Fix AI Data Problems with Salesforce Data Cloud

AI technologies can write emails, guess what customers will do next, and even tell you what to do next in a sales cycle. Sounds like fun, right? But there is one thing that makes all of this possible: data.

Data is what makes AI work.

AI learns from patterns, depends on data, and presents a story. That’s why the strength of your AI depends on the quality of your data.

And people do care. A lot!

According to a Forbes article, more than 75% of people are worried about AI giving out false information.

So, is false information an AI problem or a data problem?  

Here’s something to help you decide: AI doesn’t think for itself. It just does what it’s told. And it only becomes clever, fast, and reliable when the data it’s fed is accurate.

That’s where Salesforce Data Cloud comes in. It brings all of your data together in one location, in real-time.

Know how, with Salesforce Data Cloud, you can unify your data effortlessly, making sure your AI has the trusted insights it needs to truly shine.

You know how everyone wants to skip the boring data labor and look at the cool AI models?

Researchers at Google think that’s where the problems begin, especially when AI is making significant choices in areas like healthcare or conservation.

They term it “Data Cascades,” which are small errors in data that build up and lead to big AI faults.

And you know what? This happens in more than 90% of AI programs!

Take the case of the Air Canada chatbot from 2024.

After his grandma died, a man named Jake approached the airline’s virtual assistant about bereavement tickets.

The bot told him he could buy a standard ticket and then get a discount later. Jake did that, but when he asked for his money back, the airline answered, “Nope, that’s not how it works.” He sued them, and the judge decided the airline didn’t do enough to make sure its chatbot was offering correct information. What happened? Air Canada had to pay for damages.

When AI obtains faulty data, it messes things up for individuals and businesses. This is a real-life illustration of what happens.

And it’s not just the airlines. Bad or insufficient data in AI can:

What does it all come down to?

Data quality!

The AI’s advice won’t be much better if the data is disorganized or missing.

To start, most businesses still view data preparation as an afterthought.

You might have a great CRM or strong analytics platform, but if each app pulls from different data sources, none of which talk to each other, AI agents are forced to work with a fragmented context.

You’ve seen what happens when AI runs on half-baked data — from chatbot mishaps to model hallucinations in healthcare or finance.

But what if the fix isn’t about the model at all? What if it’s about giving your AI smarter fuel?

That’s where Salesforce Data Cloud comes in.

Salesforce Data Cloud changes the game by bringing together, harmonizing, and activating data from all sources—inside and outside of Salesforce—in real-time. This makes it ready to use for AI right away. This is how:

Unified Profiles in Real-Time

Data Cloud’s main job is to make a Golden Record, which is a single, up-to-the-millisecond view of your client or entity. It doesn’t just clean your data; it puts it in perspective. All of the data, whether it’s orders, support cases, site activity, or IoT data, is put together in real time.

No ETL, No Duplicates

Data Cloud interacts with Snowflake, AWS, Google, and Databricks without transferring or changing data, thanks to its zero-copy architecture. You don’t have to wait for ETL pipelines or worry about version mismatches anymore.

Power for AI Agents

When Data Cloud runs Agentforce or Einstein Copilot, it not only answers. It thinks through data that is pertinent to the situation:

If they’re a high-value account or at risk of leaving

You don’t have to go get or join anything by yourself; Data Cloud does all of that for you in the background.

Built-In Trust Layer: All AI prompts and responses go through the Einstein Trust Layer, which makes sure that data access is safe, controlled, and compliant. Sensitive information is hidden. Data never trains models from outside. Audit trails are kept up to date automatically.

Without Data Cloud

Einstein Copilot helps a sales rep compose a follow-up email. The AI gets general information and makes suggestions:

“Hey John, thanks for being interested. If you need help, just let me know.

With Data Cloud

The same person utilizes Einstein Copilot, which is now powered by Data Cloud. The AI can know everything about John, including his previous downloads, the support request he opened yesterday, and the fact that he has an at-risk account. Copilot says this time:

“Hey John, I observed that you got our guide to integrating AI and asked a question about how to get into the sandbox. I got support involved, and we’d love to show you a personalized demo.

That’s not just making it your own. That’s accuracy on a large scale, thanks to data that is networked and available in real time.

Bad data breaks your AI—plain and simple.

But Salesforce Data Cloud flips the script.

And we have just read how it helps you avoid feeding your AI junk by making sure data is created the right way from the start.

Here’s how to keep that data clean, consistent, and ready to fuel smarter outcomes:

Whether you’re just starting with Salesforce Data Cloud or scaling up your AI efforts, now’s the time to re-evaluate how your data is captured, connected, and activated.

And if you’re unsure where to start, consulting a Salesforce Data Cloud partner can help you navigate the complexities and build for what’s next.