In this blog, we’ll take a closer look at how AI is fuelling a rise in Shadow IT, why it matters, and what businesses can do to stay in control without stifling innovation.
Why AI Is Accelerating Shadow IT
The AI landscape has exploded in recent years, with a huge range of tools now available online — many offering free or freemium access with minimal sign-up requirements. From AI-powered copywriting tools and image generators to advanced data analysis platforms, these tools are often just a few clicks away.
It’s no surprise, then, that employees are increasingly turning to them to speed up tasks or solve problems, sometimes without stopping to check whether the tool in question is approved, secure, or appropriate for handling company data.
And because many of these AI tools live in the cloud, they can be used on personal devices or through web browsers, making it harder for IT teams to maintain visibility and control.
What is Shadow IT?
Put simply, Shadow IT refers to the use of hardware, software, or online services without approval or oversight from an organisation’s IT department. It could be something as simple as a cloud-based file-sharing app or an AI tool a member of staff has started using to help with their day-to-day tasks.
While it’s often well-intentioned — typically driven by a desire to work more efficiently — Shadow IT can introduce real risks if it isn’t properly managed.
What Are the Risks?
- While AI-driven Shadow IT might seem harmless on the surface, it can open up a number of risks for businesses, including:
- Data Privacy & Compliance Issues: Sensitive information may be uploaded to external AI platforms without proper safeguards in place, putting the organisation at risk of data breaches or regulatory non-compliance.
- Cybersecurity Vulnerabilities: Unvetted AI tools can become entry points for cyber threats, particularly if they require access to company systems or data.
- Lack of Visibility: If IT teams don’t know what tools are being used and where data is being shared, it becomes much harder to manage risks effectively.
- Intellectual Property Concerns: Company data and creative content could be used to train external AI models, raising questions about ownership and control.
A Quick Example:
Imagine a marketing team using an AI image generator to create visuals for a client campaign. Without proper oversight, they might accidentally upload protected logos or sensitive information, potentially breaching contracts and exposing the business to reputational damage.
How to Tackle the Issue
The good news is, it’s not about banning AI tools altogether — and doing so would likely drive Shadow IT further underground. Instead, businesses should focus on enabling safe, responsible AI use by:
- Raising Awareness: Educating staff on the risks associated with unapproved AI tools and how to use technology responsibly.
- Setting Clear Policies: Defining what types of AI tools are acceptable, how they should be used, and the process for getting new tools approved.
- Offering Approved Alternatives: Curating a list of trusted, vetted AI solutions that meet business and security requirements.
- Using Monitoring Tools: Employing software to detect and manage unauthorised tool use, helping IT teams keep track of emerging risks.
- Developing AI Governance Frameworks: Putting in place clear guidelines for AI adoption, covering areas like data handling, privacy, and ethical use.
Turning a Challenge Into an Opportunity
It’s important to remember that instances of Shadow IT often highlight genuine needs within an organisation. If employees feel compelled to look outside the approved toolkit, it may be a sign that existing systems aren’t meeting their needs.
Handled in the right way, this can be a valuable opportunity for IT leaders and decision-makers to improve internal processes, provide better tools, and encourage responsible AI innovation across the business.
