The gap between "having data" and "understanding data"

The gap between "having data" and "understanding data" has never been wider.

Most organisations sit on massive datasets but struggle to extract meaningful insights. Process mining tools reveal bottlenecks, but interpreting them requires specialised expertise. Analytics dashboards exist, but decision-makers still can't get quick answers to ad-hoc questions.

LLMs are changing this in three fundamental ways:

1. Natural Language as the New Query Language

Instead of learning SQL, Python, or proprietary query languages, analysts can now ask: "Which customer segments churned most after our pricing change in Q3?" The LLM translates intent into executable queries, runs the analysis, and explains the findings in context.

This isn't just convenience, it's democratisation. Domain experts who understand the business can now directly interrogate data without waiting for technical resources.

2. Automated Process Discovery and Anomaly Explanation

Traditional process mining identifies that your order-to-cash cycle takes 47 days instead of 30. But why? LLMs can now analyse event logs, correlate them with external factors, and surface hypotheses: "Orders from Region X consistently stall at approval stage when values exceed $50K—possibly due to understaffed finance team."

The breakthrough is moving from descriptive analytics (what happened) to diagnostic analytics (why it happened) at scale.

3. Context-Aware Analysis That Connects Dots

LLMs can synthesise insights across previously siloed datasets. They connect patterns in your CRM, financial systems, and operational logs to reveal relationships that traditional analytics miss. "Customer satisfaction scores dropped 2 weeks after you changed your fulfilment provider" becomes visible without manually running correlation analyses.

Building the Future at Intellifold

At Intellifold, we're integrating these capabilities directly into our platform. Natural language to queries is already available—you can ask questions in plain English and get immediate insights from your process and data analytics. Interactive process and dashboard filtering will follow shortly, making exploration even more intuitive. Interactive root cause analyses are next on the roadmap, bringing that diagnostic power to every user.

We're building the next evolution in process and data intelligence. Exciting times.

The Reality Check

This technology isn't magic. LLMs still hallucinate, struggle with complex multi-step reasoning, and require careful prompt engineering. Data quality remains paramount—garbage in, garbage out applies even more when AI is involved.

But the trajectory is clear: the bottleneck in analytics is shifting from technical execution to asking the right questions. Those who develop strong analytical thinking - who know what to ask and how to validate answers - will thrive in this new landscape.

The technical barrier to insights is collapsing. The intellectual barrier to good judgement remains.