Discover the 5 key factors for building trusted, agentic AI and how they help businesses safely scale AI. From AI governance to privacy policies, explore the essential components for fostering trust and maximising AI's potential in today's rapidly evolving landscape.
Build trust with robust governance, clear AI guardrails, and a strong focus on accuracy, reliability, and privacy and empower your business to innovate responsibly and deliver smarter, more secure customer experiences.
Ensure AI agents act safely and responsibly by establishing guardrails that define appropriate actions. These AI guardrails should align with your business policies, regulatory requirements, and operational workflows while allowing agents the flexibility to deliver outcomes within trusted limits.
Human oversight is critical for building trusted AI. Establish clear escalation paths and review processes to maintain oversight where it matters most. With ongoing monitoring and tuning, you can keep AI aligned to your business goals and deliver outcomes you can stand behind.
Continuous feedback is key to making AI agents more reliable. Use real-world interactions to identify gaps, refine responses, and optimise performance over time. By implementing feedback loops, you can improve outcomes and keep AI aligned with customer expectations.
Protecting customer data is essential at every stage of your AI lifecycle. By embedding privacy into data collection, model training, and deployment, you can ensure sensitive information is handled responsibly. Align with global regulations, such as GDPR and HIPAA, while building trust through transparent, compliant AI experiences.
Agentforce has trusted access to the right customer data it needs to respond immediately, securely, and accurately to every customer request.
Jim RothPresident, Customer Success, Salesforce
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AI guardrails are a set of features and controls that reinforce trusted behaviour and prevent deviations from the intended behaviour of AI agents, helping businesses maintain fairness, accuracy, and compliance as they scale AI initiatives.
Different types of AI agents guardrails can be implemented across the agentic lifecycle. Common examples include applying role-based permissions, strict data access, declarative policies and logic, and a human escalation point.
Consider the policies, rules, and requirements that apply to the work today. This should be a starting point for identifying the needs and concerns when rolling out agentic AI. Protecting this sensitive data with encryption, access controls, and transparent consent processes is vital to maintaining privacy and customer trust while scaling responsible AI.
Salesforce Professional Services offers expert guidance to build governance frameworks, ensuring your AI initiatives are ethical, compliant, and aligned with industry best practices.
