Draft a Chart Explanation With AI at the Cursor: A Data Analyst's Workflow

The short answer: once you have checked an analysis, speak the verified inputs (metric definition, period, observation and caveat) into a compatible, focused text field in Windows. Then ask AI to arrange them into a structured chart explanation. The draft appears at your cursor, where you review and edit it before it goes anywhere. Every number and claim must come from you. Do not ask the AI to calculate, to explain causes or to supply dataset facts, and treat any such content in a draft as an error to remove.

This article covers the workflow, a setup step that protects your review, a before-and-after example, a reusable template, a review checklist, and a method for measuring whether the process shortens your time to reviewed output. The template, checklist and measurement method are useful with any drafting tool, including none.

A chart explanation is the short passage beside a visual in a report, dashboard note, ticket reply or email. It tells the reader what is plotted, over what period, what the checked analysis shows and what it cannot show.

SpeakLingo is designed to support this task with three capabilities:

• Online transcription in 99+ languages, so you can speak your inputs in a supported language that suits you and your reader.
• AI contextual formatting, which can turn loosely spoken material into a structured draft.
• Spoken AI text requests that produce text at a compatible, focused Windows text field. Where the cursor workflow fits your setup, the draft lands where you are already working, which can remove the step of copying from a separate AI window.

The boundaries matter as much as the capabilities:

• The workflow does not work in every application or field. Test your target field before relying on it.
• The product places text at your cursor. It does not take over your computer or decide what to do with the text. An optional Enter-after-delivery behavior can submit text in some apps, which is why the setup step below matters.
• AI requests need an internet connection, an enabled service, your consent and the relevant access.
• Audio and text may be sent to remote services to fulfil a request. If you opt in to screen context, that context may be sent as well. Bear this in mind when the chart or the screen around it contains anything you are not permitted to share.
• AI output is a draft and needs your review.

For a wider view of the product, see the features page and the use cases page.

Analysts often finish the demanding parts, the query, the validation and the visual, and then slow down on the sentences under the chart. A few common reasons:

1. The facts live in different places. The metric definition is in documentation, the period is in a filter, the observation is in your head and the caveat is in a note from days ago.
2. Structure takes manual effort. Even a four-part explanation needs ordering, consistent phrasing and a tone that suits the audience.
3. Switching tools adds steps. Writing a prompt in one window, waiting, copying the result and pasting it into the destination moves your attention away from the analysis.
4. A first written draft can be harder than saying it aloud. Many people can talk a colleague through a chart more easily than they can write the same explanation cleanly.

Syping is SpeakLingo's name for this speak-and-type approach, and the Syping page explains the idea. In this workflow it may ease the structuring and tool-switching steps (points 2 and 3), and it gives you a way to speak a first draft (point 4). It does nothing for point 1. You still need to gather and verify the facts before you speak them.

Two minutes of preparation protect the review step.

One boundary to understand first: to get a drafted explanation, use the supported AI Task workflow and put the instruction and the verified facts together in that one spoken request. Ordinary dictation alone does not turn on AI. Your earlier dictations, text already in the field and whatever is on your screen are not automatically available to the AI. A request such as "explain the chart above" gives it nothing to work from. The metric definition, period, observation and caveat must be in the request itself. Screen context is a separate opt-in, and what it captures may be sent to remote services.

1. Turn off automatic Enter or send behavior. If your setup includes the optional behavior that presses Enter after text is delivered, switch it off for this workflow. In some apps, Enter submits a message, a comment or a ticket reply, and you want the draft to sit in the field unsent until you have checked it.
2. Pick a compatible, focused text field. A document, an email draft or a ticket comment box are typical targets. Click into the field so the cursor is active, then run a short test with a harmless sentence to confirm the text lands where you expect.
3. Confirm your connection and service. AI requests need internet access, an enabled service and your consent. If any of these is missing, plan to structure the explanation by hand.
4. Decide about screen context. It is optional and opt-in. If you enable it, close windows and dashboards that show anything you are not permitted to share.
5. Gather your four verified inputs. Have your results open where you can see them, but off the shared screen if you are not using screen context deliberately.
6. Review the draft before sending or using it. The final read is yours, and nothing in this workflow replaces it.

The workflow uses a deliberately small set of inputs. Each one should be something you have already checked.

Interpretation and cause are absent from this table on purpose. If your analysis supports a particular interpretation, say it as part of the observation and keep it as strong as the evidence allows. If it does not, leave the topic out of the request rather than inviting the draft to speculate.

