive AI Management

Proactively managing AI means harnessing employee initiative while maintaining security. It delivers the business value discovered in shadow AI but does so via AI tools that are approved by IT. To that end, ITDMs and employees make several strategic recommendations in the report.

  • 63% of ITDMs advise integrating approved AI tools into standard workflows and business applications, 60% suggest implementing clear policies on acceptable AI use, and 55% suggest establishing a list of vetted and approved tools.
  • 66% of employees recommend setting clear policies that are fair and practical, 63% recommend providing official tools that are relevant to their tasks, and 60% advise providing better education on understanding the risks.

"Shadow AI is a fatal flaw for most organizations," said Sathish Sagayaraj Joseph, regional technical head at ManageEngine. "IT teams can't manage risk they can't see — and they can't enable business value that users won't divulge. Proactive AI management unites IT and business professionals in their pursuit of common, organizational goals. That means employees are equipped to understand and avoid AI-related risks, and IT is empowered to help them use AI in ways that drive real business outcomes."

Survey Methodology: In May 2025, ManageEngine commissioned independent market research agency Censuswide to conduct a study of 350 ITDMs and 350 working professionals across the US and Canada, employed in organizations with at least 500 employees and $10M in annual revenue. The survey explored AI usage patterns, security concerns, and governance gaps, with a focus on real-world behaviors across organizations of varying sizes and industries.

Related Links

Hot Topics

The Latest

Clearing the Path to AI: Why Vendor Consolidation Matters Now

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

Explainability Is the New Battleground in AI-Powered Observability

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

Empowering the Human Side of the Autonomous IT Age

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

No Escalations ≠ No Work: Why Visibility in DevOps Matters More Now That AI Is Accelerating Everything

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

Observability Costs Rising Faster Than Value

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Customers Demand Frictionless Experiences - This Is How Retailers Can Provide Them

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

IT's Motivation Crisis Is Really a Process Crisis

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...

Shadow AI: A Fatal Flaw for Most Organizations

Learn more about ManageEngine

"Shadow AI represents both the greatest governance risk and the biggest strategic opportunity in the enterprise," said Ramprakash Ramamoorthy, Director of AI Research at ManageEngine. "Organizations that will thrive are those that address the security threats and reframe shadow AI as a strategic indicator of genuine business needs. IT leaders must shift from playing defense to proactively building transparent, collaborative, and secure AI ecosystems that employees feel empowered to use."

The Shadow AI Surge in Enterprises: Insights from the US and Canadian Workplace, a report from ManageEngine based on a survey of IT decision makers (ITDMs) and business employees, investigates the rise of shadow AI — unauthorized AI tools used for work — and identifies critical gaps that organizations need to close if they want to reduce the risks of shadow AI and turn it into a strategic advantage.

The rise: 60% of employees are using unapproved AI tools more than they were a year ago, and 93% of employees admit to inputting information into AI tools without approval.

The risks: 63% of ITDMs see data leakage or exposure as the primary risk of shadow AI. Conversely, 91% of employees think shadow AI poses no risk, not much risk, or some risk that's outweighed by reward.

The rewards: Summarizing notes or calls (55%), brainstorming (55%), and analyzing data or reports (47%) are the top tasks employees complete with shadow AI. Generative AI text tools (73%), AI writing tools (60%), and code assistants (59%) are the top AI tools ITDMs have approved for employee use.

Identifying the Shadow AI Gaps

To turn the use of shadow AI from a liability into a strategic advantage, IT leaders need to close the gaps in education, visibility, and governance revealed by the report. Specifically, a lack of education around AI model training, safe user behavior, and organizational impact is driving systematic misuse. Blind spots continue to grow in organizations, even as IT teams move to approve and integrate AI tools as quickly as possible. Meanwhile, shadow AI proliferates due to inadequate enforcement of established governance policies.

  • 85% of ITDMs report that employees are adopting AI tools faster than their IT teams can assess them.
  • 32% of employees entered confidential client data into AI tools without confirming company approval, while 37% entered private, internal company data.
  • 53% of ITDMs say employees' use of personal devices for work-related AI tasks is creating a blind spot in their organization's security posture.
  • Only 54% of ITDMs report their organizations have implemented clear, enforced AI governance policies and actively monitor for unauthorized use, while 91% have implemented policies overall.

Pivoting to Proactive AI Management

Proactively managing AI means harnessing employee initiative while maintaining security. It delivers the business value discovered in shadow AI but does so via AI tools that are approved by IT. To that end, ITDMs and employees make several strategic recommendations in the report.

  • 63% of ITDMs advise integrating approved AI tools into standard workflows and business applications, 60% suggest implementing clear policies on acceptable AI use, and 55% suggest establishing a list of vetted and approved tools.
  • 66% of employees recommend setting clear policies that are fair and practical, 63% recommend providing official tools that are relevant to their tasks, and 60% advise providing better education on understanding the risks.

"Shadow AI is a fatal flaw for most organizations," said Sathish Sagayaraj Joseph, regional technical head at ManageEngine. "IT teams can't manage risk they can't see — and they can't enable business value that users won't divulge. Proactive AI management unites IT and business professionals in their pursuit of common, organizational goals. That means employees are equipped to understand and avoid AI-related risks, and IT is empowered to help them use AI in ways that drive real business outcomes."

Survey Methodology: In May 2025, ManageEngine commissioned independent market research agency Censuswide to conduct a study of 350 ITDMs and 350 working professionals across the US and Canada, employed in organizations with at least 500 employees and $10M in annual revenue. The survey explored AI usage patterns, security concerns, and governance gaps, with a focus on real-world behaviors across organizations of varying sizes and industries.

Related Links

Hot Topics

The Latest

Clearing the Path to AI: Why Vendor Consolidation Matters Now

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

Explainability Is the New Battleground in AI-Powered Observability

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

Empowering the Human Side of the Autonomous IT Age

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

No Escalations ≠ No Work: Why Visibility in DevOps Matters More Now That AI Is Accelerating Everything

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

Observability Costs Rising Faster Than Value

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Customers Demand Frictionless Experiences - This Is How Retailers Can Provide Them

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

IT's Motivation Crisis Is Really a Process Crisis

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...