In today’s fast-paced digital landscape, agility is everything. Employees are constantly seeking faster, more efficient ways to get their work done, often turning to tools and platforms outside the purview of their IT/ICT departments. This phenomenon, known as shadow IT, is both a sign of innovation and a growing security concern.
Shadow IT refers to the use of software, hardware, or cloud services without explicit approval or oversight from the central IT/ICT team. Think of employees using personal public storage accounts to share files, or marketing teams adopting a new SEO or an analytics tool without informing IT/ICT. The reason for shadow IT is often related to an organization skipping over process due to urgency, lack of awareness, lack of IT/ICT service management and work culture of the organization. The risk involved is related to operational inefficiencies where IT/ICT teams lose visibility and control, making it harder to manage systems and respond to incidents. Compliance violations are due to tools that don’t meet regulatory standards and data breaches.
In the AI world, shadow AI is the proliferation of unauthorized AI tools and applications sneaking into enterprises without the knowledge or agreement of IT/ICT departments and CISO/security teams. These unauthorized AI systems and tools, deployed by individual employees or departments, could pose significant risks to the organization, compromising security, compliance, and the bottom line including the threat to brand value of the organization.
In the digital transformation focused world, the attraction and adoption of AI is undeniable. Organizations across various industries are racing to harness the power of machine learning, large language models (LLM), Gen AI and automation to drive efficiency, increase productivity, and gain a competitive advantage. However, this persistent pursuit of AI-powered revolution in the corporate world has given rise to a new and insidious threat: shadow AI.
The Stealthy Penetration of Shadow AI in Your Organization
ChatGPT, Deepfake and Grok — technology that has basically reshaped how employees approach their day-to-day from strategy to operation domains. With free availability of ChatGPT, complex data analysis, workflow automation, and even code debugging is simplified with precise accuracy. Employees have understood that by leveraging these AI tools, they can relieve repetitive tasks and use their time and energy towards meaningful work for the organization.
Public cloud offerings, SaaS applications, and relaxed device policies have empowered employees by allowing them to adopt cutting-edge tools without administrative hurdles. Chief among these are the AI-powered aces that have captivated the modern Gen Z and all aged workforce – chatbots, automation platforms, predictive analysis, and more.
In the last few years, employees have unleashed their creativity using free and paid AI tools, and will continue to embrace AI-driven solutions, regardless of formal corporate policies, process or approvals. However, the very features that make these tools attractive can also open the door to security and compliance breaches. Shadow AI applications may collect and store sensitive data, bypass established security protocols, and operate in silos, leaving organizations vulnerable to data leaks, regulatory fines, and reputational damage of the company.
Unmasking the Threat: Strategies for Addressing Shadow AI
- Risk Assessment and Mitigation: Do assess the security, compliance, and data privacy risks associated with each AI tool you use. Once identified, enable the right safeguards in place—this includes using AI-specific cybersecurity measures, integrating the tools with your existing security systems, encrypting sensitive data, and setting strong access controls.
- Unified Security Framework: Centralize control for all AI applications, models and services which are enforced by service usage policies within the organization without interruption of workflow.
- AI Asset Inventory and Visibility Assess the security, compliance, and data privacy implications of each AI tool deployed, and implement reasonable safeguards and controls to mitigate identified risks. This action should include deploying AI-specific cybersecurity controls and integrating AI tools into your existing security solutions, implementing data encryption, and establishing holistic actionable access controls.
- Unified AI Strategy: Baseline your organization’s AI initiatives with its broader business objectives, ensuring that the deployment of AI tools supports the overall strategic objectives and value delivery. This could involve consolidating disparate AI applications into a consistent, enterprise-wide platform or leveraging existing or new centralized AI-as-a-service model.
- Governance and Oversight committee: Create a cross-functional AI governance board or center of excellence to oversee the adoption and use of AI tools within your organization. This team should be responsible for developing and enforcing AI related policies, reviewing and approving AI initiatives, and providing guidance to employees on the appropriate use of these technologies.
- Education and Awareness: Educate your employees on the emerging risks and risk of shadow AI and the importance of following your organization’s AI policies. Inspire a culture of transparency and collaboration, where employees feel empowered to seek guidance and approval before adopting new AI tools in your organization.
Conclusion
Like shadow IT, shadow AI is silently compromising your security and compliance, especially data breaches. By proactively addressing this threat, you can unlock the full potential of AI while safeguarding your entire ICT environment. The path to AI-driven success depends on the careful balance of innovation, delivery and governance, empowering employees while maintaining the necessary AI design and delivery controls to protect the enterprise.
Rajasekharan KR, CISM, CDPSE, PMP
Is associated with NTT DATA as Global Capability Leader (Cyber Security). He specializes in Cloud Security, AI programs, ICT Infrastructure Security and Operational Technologies (OT) Security.