5 steps for choosing the right AI governance software

At a glance

• As generative artificial intelligence (AI) revolutionizes the way businesses operate, concerns over accountability, transparency, and ethical data use have come to the fore.
• Deploying a robust AI governance software is one of the most impactful steps an organization can take to address these concerns.
• By applying AI governance at the code level, AI governance software provides critical technical safeguards—managing and monitoring data going into AI tools and LLMs, and enforcing policies on the data that comes out. 
• Read on to learn five steps for choosing the right AI governance software for your company. 

Table of contents

1. Identify your AI governance needs
2. Evaluate specific features
3. Look for customization and integration options
4. Assess scalability
5. Evaluate the vendor holistically

Step 1: Identify your AI governance needs

The first step in selecting an AI governance software is to identify what exactly your AI governance system needs to do. Here’s a few questions to get the ball rolling:

• How is AI used across your organization? 
• What kind of data are you working with (personal, sensitive, etc.)?
• What AI model(s) are you using?
• What applications will be feeding data into your AI model(s)?
• Is there a point at which personal or sensitive data could enter an LLM?

You should also consider the scale at which your organization operates and the volume of data being processed. Evaluate the complexity of the AI models being used and the potential ethical implications of sharing company data with that model. 

Combined, these factors will dictate the level of oversight and control needed from your AI governance software.

Though it can feel like a complex task, taking the time to clarify your expectations, goals, and scope will provide crucial guardrails when narrowing down your list of potential AI governance solutions.

Step 2: Evaluate specific features

Your next step is to evaluate the features of different AI governance platforms and then compare them with your needs. Ensure the software can address all aspects of AI governance, including data privacy, security, transparency, and explainability.

Other features to consider may include data lineage, auditability, monitoring and alerting, and insights. Any AI governance software you choose should adhere to regulatory requirements such as GDPR, CCPA, and HIPAA. 

A comprehensive product demonstration will help you assess the effectiveness of each solution in meeting your AI governance needs.

Remember to pay attention to how the software enables accountability, and whether it offers a robust reporting system. These features can aid in tracking decisions made by AI systems, thereby ensuring ethical and responsible practices in AI usage.

Step 3: Look for customization and integration options

Every organization has unique AI governance needs. So, when selecting an AI governance software, make sure it can be customized to match your specific requirements. This may include adapting to your existing workflows, implementing governance rules, or multi-language support.

The software should also integrate with your existing data sources, analytical tools, and databases. Additionally, look for software that allows you to take queues from leading frameworks and adhere to any industry-specific regulations. This will help streamline your AI governance processes, while adding more value.

Step 4: Assess scalability

Organizations face varying AI governance needs. The most effective AI governance softwares will support seamless scalability and expansion, such as increasing data volumes, AI models, and users. The governance software should also be able to support future business growth.

Assessing the scalability of AI governance software is critical—as it ensures the solution can grow and adapt with your organization's evolving needs. It should comfortably handle increases in data volume, the complexity of AI models, and the number of users without compromising performance or efficiency. 

A scalable solution will not only meet your current business needs but also accommodate future expansion, facilitating seamless integration of new features and technologies.

Step 5: Evaluate the vendor holistically

Vendor evaluations are an essential step in assessing an AI governance software. Conduct due diligence, such as customer reference checks, and try to get an understanding the full breadth of their experience in AI governance and technology domains.

Additionally, evaluations should include assessments of the vendor’s product roadmap, support, maintenance, and pricing models. Choose a vendor that aligns with your values, has a history of consistently satisfying their clients' needs, and is transparent and collaborative.

Conclusion

Choosing an effective AI governance software is critical for responsible and successful AI implementation at your organization. 

By following the five steps outlined above, you can identify your AI governance requirements, evaluate specific features, including customization and integrations, assess its scalability, and make informed decisions through vendor evaluations. 

Remember to choose an AI governance software that is transparent, adheres to legal and regulatory requirements, and aligns with your organization's values.

More AI governance resources

• Transcend's approach to AI governance
• AI governance 101
• Introducing Transcend Pathfinder—the governance layer for enterprise AI
• Transcend joins IAPP’s AI Governance Center as 
first top-tier foundational supporter
• Introducing the AI Risk Assessment template

About Transcend

Transcend is the governance layer for enterprise data—helping companies automate and future-proof their privacy compliance and implement robust AI governance across an entire tech stack.

Transcend Pathfinder gives your company the technical guardrails to adopt new AI technologies with confidence. While Transcend Data Mapping goes beyond observability to power your privacy program with smart governance suggestions.

Ensure nothing is tracked without user consent using Transcend Consent, automate data subject request workflows with Privacy Requests, and mitigate risk with smarter privacy Assessments.