Blog 4
Working safely with Agentforce: how do you keep control of your AI agents?
In the previous blog posts of our Agentforce deepdive, you read what exactly this AI solution in Salesforce does, how to build your own agent and how SMEs are already successfully deploying AI agents today. In this fourth part, we focus on an important follow-up question: how do you keep control of your agents once they are active?
AI agents can take a lot of work off your hands. However, it is still important to maintain control. Especially in a business context, where customer data and internal processes are at stake, it is essential that AI is deployed safely and responsibly.
What do we mean by ‘governance’?
Governance means: clear agreements and frameworks to keep technology manageable . With AI, there is an additional dimension to this: After all, AI systems make decisions or perform actions based on input, context and data. As an organisation, you want to be sure that this happens within your own rules and expectations.
The deployment of Agentforce includes:
- What data is an agent allowed to use?
- What is it allowed to perform automatically (and what not)?
- Who has access to which agent?
- How is it logged and monitored?
- How do you detect errors or undesirable behaviour?
Specifically, how do you arrange governance within Agentforce?
1. Limit and define the role of each agent
Each Agentforce agent works on the basis of a clearly defined role. You define which data it can use, which actions it can perform and within which channels it operates. This prevents an agent from “knowing more” than necessary.
2. Provide clear guardrails
As a company, you can set what an agent is definitely not allowed to do. Think: no access to confidential files, no automation of invoicing, no communication with external parties without approval. This way, control remains with the user.
3. Log all actions
Agentforce automatically keeps track of what actions an agent performs. This allows you to track who did what and when. This is crucial in case of incidents or errors, and helps build trust with your team.
4. Provide human intervention when in doubt
You can set up your agents to make suggestions, but not perform actions without manual confirmation. This hybrid model – AI as assistant, not decision-maker – is ideal for companies just starting out with AI.
5. Work with roles and rights
Not everyone needs to have access to all agents. In Salesforce, you can work with role-based access, so that only authorised employees can use, modify or create agents.
6. Test and train in a safe environment
Use a sandbox environment to test new agents before they go into production. Let multiple users work with it, gather feedback and learn from mistakes. This way, you reduce the risk at launch.
What about GDPR?
Agentforce works within Salesforce’s familiar structure, including the platform’s privacy rules and security protocols . Still, it is important that you as an organisation bear ultimate responsibility for what your agents do with personal data.
Some points of interest:
- Limit your agent’s access to only necessary data
- Mention the use of AI agents in your privacy policy
- Don’t let sensitive data be processed automatically without human review
- Give your customers the opportunity to access or delete data (right to access/remember)
In conclusion: AI as a responsible extension of your organisation
A well-designed AI agent takes work off your hands, without you losing control. By making smart use of the built-in security and governance structure within Agentforce, you build a secure and future-proof AI environment.
In the next and final blog post of this series, we will look at how to measure the impact of Agentforce: what ROI can you expect, how do you track usage and how do you expand successfully?
In the meantime, let us know if you have any questions or would like a demo!
