There’s no denying that in 2025, Generative AI has shifted from a pilot technology to core business essentials, reshaping how companies create, operate, and protect their data. While it drives innovation, automates workflows, and boosts productivity, it also introduces new risks such as data leakage, regulatory gaps, and unmonitored AI usage, which could spiral into compliance and security threats.


From Power to Peril: The Dark Side of Shadow AI

Shadow AI has emerged as a new form of insider threat. According to Forrester’s 2024 prediction, 70% of employees will use unapproved GenAI tools at work, turning Shadow AI into a fast-growing insider threat vector, contributing to a sharp rise in data exfiltration incidents.


Empowered by AI, Exposed by Shadow

We are not lost in the shadows! Little did we know that Shadow AI has evolved from a fringe concern into a deeply embedded risk within enterprise operations. Catching up with the trend, Shadow AI has woven itself into daily workflows, with employees adopting external GenAI applications to boost productivity, generate content, or automate tasks frequently. But we’re now entangled in a web of data breaches, regulatory lapses, and unchecked AI activity.

GenAI at the Edge: 5 Strategic Moves to Prevent Risk Fallout


1) Engage Stakeholders Across Business Units

Leaders are at the forefront when it comes to taking the first move to collaborate across departments especially with IT, legal, compliance, and to establish a clear AI acceptable user policy. This policy should define when, where, and how AI technologies can be used, while reinforcing that unapproved tools are strictly off-limits. According to a March 2024 ISACA survey of 3,270 digital trust professionals:

  • Only 15% reported having formal AI policies in place
  • 70% acknowledged employee use of AI tools
  • 60% said generative AI is already being used within their organization


2) Be Proactive – Save and Guard Sensitive Data

As organizations navigate in a complex digital ecosystem, protecting sensitive data demands more than reactive defences. By embedding real-time content inspection into data flows and managed policies internally, companies will have the upper hand to gain consistent visibility and control. There should be an alert if someone violates any policy, streamlining compliance across cloud and on-premises environments. This will ensure sensitive information is only accessible to the right people, at the right time, under the right conditions.


3)Staying ahead of Evolving AI-Driven Threats

As AI-powered threats grow more intelligent and evasive, organizations must move beyond traditional defenses. A zero-trust security model built on the principle of ‘never trust, always verify’ enables continuous validation of users, devices, and data interactions. This proactive approach helps detect stealthy risks in real time and blocks unauthorized access before damage is done, even when threats are embedded within AI-generated content.


4)Designing an AI – IT Roadmap

Employees often adopt external AI tools not to break rules, but to work smarter and meet goals faster. To stay ahead of this trend, IT teams must take a proactive approach by offering secured, enterprise-approved AI solutions that align with real-world workflows. When AI initiatives are tightly mapped to both individual productivity and broader organizational goals, the temptation to use unsanctioned tools fades. By making “responsible AI” part of the company’s values, you instill a sense of pride and duty in employees to do the right thing. We cannot forget the fact that most shadow AI arises from people trying to do their jobs better.


5) Embed AI Risk Intelligence through Continuous Upskilling

Guess what? Creating a policy is not enough to prevent AI misuse. Security awareness must evolve with the tech today, which means embedding generative AI into organisation-wide learning, not just IT checklists. Shift the mindset from Restriction to Responsibility. Employees aren’t just users, they’re digital custodians of customer trust. Show them how to work with AI tools safely, like anonymizing data or using approved internal platforms. Remember, regular, practical education is essential in highlighting how unauthorized AI use can lead to data breaches, regulatory issues, or accidental exposure of confidential information.


Next Stop: Agentic AI as a Digital Teammate

As GenAI evolves into Agentic AI, it’s clear that business strategies need to keep up by making sure productivity gains don’t come at the cost of privacy, compliance, or trust. To stay ahead, organizations should build governance into every part of their AI journey. That means offering secure, approved AI tools, setting clear usage rules with real-time monitoring, and encouraging a culture where AI is used responsibly and transparently.

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