Unmasking Shadow AI

The artificial intelligence boom is actively changing how we go about our daily lives—especially when it comes to how we do business. 

80% of companies are using AI, or are in the process of incorporating AI into their daily operations. 

But just like mass SaaS adoption led to Shadow IT, AI use has resulted in Shadow IT, marking some significant challenges for IT managers everywhere.

Also, like Shadow IT, Shadow AI will be nearly impossible to eliminate completely, but it doesn’t need to be. 

Recognizing Shadow AI, understanding its risks, and developing governing mechanisms will allow you to better protect your business and harness the productive power of artificial intelligence. 

What is Shadow AI? 

Shadow AI refers to deploying AI systems and applications within an organization without the approval or oversight of the central IT department. Employees eager to solve problems or enhance productivity turn to AI tools that are easy to access but often lack the security, compliance, and governance that sanctioned IT solutions would have.  

Like Shadow IT, Shadow AI emerges when traditional IT governance is seen as too slow or cumbersome to keep up with the pace of business needs. While employees may have the best of intentions, the lack of oversight can lead to consequences. 

One of the things that separates Shadow AI from Shadow IT—and in many cases, makes it more formidable—is that every single user has the potential to become a threat. Users don’t need to know how to build and deploy applications to use AI. All they need to do is upload some data or ask some questions, revealing company data to third-party vendors along the way. 

Key Characteristics of Shadow AI: 

1. Lack of Oversight: These AI systems bypass the formal governance structures of the organization, leading to potential security and compliance risks.
2. Decentralized Development: Shadow AI solutions are often developed by non-IT staff, which can result in systems that lack the robustness and scalability of officially sanctioned AI projects.
3. Rapid Deployment: These solutions are typically implemented quickly to address immediate needs, skipping the approval processes that accompany formal IT projects.
4. Innovation and Flexibility: Shadow AI can foster innovation by allowing employees to experiment with new tools and techniques, unhindered by bureaucracy. 

Examples of Shadow AI 

• A marketing team starts using an AI-powered customer segmentation tool without informing the IT department. The tool helps the team refine their campaigns, but it also processes sensitive customer data without adhering to security protocols.
  

• A finance department adopts an AI-based forecasting model, but the lack of integration with existing systems creates data silos that complicate decision-making across the organization.
  

• The HR department uses an AI tool for resume screening without IT oversight, risking data security breaches and potential bias in hiring decisions that could lead to compliance issues.
  

• A regional office launches an AI chatbot on the company website to handle customer inquiries, but the bot lacks proper security measures and can harm brand consistency with inaccurate responses. 

Shadow AI can lead to: 

1. Security Vulnerabilities: AI systems are often data-hungry, and when they're developed without IT's knowledge, they may not adhere to best practices for data security. Sensitive data could be at risk, creating opportunities for breaches or compliance violations.
2. Compliance Issues: Regulatory compliance is a key concern, particularly in industries with stringent data protection requirements. Shadow AI systems, operating outside of formal governance, may inadvertently violate these regulations, leading to fines or legal repercussions.
3. Ethical Concerns: AI systems can introduce bias, and when developed without oversight, there is a higher chance that ethical guidelines may be overlooked. This can result in unfair decision-making, negatively impacting both employees and customers.
4. Operational Inefficiencies: When different departments deploy their own AI solutions, the organization can suffer from fragmented data and duplicated efforts. This fragmentation can hinder collaboration and prevent the organization from fully realizing the potential of AI. 

Upside of Shadow AI 

Despite the risks, Shadow AI is not inherently negative. When harnessed properly, it can offer advantages. 

• Agility: AI allows teams to address pressing challenges quickly. This rapid problem-solving capability can give departments a competitive edge and improve efficiency.
  

• Empowerment: Employees gain a sense of ownership and initiative by experimenting with AI tools to improve their workflows and productivity.
  

• Innovation at the Edge: AI initiatives often occur at the edges of an organization, where employees are closest to day-to-day challenges. This proximity typically leads to creative solutions that might not have been previously considered.

The key to unlocking these benefits is governance—finding the right balance between control and flexibility. 

Governing and Managing Shadow AI 

Effectively managing Shadow AI requires a combination of clear policies, a collaborative culture, and proactive monitoring. These things all operate within an AI Risk Management Framework, your company’s roadmap to effective AI use.  

Organizations can govern Shadow AI to maximize its potential while minimizing the risks by doing the following:

1. Establish Clear Policies   

Organizations must set clear guidelines for AI usage, outlining who can implement AI tools, what tools are acceptable, and what security measures are required. Policies should also cover the ethical use of AI, data privacy, and compliance with industry regulations. It’s crucial to make these policies easily accessible so employees understand the risks of bypassing IT governance.

For example, employees should be aware of data security requirements, and there should be a clear process for vetting and approving AI tools. 

2. Foster a Culture of Collaboration   

To prevent the rise of Shadow AI, it’s important to bridge the gap between IT and other departments. IT should act as an enabler rather than a gatekeeper, working closely with business units to understand their needs and help them deploy AI solutions that are secure and compliant. Encouraging open communication can reduce the temptation for departments to go rogue with their AI initiatives.

Regular cross-functional meetings, where teams discuss AI needs and challenges, can help foster collaboration and ensure that AI tools are aligned with the organization's broader goals. 

3. Provide Education and Training   

Employees often turn to Shadow AI out of a desire to solve problems, not out of a desire to create risks. Offering training on AI governance, data security, and compliance can help employees make informed decisions. Educating employees on the implications of using AI outside of oversight channels can go a long way toward reducing Shadow AI. 

Training should also focus on responsible AI usage, helping employees understand how to avoid introducing bias and ensuring that their AI solutions align with the organization’s ethical standards. 

These steps should be coupled with regular audits of AI usage, ensuring that authorized AI tools are being used appropriately and that no unauthorized tools have slipped through the cracks. 

AI for the Good, Not the Shadows 

Shadow AI represents both a challenge and an opportunity for organizations. On the one hand, it can drive innovation and agility, allowing employees to experiment with new tools and techniques. On the other hand, it introduces risks related to security, compliance, and operational efficiency.  

The key to managing Shadow AI lies in balancing governance and flexibility. Organizations can harness the benefits of Shadow AI while mitigating its risks by establishing clear policies, fostering collaboration, providing education, and implementing monitoring tools. 

Shadow AI isn’t going away. But with the right approach, organizations can turn this challenge into an opportunity, leveraging AI’s potential without sacrificing security or compliance. 

At HBS, we want your organization to reach its full potential with AI. We specialize in helping businesses in developing technology frameworks, strategies, and governance. AI is no different. 

Reach out now to learn how HBS can assist you with all your AI-related needs.