According to ZDNet, Salesforce’s State of Data and Analytics Report reveals a massive disconnect in how businesses view their data capabilities. The survey of 3,800 data leaders and 3,852 business leaders found that 63% of organizations describe themselves as very data-driven, up from 53% just last year. Yet nearly two-thirds of technical leaders admit their companies struggle to actually drive business priorities with data. Here’s the kicker: data leaders estimate 26% of their organizations’ data is “untrustworthy,” and 42% of business leaders say their data strategies don’t align with business objectives. Meanwhile, 84% of CIOs believe AI will be as significant as the internet, creating enormous pressure to fix these data problems quickly.
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<h2 id="the-unstructured-data-problem”>The Unstructured Data Problem
Here’s where things get really messy. We’re talking about an estimated 80-90% of enterprise data being unstructured, and 70% of data leaders believe their most valuable insights are trapped in that unstructured mess. Think about all those PDFs, emails, meeting notes, and customer conversations sitting in digital filing cabinets. AI agents can’t work magic if they’re fed garbage. And 84% of data leaders agree that AI’s outputs are only as good as its inputs. So basically, we’re building these incredibly sophisticated AI systems to drink from firehoses of questionable data.
The Real-Time Data Crisis
Now here’s something that jumped out at me: real-time data has suddenly become the top data challenge, surpassing even security threats and data quality issues. That’s huge. Why? Because AI agents need current information to make good decisions. But the average enterprise uses 897 applications, and only 29% are connected. That’s like trying to run a modern business with 1970s-era inter-office memos. More than half of leaders aren’t confident they can even access the data they need. How are AI agents supposed to function in that environment?
The Human Factor
Don’t forget the people problem. 92% of leaders cited lack of data fluency among staff as a major barrier. And 93% of business leaders said they’d perform better if they could just ask data questions in natural language. That’s why Salesforce and others are pushing “agentic analytics” – the idea that people should be able to have conversations with their data platforms. But here’s my question: if we can’t trust the data, does it really matter how we access it? 49% of companies occasionally or frequently draw incorrect conclusions from data that misses business context. So we’re building better interfaces to potentially flawed information.
The Investment Imbalance
CIOs are spending four times as much on data infrastructure as on AI itself. That tells you everything. We’re recognizing that you can’t skip the fundamentals. The full report shows businesses are prioritizing building AI capabilities, improving data quality, and providing real-time access. But here’s the thing: data volumes are growing 30% annually. We’re creating data faster than we can clean it up. It’s like trying to fix a leaky boat while someone’s actively drilling more holes in the bottom. Until companies get serious about data governance and quality, their AI agent dreams will remain just that – dreams.
