I recently tried an experiment:

Could I use Claude Code to build a Power BI executive dashboard without manually creating every measure, visual and formatting element?

Not just asking AI to explain DAX.

Not copying and pasting code between ChatGPT and Power BI.

I wanted the AI agent to actually work with the Power BI project itself.

So I gave Claude Code access to a Power BI project and asked it to turn an existing report into a clean, executive-ready dashboard.

The result gave me a very different perspective on where Power BI development is heading.

We’ve Been Using AI in Power BI the Wrong Way

Most analysts already use AI.

But usually, the workflow looks something like this:

“Write a DAX measure for YoY growth.”

Copy » Open Power BI » Paste » Error » Go back to AI » Copy again

Then manually create the visual, configure it, format it and position it.

AI is helping, but we are still doing most of the development ourselves.

I wanted to test a different model.

Instead of asking:

“How do I build this?”

I wanted to ask:

“Can you help me build this?”

That’s a subtle difference, but I think it’s an important one.

From AI Assistant to AI Agent

Using the Power BI PBIP project format, Claude Code and Power BI authoring tools, the AI could interact much more directly with the project.

Claude was able to understand the existing structure and help create the new executive summary.

It worked on:

  • DAX measures

  • Data model understanding

  • KPI cards

  • Monthly trend analysis

  • Waterfall analysis

  • Country performance tables

  • Report formatting

  • Custom theme

  • Visual positioning and layout

But one of my favourite parts wasn’t actually the DAX or the visuals.

It was the workflow.

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I Asked Claude to Understand the Business First

Instead of immediately telling Claude:

Create four KPI cards, one line chart and one waterfall.

I wanted the process to start with the business objective.

What does an executive actually need from this page?

What questions should the dashboard answer?

What deserves attention?

Only then should we decide which visuals belong on the page.

The workflow became something closer to:

This is much closer to how a good BI project should work.

And it points to something bigger than simply using AI to generate DAX.

Did Claude Build Everything Perfectly?

No.

And I deliberately show that in the video.

There were sorting issues.

Some formatting wasn’t right.

Certain visual decisions needed adjustment.

I made manual changes as well.

There were moments where the output needed debugging and another prompt.

But that’s precisely why I found the experiment useful.

I’m less interested in polished demos where someone enters one prompt and magically gets a perfect dashboard.

That’s not how real analytics projects work.

The more useful question is:

How much repetitive Power BI development can an AI agent take away from an analyst?

And based on what I’m seeing, the answer is becoming increasingly interesting.

Does This Mean Power BI Developers Won’t Be Needed?

I don’t think that’s the right conclusion.

Instead, I think what makes a good Power BI developer valuable is changing.

Consider DAX.

If AI becomes extremely good at generating DAX, memorising hundreds of functions becomes less important.

But understanding whether the generated measure is correct becomes more important.

You still need to know:

  • Is the data model designed correctly?

  • Is the filter context behaving as expected?

  • Is this KPI actually meaningful?

  • Does this visual answer the business question?

  • Are we comparing the correct periods?

  • Can we trust the result?

  • Is the dashboard helping someone make a decision?

AI can generate things incredibly quickly.

But generating something and generating the right thing are two very different problems.

That’s why I think the strongest analytics professionals over the next few years will combine:

Business Understanding + Data Modelling + Analytics + AI Agents + Judgement

Power BI Development Is Becoming More Agentic

Traditionally, our workflow has been:

Requirements → Data → Model → DAX → Visuals → Formatting → Testing

AI initially helped around the edges.

Need SQL? Ask AI.

Need DAX? Ask AI.

Need Power Query? Ask AI.

Need documentation? Ask AI.

But agentic tools introduce another possibility.

Instead of AI sitting outside Power BI and giving us snippets, the agent can increasingly participate in the development process itself.

That could eventually make the workflow look more like:

Business Problem → Analyst + AI Agent → Analytics Solution

The analyst isn’t removed from the process.

The analyst moves up the value chain.

Less time manually configuring things.

More time understanding the business, asking better questions, designing the solution and validating what the AI produces.

That’s the part of AI + BI that I’m most interested in exploring.

🎓 Want to Learn This Yourself?

I’m launching my new practical course: Agentic Power BI.

You’ll build a complete AI Business Analyst project using:

Power BI → Microsoft Fabric → AI-Ready Semantic Model → External Data → Business Context → AI Agent

This isn’t another “build a dashboard” course. The goal is to give you a portfolio-ready project and practical AI + Power BI skills you can demonstrate in your current role or your next interview.

🚀 First 50 Students: $99 AUD

Regular price: $199 AUD → Launch price: $99 AUD

Think about the economics.

A $5,000 salary increase is ~$96/week.
A $10,000 salary increase is ~$192/week.

The course costs $99 once.

Of course, no course can guarantee you a promotion or a new job. But if these skills help you stand out in one interview, take on higher-value work, or position yourself for your next opportunity, the potential upside can be far greater than the cost of learning them.

The bigger cost may be waiting while the skills employers expect continue to change.

👉 GET AGENTIC POWER BI FOR $99

Launch pricing is available to the first 50 students only.

👋 Want to Talk 1:1?

Courses aren’t always the right answer.

Sometimes you need someone to look at your specific situation.

I also offer a limited number of 1:1 mentorship sessions for people working in or moving toward data and analytics.

Depending on where you are in your journey, we can work on:

  • Power BI / Data Analytics career direction

  • Your learning roadmap

  • Resume and LinkedIn positioning

  • Portfolio and project strategy

  • Interview preparation

  • Power BI and Microsoft Fabric skills

  • Moving from traditional analytics toward AI-enabled analytics

The session is focused on your situation and your next steps, rather than following a predefined curriculum.

👉 BOOK A 1:1 MENTORSHIP SESSION

If you work with Power BI, Microsoft Fabric, data analytics or AI, subscribe to Analytical Guy — there’s a lot more coming.

And I’d love to hear your view:

If an AI agent could take over ONE part of your current Power BI workflow, what would you give it?

Cheers,
AJ
Perth, Australia
admin@analyticalguy.tech

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