Shadow AI, a term describing unsanctioned or ad-hoc GenAI use

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Shadow AI, a term describing unsanctioned or ad-hoc GenAI use
Shadow AI, a term describing unsanctioned or ad-hoc GenAI use

Business stakeholders must be involved while embarking on the GenAI journey

This is an exclusive article series conducted by the Editor Team of CIO News with Subhash Singh Punjabi, CISO & Head Enterprise Architect, Deepak Fertilisers and Petrochemicals Corporation Limited.

Shadow AI is a term describing unsanctioned or ad-hoc generative AI (GenAI) use within an organisation that’s outside IT governance. Shadow AI is a big challenge for the security team and is becoming a real threat for organisations because of the easy accessibility of the technology to generic enterprise users.

I think it’s important that organisations have clear policies and procedures in place with respect to the usage of AI and GenAI to reestablish the role of IT and security.

The risks associated with AI/GenAI:

  • Data Privacy: Training data used to develop Gen AI models may contain sensitive information. If not handled properly, there’s a risk of exposing personal or confidential data, leading to privacy breaches.
  • Data Confidentiality: While AI is extremely effective in bringing relevant insights out of customer data, it’s important to note that this data can be misused. Often, GenAI initiatives do not mask customer data before use, which leads to bigger ramifications.
  • Intellectual Property Concerns: Gen AI models trained on copyrighted material could potentially infringe on intellectual property rights if used to generate content without proper authorization.
  • Regulatory issues: Business users also tend to miss the regulatory requirements when it comes to critical data.

How do we address these concerns?

  • Policies and Framework: Set the right policies and framework right at the beginning for AI use cases to deploy for the organisation.
  • Data Protection: Ensure that sensitive data used for training GenAI models is properly anonymized and protected to prevent unauthorized access or disclosure.
  • User Awareness and Education: Educate users about the risks associated with Gen AI-generated content and provide guidance on how to critically evaluate and verify information. Encourage all business users to collaborate with the security team if they want to use GenAI.
  • Cross-functional team: It’s important to involve all the business stakeholders while embarking on the GenAI journey. Organisations can form a cross-functional team that has representations from all business functions like IT, marketing, HR, supply chain, etc., along with the CISO, who can act as a panel to vet prospective GenAI solutions. Have a clear checklist regarding the pros and cons of the technology, identify the risks associated, and ensure regulatory compliance before going ahead with the project.
  • Continuous Monitoring: Implement monitoring mechanisms to detect and respond to security threats or misuse of GenAI systems in real-time because GenAI initiatives keep evolving.
  • Regulatory Compliance: Adhere to relevant regulations and standards governing the ethical use of AI, data privacy, and intellectual property rights.
  • Sandbox environment: Ensure that GenAI POCs are executed in sandboxed environments using sample or mask data.

By proactively addressing the above points and implementing appropriate safeguards, it’s possible to mitigate the risks associated with shadow AI and ensure the responsible and ethical use of artificial intelligence technologies.

Also readUnveiling the Ethical Imperatives: Navigating the Intersection of AI and Cybersecurity

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