Shadow AI

What is 'Shadow AI'?

Shadow AI is the use of artificial intelligence (AI) tools by the employees of an organization without approval from the IT department. While this reduces the workload of the IT team, it also leaves AI processes without vital oversight.

Shadow AI Vs. Shadow IT 

Shadow AI is a subset of the broader concept of ‘shadow IT’. While shadow IT refers to any IT system or software used within an organization without approval, shadow AI specifically involves AI tools and applications.

In both cases, IT teams would hope to empower ‘business-led IT’, where employees can access whatever software tools best support their work through self-service. Yet, without proper oversight, the use of unauthorized software can be dangerous.

Samsung recently had to ban its employees from using the AI large language model (LLM) ChatGPT. This was because the firm learned its developers had uploaded proprietary code into a public instance of ChatGPT for automated bug testing. 

While the risks of shadow IT have long been a concern for CIOs, there is now speculation that Shadow AI will be much worse than shadow IT. This is because AI tools:

• Require no training to use, as you can simply ask them to complete a task
• Require users to provide data for it to work from, which may be private
• Use the data provided to train itself, and can then offer that information to other users
• Experience ‘hallucinations’ – treating fictional information the tool has created as fact
• Have no built-in safeguards or human oversight

Sundar Pichai, CEO of Google, said, “AI is probably the most important thing humanity has ever worked on. I think of it as something more profound than electricity or fire.” There’s little doubt that AI tools are an incredible innovation for enterprises, yet there is potential for misuse.

As such, IT professionals must have oversight of AI use in their organizations. Only then can they ensure this revolutionary technology is implemented correctly.

Importance of Understanding Shadow AI

Understanding shadow AI in your organization is the first step to managing the associated risks and benefits effectively.

By recognizing how Shadow AI emerges and the potential vulnerabilities it introduces, companies can develop strategies to mitigate risks while fostering an environment that encourages responsible innovation.

This awareness can help balance the need for rapid technological adoption with the necessity of maintaining robust security and compliance standards.

📚 Related: What is AI?

How does Shadow AI Emerge?

Several factors contribute to the rise of Shadow AI:

• Ease of Access: Many AI tools are either free web-based options or offered through software-as-a-service (SaaS). This makes it much easier for non-technical employees to leverage AI solutions without IT approval.
• Innovation and Agility: Business leaders are under constant pressure to keep up with the pace of technological evolution. When enterprise architects and IT teams gain a reputation for blocking progress, employees may take the initiative in hunting for self-service tools they can leverage independently.
• Unclear Policies: Our recent SAP LeanIX AI Report 2024 found that only 19% of IT experts have a framework in place for AI governance. Organizations that do not have well-defined guidelines for adopting and using AI technologies often find that their employees take matters into their own hands.

📚 Related: What is Generative AI?

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Risks Associated with Shadow AI

1. Security Vulnerabilities

Shadow AI can introduce significant security risks as unauthorized tools may not comply with organizational security policies, potentially leading to data breaches. For instance, a self-procured AI tool might lack robust security measures, making it a target for cyberattacks.

"Security is always going to be a cat-and-mouse game," said Kevin Mitnick, a renowned cybersecurity expert. The lack of centralized oversight in Shadow AI makes it difficult to enforce consistent security protocols, increasing the vulnerability to attacks.

2. Compliance Issues

Using unsanctioned AI tools can result in non-compliance with data protection regulations. If sensitive data is processed or stored by these tools without proper oversight, it can lead to significant regulatory penalties.

For instance, GDPR violations in the EU can result in hefty fines, damaging an organization’s financial standing and reputation. Compliance with data protection laws is critical, and shadow AI tools often bypass the necessary checks and balances required to ensure regulatory adherence.

3. Operational Inefficiencies

Disparate AI tools used without co-ordination can create data silos, leading to inconsistent results and decision-making challenges. This fragmentation can also duplicate efforts and reduce overall efficiency.

When teams work in isolation with their own set of tools, it hinders collaboration and the ability to leverage integrated data insights across the organization. The resulting inefficiencies can slow down operations and affect the quality of outcomes.

