Salesforce is leveraging AI to drive CRM growth, but data quality remains a challenge. As AI becomes more integrated into decision-making, the reliability of CRM data is under scrutiny. Companies are finding that AI tools can amplify both efficiency and errors, depending on the quality of the data they use.
AI Changes How CRM Is Used
Salesforce CEO Marc Benioff has said apps aren’t dying—they’re evolving. AI is reshaping the CRM landscape, with more users relying on agentic tools and CLI calls. In the second quarter of Salesforce’s 2027 fiscal year, usage via these methods increased sixfold. You might wonder how this shift affects your workflow.
AI Recommendations Can Be Risky
A survey by Validity shows that many leaders act on AI recommendations, even when they later question their accuracy. Nearly 80% of C-suite leaders and 92% of SVPs/VPs said they trusted AI advice that turned out to be flawed. This highlights a growing concern: if the data is shaky, AI can make things worse.
Data Quality Is a Major Hurdle
Many companies are struggling with CRM data quality. According to the same survey, 62% of organizations have lost revenue because of poor data. You might not realize how much this affects your bottom line. Only 21% of marketers say their CRM data is well-prepared for AI, which means a lot of teams are working with incomplete or inaccurate information.
AI Multiplies the Impact of Poor Data
AI isn’t just a tool—it’s a multiplier. A single bad data point can lead an AI agent to make the wrong decision, especially if there’s no human oversight. That’s a risk many companies are only just starting to understand. You need to make sure your data is clean before you let AI take the lead.
Salesforce Is Leading the Way
Salesforce is capitalizing on the AI boom. Its Q2 2027 earnings report shows strong growth, with revenue targets raised due to increased demand for AI and data products. The company’s market cap stands at around $168.4 billion, showing its dominance in the CRM space. You might want to take note of how they’re managing this transition.
Pressure to Adopt AI Is Growing
The same survey shows that many marketing leaders feel pressured to adopt AI, even when the data isn’t ready. Nearly 60% of C-suite respondents and 52% of SVPs say they feel this pressure. This creates a gap between what companies want to achieve and what their data can support.
How Can You Fix the Problem?
Marketers say continuous, automated monitoring is key. A third of respondents said real-time data fixes would boost their confidence in CRM systems. But this isn’t easy, especially when teams spend six or more hours a week on data reconciliation. You need to find the right balance between automation and human oversight.
Experts Warn of the Risks
Practitioners like Leah Sand, senior vice president at Perficient, see the value in AI-driven CRM but stress the need for balance. She says figuring out what should be generative, agentic, or just automation is the real challenge. You have to make sure you’re using AI in the right way.
Why Is Data Quality So Important?
If AI is supposed to make things easier, why are teams spending more time fixing data than driving growth? The answer is clear: AI is only as good as the data it’s fed. As companies rush to adopt AI, they’re also racing against a growing problem—data quality. You need to make sure your data is up to the task.
