Shadow AI: Safely Integrating Generative AI

Many employees use AI tools on their own to increase their productivity, often without formal instructions from their employers. A study by Microsoft and LinkedIn found that 78 percent of AI users now bring their own AI tools to work, in line with the motto ‘Bring Your Own AI’ (BYOAI). This demonstrates that a lack of training and awareness on the part of companies cannot prevent employees from using AI in potentially risky areas, ultimately creating a culture of covert generative AI (GenAI) use.

Shadow AI as a Result of Unmet Needs

The uncontrolled use of unauthorized software, hardware, or cloud services brings significant security risks that are often underestimated in IT departments. The problem lies in the fact that employees who bypass the IT department often circumvent established security protocols, creating critical vulnerabilities. Without security measures such as firewalls, endpoint protection, multi-factor authentication, or data encryption, sensitive data ends up in unsecured environments, which drastically increases the likelihood of data leaks. In the case of generative AI using public models, this brings an entirely new level of security risks.

Shadow IT, and especially shadow AI, not only leads to significant compliance violations, particularly against the GDPR, but also increases the risk of cyberattacks. Attackers specifically target these unofficial systems to smuggle malware, ransomware, or viruses into the company network via unsecured access points. In the case of shadow AI, sensitive data or information can be loaded into public models and distributed.

Consistent Monitoring and Clear Guidelines

This situation can have far-reaching consequences. A single security incident can significantly impact business operations due to downtime or data loss, while also damaging an organization’s reputation and destroying the trust of customers and business partners. Moreover, the IT department loses control and transparency: in the absence of centralized access controls with corresponding authentication and authorization models, it becomes challenging to maintain an overview of the infrastructure used and the data managed. Without consistent monitoring and clear guidelines, shadow AI poses a security risk that can cost companies dearly.

In most cases, such situations arise because employees feel that their needs are not being adequately met. This can be avoided if companies proactively provide solutions. Shadow AI is therefore not only a security risk but also an indication that the internal IT landscape needs further development to ensure agility and security in equal measure.

Embed GenAI Seamlessly into Existing Systems

Clearly defined guidelines and targeted training are crucial to ensuring that employees can use the technology efficiently and securely. This can ultimately lead to significant time savings and increased productivity. To fully exploit the benefits of generative AI while minimizing security risks, companies need to invest in robust security measures.

Another key aspect is the use of integration platforms that allow GenAI to be seamlessly embedded into existing systems while enforcing essential security and compliance policies. These platforms ensure consistent data integration and protect sensitive information while realizing the benefits of AI.

Finally, organizations need to foster a culture of innovation and ensure that their IT landscape is prepared for the demands of the digital future. A carefully planned implementation of generative AI can create measurable business value and strengthen competitiveness in the long term.

Dominic Wellington

Enterprise Architect at SnapLogic.