Better Data, Smarter AI: The Key Role of a Data Governance Framework

What’s the one thing agentic AI can’t do without? Data. But just gathering data isn’t going to cut it — it needs to be accurate, secure, and private to really be valuable in. 

You need a solid data governance framework to make it all work.

Understand Data Governance

Imagine data governance as the organizational system of a well-maintained library. It involves establishing processes, policies, and guidelines to ensure proper data management within an organization.

Similar to how a librarian determines who can borrow books, how they’re handled, and ensures their safekeeping, data governance defines who has access to data, its appropriate usage, and protection measures.

Key components of data governance include: 

• Data Quality: Guaranteeing that data is current, accurate, complete, and reliable. For example, a retailer requires precise shipping information to ensure timely deliveries.
• Data Security: Protecting information from theft or unauthorized modifications. Financial institutions, for instance, implement multi-factor authentication to safeguard customer data.
• Data Privacy: Collecting, storing, and utilizing personal information responsibly and ethically. Healthcare providers adhere to strict regulations to ensure they only use necessary patient data.
• Data Architecture: Organizing, integrating, and managing data across the organization. This includes structures like data lakes for raw data, data warehouses for structured data, and databases for transactional operations.
• Data Management: Utilizing processes and tools to organize, store, and access data. Platforms like Data Cloud provide a comprehensive view of the customer, enabling real-time insights.

Data governance not only keeps your organization’s data secure, private, and well-managed, but also ready to use. It’s like having all the books on the right shelves, labeled correctly, and ready to be checked out. 

Connect Data Governance and Agentforce

Agentforce relies on data to learn, make decisions, and improve over time. However, it’s not just about the quantity of data; quality is paramount. 

As more industries adopt Agentforce and integrate AI agents into their operations, robust data governance becomes increasingly critical.

A solid data governance framework can:

• Ensure Accuracy and Quality: By setting standards for data collection, management, and storage, organizations can prevent errors, biases, and inconsistencies.
• Mitigate Legal and Ethical Risks: Adhering to privacy laws and ethical standards protects individual rights and builds trust.
• Facilitate Responsibility, Transparency, and Accountability: Clear data governance policies ensure that data usage is transparent and that individuals are accountable for their data practices. 

Achieve Success with Change Management

As your organization expands and adopts Agentforce, your data governance program must evolve accordingly. Effective change management is key.

Best practices include:

• Establish a Clear Vision and Goals: Understand the necessity for changes and define desired outcomes. For example, implementing Agentforce to assist with customer inquiries requires a robust data management and governance framework.
• Communicate Effectively: Recognize that change can be disruptive. Consistent and transparent communication with all stakeholders helps manage expectations and address concerns. Specifically, dedicated channels like Slack can be highly effective for sharing updates.
• Train and Educate Employees: Equip your teams with knowledge about new processes to ensure effective implementation. At Salesforce, we provide role-specific Trailhead modules to ensure employees understand and adhere to evolving data governance policies, especially when using Agentforce. For example, customer service and sales representatives can learn the proper methods for collecting and using customer data.
• Monitor and Evaluate: Acknowledge that change management is an ongoing process. Continuously assess and adjust initiatives to stay ahead in the evolving landscape of data and AI.

By following these best practices, you can ensure your data governance framework remains effective and adaptable.

Build a Trusted, Scalable Data Governance Framework

Data serves as the backbone of agentic AI, but its true potential is realized through solid data governance. By ensuring data is accurate, secure, and private, you can maximize AI’s benefits while building trust and reliability in your systems.

Ready to harness the power of your data? Explore Data Fundamentals for AI➚ on Trailhead.