How Data Cloud Enhances Contextual AI for Salesforce Admins

Today on the Salesforce Admins Podcast, we talk to Mehmet Orun, SVP, GM, and Data Strategist at PeerNova.

Join us as we chat about how to use Data Cloud to create trustworthy AI experiences.

You should subscribe for the full episode, but here are a few takeaways from our conversation with Mehmet Orun.

How Data Cloud powers trustworthy AI experiences

The last time we had Mehmet on the pod, the big concern with AI was hallucinations. How can we be sure that the agents we create don’t start making stuff up? What’s more, how do we know that they won’t share data they shouldn’t? In short, how do we create trustworthy AI experiences?

As we’ve learned time and again, AI is only as good as the data you give it. But, as Mehmet explains, Data Cloud has changed the game for admins in terms of control over who sees what and in what context. Admins can create personalized experiences with Agentforce, constrained by the permission model and capabilities of Flow to ensure that everything is working as intended.

How data management best practices have changed with AI

One thing Mehmet reflects on is the way that data management techniques have changed over time. Several best practices no longer make sense in today’s context of AI. For example, duplicate records that used to be a mortal sin make more sense when you’re trying to constrain what a customer can see vs. your employees vs. your vendors.

However, the personalized engagement that is possible with Agentforce requires a complete understanding of what’s happening with someone. At the same time, you want your agents to only act on information they’re “allowed” to see, or generate insights that are relevant to the outcomes you want to achieve. As Mehmet explains, “good” data and “bad” data is really about making sure your data is structured in a way that makes it easy to use.

Data unification made easy with Data Cloud

The good news is that it’s never been easier to take care of your data with Data Cloud. Mehmet’s seen this with the nonprofits he works with. Data unification projects that used to take months or even years are now relatively simple affairs. You can identify bad data, filter out irrelevant data, and put the right data standardizations in place all in setup.

Mehmet’s biggest piece of advice is to measure your data quality in terms of the business outcomes you are trying to achieve. As he points out, the amount of data you need to open an opportunity is different than what you need to close an opportunity. The same principle applies to AI agents. If you make sure they get everything they need and nothing extraneous, you’ll get good results.

There are a ton of great insights about data management best practices for AI in our conversation with Mehmet, so be sure to listen to the full episode. And make sure you’re subscribed to the Salesforce Admins Podcast so you can catch us every Thursday.

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