AI has been nothing short of a superpower for developers. Large Language Models (LLMs) and AI-native copilots like Cursor, GitHub Copilot, and Claude have transformed programming - automating boilerplate code, writing tests, and even assisting with architecture decisions.
The coding world has become significantly more efficient, with AI tools reducing much of the manual work that once slowed developers down.
But analytics hasn’t seen the same level of transformation (yet). Despite the hype around AI and natural language querying, the field remains surprisingly manual for most companies. Why?
The importance of context in Analytics
Unlike programming, analytics isn’t just about writing code. It’s about understanding the business deeply enough to ask the right question - and then translating that into a query that hits the right tables, respects governance rules, applies the correct filters, and surfaces results in a format that’s actually useful. Effective analytics depends more on contextual reasoning.
This is why LLMs have struggled to drive the same kind of lift in analytics. Natural language interfaces like ChatGPT can generate SQL, but unless the underlying business logic is explicitly modeled, the queries they produce are often wrong, incomplete, or misleading.
The semantic layer as the bridge between AI and business logic
The key to enabling AI in analytics isn’t better prompts. It’s better context. That’s where semantic layers come in.
Semantic layers act as the connective tissue between raw data and business meaning. They encode dimensions, measures, joins, access controls, and documentation in code.
This structure not only serves human analysts, it gives AI agents the metadata and surface area they need to generate useful, accurate outputs.
At Shearwater, we’re investing heavily in helping agents reason through data by giving them programmatic access to these semantic layers.
Holistics’ Data Modeling Layer acts as a semantic layer, abstracting complex SQL into reusable logic that AI tools (like GPT-based assistants) can understand and interpret accurately. This helps AI generate accurate queries, visualizations, and even narratives without misinterpreting metrics.
When agents can work with tools that describe how revenue is defined, how churn is calculated, and how customer segments are modeled, they can do far more than generate SQL. They can deliver real analysis.
Driving AI in Analytics with semantic BI tools
If you want AI to meaningfully support your analysts, the path is clear: move your data stack to code.
Traditional BI tools can be user-friendly, but they are a dead end for AI. Without a semantic layer, they leave behind no audit trail, no structured metadata, and no clear representation of business logic. There’s nothing for an AI system to reason over.
Semantic-layered BI tools like Holistics, Looker or Omni, on the other hand, provide a structured, code-based map of your metrics, dimensions, and data relationships. They turn business logic into something both analysts and AI agents can understand, reuse, and build upon.
The more of your logic you encode in tools like these, the more capable your AI agents become.
How Holistics accelerates your AI-Driven Analytics Journey?
Holistics provides a modern data modeling and reporting platform designed to support self-service, scalable analytics making it a natural fit for an AI-augmented analytics workflow.
Semantic Layer made simple
Holistics offers a code-light modeling layer that lets you define business logic using SQL directly in the UI - without managing YAML files or external transformation layers.
- Define models using SQL queries or our custom DSL
- Create reusable dimensions and measures like “Monthly Recurring Revenue” or “Customer Churn Rate”.
- Use the visual interface to describe relationships, set default filters, and organize fields for easy discovery.
This approach gives you the power of a semantic layer without the complexity of traditional modeling tools.
Explore data with Natural Language
Once your business logic is modeled in Holistics, you unlock the full potential of Holistics AI, a conversational analytics experience that makes data exploration as easy as chatting with a data analyst.
Explore Mode lets you ask questions, build dashboards, and refine insights - all through a natural language conversation.
- Ask “What was our revenue growth last quarter?” and get instant answers with charts.
- Follow up with “Break it down by product line” or “Show YoY comparison”.
- Get helpful chart explanations and suggestions without ever writing SQL.
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Once your business logic is structured and accessible, AI can begin to take on truly meaningful tasks in analytics. Agents will move beyond simple SQL generation to:
- Explore hypotheses based on business context
- Evaluate changes in key performance indicators (KPIs)
- Explain variance and uncover root causes
- Assist in building and validating complex formulas
- Access and combine data across multiple dimensions seamlessly
That’s the future we’re building toward at Shearwater and Holistics.
Move your business logic to code. Structure your data with semantic layers. And give AI the context it needs to stop guessing and start reasoning.
Interested in watching the Holistics demo? Reach out to us to schedule a session!
