Securing adoption in the era of shadow AI

Date:
Mon, 17 Aug 2026 07:43:57 +0000

Description:
How organizations can reduce shadow AI risks while enabling secure, responsible AI adoption at scale.

FULL STORY ======================================================================Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Subscribe to our newsletter Artificial intelligence (AI) is rapidly becoming embedded in the modern workplace, with employees are increasingly turning to AI tools to work more efficiently and boost productivity.

This growing demand for faster, more effective ways of working is driving the rise of shadow AI - the use of AI tools outside approved organizational controls and governance frameworks which results in organizations quickly losing visibility into data usage and potential risks. Martin Tombs Social Links Navigation

Field CTO EMEA at Qlik. The scale of this challenge is significant. While 90% of executives are confident in their organizations' visibility into AI tools, just 52% of employees admit to using AI tools without approval, often through personal accounts. Latest Videos From TechRadar Watch full video here:

As a result, organizations are left grappling with a widening gap between AI adoption and AI governance. The next frontier of AI risk When AI is used without formal oversight, it can bypass governance controls, increasing the risk of errors, regulatory breaches and sensitive data leakages.
Organizations are most exposed when AI is already influencing business-critical activities, from customer service and operational decision-making to software development and content creation. You may like Shadow AI a step too far, or an opportunity? How governance gaps are
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The challenge will intensify as businesses move beyond large language models
, which generate information, to large action models and agentic systems that can take action. These systems can diagnose issues, recommend actions and execute workflows with minimum human input, increasing both the speed and scale at which mistakes occur.

A shadow agent operating outside approved governance frameworks could trigger harmful actions before organizations have the visibility and governance capabilities needed to intervene. Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Contact me with news
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There is also a longer-term risk that future AI systems will be trained on synthetic or lower-quality data, weakening performance and decision-making over time. Transparency and traceability will be critical to maintaining accountability, protecting ethical standards and preserving the effectiveness of AI systems as adoption continues to accelerate. AI governance as an
enabler What works is AI governance that enables innovation while putting clear guardrails in place that are integrated, transparent, auditable, and aligned with existing risk and compliance frameworks. If AI is to be used safely, firms must be able to successfully identify exactly what went wrong and why when issues arise.

In practice, mature governance starts with an approved AI tool stack that provides safe and trusted options for common use cases. This should be supported by risk-based policies that make clear the data being handled, what can and cannot be shared, which tools are permitted, and where human approval is required. What to read next Cracking down on shadow AI is making your business less secure, not more You fix it by making the secure option just as fast and frictionless as the risky one: Practical advice on addressing shadow AI If everyone is rushing to board the AI ship why are so few workflows secure?

Low-risk tasks such as drafting or summarizing content should not be governed in the same way as high-risk uses involving customer data, regulated information or business-critical decisions.

Training is equally important. The challenge, beyond only enforcing controls, involves helping employees understand why those controls exist and how to use AI responsibly. As agents increasingly diagnose issues, recommend actions,
and execute workflows with minimum input, human oversight and approval processes must scale alongside them.

Interoperability will be critical to making this workable at scale, allowing organizations to operate across jurisdictions and multiple AI models without repeatedly rebuilding governance processes and systems from scratch. Making responsible adoption the easy choice For security and compliance leaders, the goal should be to make responsible AI adoption the path of least resistance. Employees turn to shadow AI when approved tools are unavailable, difficult to access or fail to meet their needs. Companies that focus solely on
restricting usage risk driving activity further underground and losing out on the efficiency and innovation gains that AI can deliver.

Organizations that successfully balance AI productivity and control over
their systems recognize that shadow AI use is often a symptom of unmet
demand. Employees typically turn to unauthorized tools because they are
easier to access, faster to use or better suited to the task at hand. Rather than focusing on restrictions alone, leaders should understand where AI is already being used across the business and ensure approved alternatives are available for the most common use cases.

With three-quarters of office professionals saying they would be likely to look for a new job that offered better AI skills development, firms that combine governance with opportunities to build AI skills are likely to see stronger adoption of approved tools and, as a result, less reliance on shadow AI.

Building an AI-enabled culture means giving employees the tools, knowledge
and confidence to innovate within clear boundaries. By doing so, shadow AI
can be reduced while the speed and agility that workers increasingly expect
is maintained. The organizations best positioned to succeed The businesses that strike the right balance for AI success will be those that view governance as a foundation for AI adoption and not a barrier to it. By making the secure, approved path the easiest path, shadow AI risk is reduced without sacrificing productivity.

Embedding strong governance, supported by trusted and well-managed data foundations, avoids costly mistakes and allows AI to be deployed and scaled with greater safety and confidence. We've reviewed, rated, and ranked the
best small business software . This article was produced as part of TechRadar Pro Perspectives , our channel to feature the best and brightest minds in the technology industry today.

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