Last updated on June 7th, 2024 at 10:53am
Generative AI (GenAI) is an emerging technology enterprises are utilizing to drive innovation and efficiency. By automating creative processes, enhancing customer interactions, and providing valuable insights from data, GenAI holds the potential to revolutionize various aspects of business operations. However, without proper oversight and governance, the adoption of GenAI can lead to significant risks, mirroring the challenges faced during the early days of cloud computing.
Learn from the Past to Protect the Future
A decade ago, the rise of cloud computing led employees to use cloud services without proper governance or approvals, causing security vulnerabilities, compliance risks, and cost overruns. Today, we see a similar pattern with the proliferation of GenAI. Motivated by AI's potential, employees circumvent standard procedures because they find them too rigid or outdated. Initially, this might seem harmless, but over time, it can expose an organization to significant risks, including unmonitored infrastructure and AI programs.
These challenges remind us of the early concerns with cloud computing and call for the same remedies. Robust governance frameworks are essential to set policies and guardrails, ensuring the safe and effective use of GenAI. Organizations can foster innovation without compromising security, compliance, or cost control by taking a proactive stance and implementing these governance measures.
Consider the founding story of Kion—we created our platform to help a large government agency confidently and safely transition thousands of developers and applications to the cloud. This agency was wary of cost overruns and sensitive data leakage and recognized the need for a solution to govern its cloud program effectively. By focusing on developing Cloud Operational Excellence with Kion, they aimed to avoid the pitfalls of shadow IT and ensure secure, cost-effective cloud initiatives.
Pain Points of GenAI Without Proper Governance
Without proper governance, the adoption of GenAI can lead to several significant pain points, including:
- Cost Overruns: Unchecked use of GenAI resources can lead to unexpectedly high costs, as AI models often require significant computational power and storage.
Example: While experimenting with new feature development, your application team tests AWS Bedrock on a large dataset using your input tokens too rapidly, leading to unexpected cost spikes.
- Data Leakage: Sensitive data used in training AI models can be inadvertently exposed if proper data handling protocols are not in place.
Example: Customer data used for developing personalized AI recommendations could be accessed by unauthorized personnel due to insufficient access controls or used to train public models and cause a data leak.
- Compliance Risks: GenAI applications must comply with various regulations, and lack of governance can lead to non-compliance and legal repercussions.
Example: A team building a chatbot to help with support tickets using a public language model instead of creating a specific one for their product. This can lead to the chatbot providing customers with incorrect information and answers, posing a significant compliance risk and leaving the organization vulnerable to legal issues.
- Security Vulnerabilities: Organizations can face significant breaches without robust security measures.
Example: An incident involving OpenAI in March 2023, where a bug allowed users to see titles of other users' chat history and, in some cases, partial credit card details and email addresses. This breach exposed sensitive information, highlighting the critical need for securing AI systems against such vulnerabilities. OpenAI promptly patched the bug and took steps to prevent future occurrences, underscoring the importance of robust security measures to protect AI models and data from potential breaches.
- Operational Inefficiencies: Without proper governance, deploying and maintaining AI models can lead to significant inefficiencies and reduced effectiveness.
Example: Multiple teams might develop redundant AI solutions without a coordinated strategy, wasting resources and effort.
How Kion Solves These Pain Points
Kion addresses these challenges by providing a comprehensive governance platform to manage GenAI and cloud resources effectively. Key features include:
Policy Configurations: Kion allows organizations to set and enforce policies that protect data and ensure compliance. This includes defining access controls, data handling procedures, and usage limits to prevent cost overruns and leakage.
Cost Management: With Kion, organizations can monitor and manage GenAI usage, ensuring expenditures remain within budget. This includes alerts for unusual spending patterns and tools to allocate costs accurately. Kion’s enforcement mechanism can also automatically restrict model and service availability based on spend thresholds or overruns, ensuring that AI innovation budgets are effectively capped.
Compliance Automation: Kion helps organizations automate compliance checks, ensuring that your developers stick to approved services and models. This reduces the risk of public exposure, non-compliance, and associated penalties that could arise.
Security Enhancements: Kion provides robust security measures, including encryption, identity and access management, and continuous monitoring, to protect AI models and data from cyber threats.
Operational Efficiency: By centralizing governance, Kion ensures that all AI initiatives are aligned with organizational goals, reducing redundancy and improving overall efficiency.
Get Started with Kion’s AI JumpStart Today!
For existing Kion customers, Kion has released an AI Jumpstart into the platform. Customers can import Cloud Rules, AWS IAM Policies, Azure Roles, and AWS CloudFormation Templates to help you govern which models your users can access, deny some or all AI-cloud services, and even set up monitoring to track Bedrock token usage and send alerts via email. To get started, visit our documentation on the Kion Success Center at support.kion.io.
Conclusion
Proper governance and guardrails are essential for organizations to innovate confidently while maintaining a low-risk profile. By implementing comprehensive governance frameworks, organizations can harness the power of GenAI without letting the fear and uncertainty of disruptive technology hinder their innovation. Kion is committed to helping organizations protect their innovations by providing the tools and capabilities to govern AI and Cloud resources effectively. With Kion, enterprises can drive innovation, achieve Cloud Operational Excellence, and ensure their AI initiatives are secure, compliant, and cost-effective.
Request a demo for more insights on how Kion can help your organization govern its GenAI initiatives. Together, we can navigate the complexities of GenAI and unlock its full potential for your business.