4. Data Management Challenges

Managing data across various unauthorized AI tools can be challenging, leading to issues with data accuracy, integration, and governance. This lack of control can hinder effective data management practices.

As data becomes fragmented across different platforms, maintaining data integrity and consistency becomes a daunting task. Poor data management can compromise the quality of insights derived from AI tools, ultimately affecting business decisions and strategies.

Business-Led IT: The Benefits of Shadow AI

Shadow AI is a sinister term that describes the downsides of allowing employees to leverage AI tools without oversight. In this light, it can be tempting to completely block shadow AI, but there are advantages to business-led AI adoption:

1. Enhanced Productivity

Despite the risks, shadow AI can significantly enhance productivity by enabling employees to solve problems quickly and efficiently. Direct access to AI tools can streamline workflows and improve performance. As Microsoft's CEO Satya Nadella emphasizes, "Every walk of life will be transformed by digital technology, including AI."

Productivity increases with AI, Source: nngroup.com

For instance, AI-driven automation tools can handle repetitive tasks, allowing employees to focus on more strategic initiatives.

2. Increased Innovation

Shadow AI allows employees to experiment with new tools and techniques, fostering innovation. This can lead to the development of novel solutions that might not emerge through traditional channels.

3. Employee Empowerment

Giving employees the freedom to explore AI tools can increase job satisfaction and retention. Empowered employees are more likely to take initiative and contribute to the organization’s success.

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Managing and Mitigating Shadow AI

Organizations need to implement robust mechanisms to identify and monitor the use of unauthorized AI tools. This includes using tools that can detect AI functionalities within existing applications.

Continuous monitoring helps organizations stay aware of the tools being used and assess their impact on the business. Pro-active monitoring enables organizations to guide the responsible use of AI.

Risk Assessment

Conducting thorough risk assessments of all AI tools, sanctioned or unsanctioned, is essential. This involves evaluating security measures, compliance with regulations, and potential impacts on data integrity.

Understanding the risks associated with each AI tool allows organizations to take appropriate measures to mitigate those risks. Comprehensive risk assessments help ensure that AI tools are used in a manner that aligns with organizational policies and standards.

📚 Related: Secure AI in Enterprise Architecture

Implementing an AI Governance Framework

Clear policies and guidelines should be established to govern the use of AI tools within your organization. Employees should be educated about the risks and encouraged to follow proper approval procedures.

Effective governance policies provide a framework for responsible AI use and help prevent the uncontrolled proliferation of Shadow AI. These policies should be regularly updated to keep pace with the evolving landscape of AI technologies.

📚 Related: LeanIX Report Shows Need For AI Governance

Tools and Technologies for Control

AI governance tools can help manage Shadow AI by providing comprehensive visibility into AI tool usage and enabling proactive risk management.

The AI Governance Extension from SAP LeanIX can enhance transparency and control over AI tools and their usage within an organization. Leveraging these tools allows organizations to enforce policies, monitor usage, and mitigate risks effectively.

📚 Related: Is your IT landscape Ready for Generative AI?

Future Trends and Predictions

Since the early beginnings, AI technologies have continued to evolve, and the prevalence of Shadow AI is likely to increase. Organizations must stay ahead by continuously updating their policies and tools to manage these new capabilities effectively.

The future of AI will see more advanced tools becoming accessible to non-technical users, further driving the adoption of shadow AI. Staying proactive in managing these developments is crucial for maintaining control and ensuring responsible usage.

Impact of Emerging Technologies

Emerging technologies, such as advanced machine learning models and AI-powered automation tools, will further blur the lines between sanctioned and unsanctioned AI usage. Staying informed about these developments is crucial.

Innovations like quantum computing and neural network advancements will enhance AI capabilities, making it imperative for organizations to adapt their strategies to manage these technologies responsibly.

Strategies for Future Management

Developing scalable security solutions and fostering a culture of responsible AI usage will be key strategies for managing shadow AI in the future. Collaboration between IT, security, and business units will be essential.

Creating an environment where employees feel comfortable seeking approval for AI tools and where IT departments are responsive and supportive can help balance innovation with security.

As AI continues to transform industries, effective management of shadow AI will be critical for harnessing its full potential while mitigating risks.