AI Can Create Charts, But Can It Tell the Right Story?

Artificial intelligence is changing the way we work with data, but creating an effective visualization takes more than generating a chart. Great data storytelling is about helping your audience understand what matters, make informed decisions, and take action.

That's why I created my 5 AI Daily Wins for Data Visualization Challenge on LinkedIn Learning. Rather than focusing on prompt engineering or design theory alone, this course explores practical ways AI can enhance every stage of the visualisation process, from choosing the right chart to crafting a compelling narrative.

Start With the Story, Not the Chart

One of the biggest mistakes I see is people choosing chart types based on familiarity rather than purpose.

Bar charts get used for almost everything, pie charts become overloaded with categories, and line charts appear even when there's no time-based data. While these charts may technically work, they often bury the insight you're trying to communicate.

Use AI as a thinking partner. By describing your dataset, your audience, and the story you want to tell, AI tools like Claude, ChatGPT, or Gemini can recommend chart types you may never have considered, while also explaining the trade-offs behind each option.

The goal isn't to let AI make every decision, it's to broaden your thinking so you can choose the visual that best communicates your message.

Your Chart Title Should Deliver the Insight

Too many chart titles simply describe what's being displayed.

A title like "Q3 Revenue by Region" tells your audience what they're looking at, but not why it matters.

Instead, I encourage writing insight-driven headlines that communicate the takeaway before anyone studies the chart itself. AI can generate multiple headline options in seconds, helping you transform labels into messages that immediately capture attention and frame the story.

Often, a simple title change can dramatically increase the impact of an otherwise unchanged chart.

Color Should Be Intentional

Color is one of the first things people notice in a visualisation, yet it's often chosen without much thought.

Poor color choices can confuse viewers, misrepresent trends, or simply make charts harder to read. During the challenge, I show learners how to create purposeful color palettes that align with branding while following sound color theory.

Rather than selecting colors because they "look nice," the focus is on making visualisations clearer, more professional, and easier to interpret.

Accessibility Makes Better Visualisations

An effective chart should work for everyone.

Millions of people experience some form of color vision deficiency, yet many business dashboards and presentations still rely solely on color to distinguish information.

AI can quickly identify accessibility issues, recommend colorblind-safe alternatives, suggest improved contrast ratios, and even propose secondary visual cues such as labels or patterns. These small adjustments ensure visualisations remain clear across different audiences and devices. Accessibility is an essential part of effective communication.

Turn Charts Into Stories

A chart on its own presents information.

A chart with context persuades people to act.

That's why the final stage of the course focuses on narrative. AI can help generate introductions, key insights, and calls to action that transform a visualisation into a compelling story tailored to a specific audience.

Pairing your data with the right narrative makes your insights more memorable and far more likely to influence decisions.

AI Is an Assistant, Not a Replacement

AI should support, not replace, your expertise.

It can recommend chart types, generate headlines, suggest color palettes, review accessibility, and help shape narratives. But understanding your audience, interpreting the data, and deciding which story needs to be told will always require human judgement.

By the end of the five-day challenge, learners will have a practical, repeatable workflow for transforming raw data into visualisations that are sharper, more accessible, and more persuasive. More importantly, they'll understand how to use AI with intention by creating charts that don't just display data, but communicate it effectively and drive better business decisions.