The example prompt for this workflow is:

Using only these verified inputs, draft a chart explanation. Inputs: [Metric definition, period, observation, caveat]. Use a clear professional structure. Flag missing facts; do not invent them.

The last instruction earns its place. A draft that says "Missing: data source not provided" is more useful than one that quietly fills the gap with a plausible guess.

The scenario below is fictional and uses invented, non-sensitive figures. It shows the shape of the workflow. It does not describe a real dataset, a product test or a measured result, and the "draft" is an illustration of what a draft might look like, not a recorded output.

Context: An analyst has checked a line chart of weekly active trial accounts for a fictional product. She needs a short explanation to sit under the chart in an internal summary.

Before: rough notes

Her first pass might look like this:

weekly active trial accounts, went up in march I think 410 to 465, but we changed how events get logged in week 3 so not sure it's apples to apples, maybe the promo too, need to check, definition is accounts with at least one session

The notes contain real information, but a reader would struggle with them:

• The metric definition is buried at the end.
• The period is vague ("march").
• The observation and the caveat are tangled together.
• "Maybe the promo too" is speculation that could be read as a finding if someone tidied the sentence without thinking.
• The structure is hard to scan.

The spoken request

After checking her figures, she places the cursor in her document's text field and speaks:

Using only these verified inputs, draft a chart explanation. Metric definition: weekly active trial accounts means trial accounts with at least one session in the week. Period: the four weeks of March, weekly granularity. Observation: the chart shows the count rising from 410 in the first week to 465 in the last week. Caveat: event logging changed in the third week of March, so the weeks before and after the change may not be directly comparable. I have not tested whether the promotion affected the figures. Use a clear professional structure. Flag missing facts; do not invent them.

She turns the promotion into an explicit "not tested" statement. The draft can then mention it as an open question without implying an effect.

After: an illustrative draft at the cursor

A draft along these lines is what she might then review:

Chart: Weekly active trial accounts, March (weekly)

Metric: Weekly active trial accounts are trial accounts with at least one session in the week.

What the chart shows: Across the four weeks of March, the count rises from 410 in the first week to 465 in the last week.

Caveat: Event logging changed in the third week of March, so weeks before and after the change may not be directly comparable. The effect of the promotion has not been tested, so this chart does not support a conclusion about it.

Missing information: The data source and the year are not provided.

What the analyst's review changes

Her review is where responsibility sits:

• She checks 410 and 465 against her verified results. Both match, so they stay.
• She adds the year and data source from her notes, which resolves the flagged gap.
• She reads for wording that implies cause. "Rises" describes the chart. A phrase such as "driven by" would be deleted.
• She confirms that "may not be directly comparable" is as strong as her validation supports. She tightens it only if she knows more.
• She checks that the heading and tone suit the audience of the internal summary.

The AI arranged the material. The analyst owned every fact and every claim.

Keep this skeleton in your notes and speak into it, replacing the bracketed items with your own verified material.

Chart: [metric name], [period], [granularity]

Metric: [definition, including inclusions and exclusions]

What the chart shows: [observation, using only checked values and describing the pattern without explaining its cause]

Caveat: [data issues, scope limits, tracking changes; untested explanations stated as untested]

Missing information: [anything the draft flags that you still need to supply]

For the spoken request, add this line after your inputs:

Use only the inputs I provide. Do not calculate, infer causes or add data. Flag any missing facts.

Using the same skeleton across a report helps readers learn where to find the definition and the caveat. If your team has its own house format, speak that structure's headings instead and keep the four inputs the same.

A few habits make the cursor workflow more reliable:

• Check the field first. Confirm that your destination is a compatible, focused Windows text field. If it is not, expect the workflow not to work there.
• Speak numbers deliberately. Transcription can mishear figures, so check each digit in the draft against your results.
• Name the structure aloud. Saying "metric definition... period... observation... caveat..." gives the formatting a clear map.
• Mind what is on screen. If you have opted in to screen context, anything visible may be sent to remote services, so use it only when you have access and permission to share what is shown.
• Read the whole passage. With automatic Enter turned off, the draft stays in the field until you act on it. The final read is the last safeguard before the text leaves your editor.

Run this list on every AI-assisted chart explanation. It is an illustrative writing practice, not a formal standard or professional advice. Adapt it to your team's own conventions.

Facts - [ ] Every figure in the draft matches my checked results, digit by digit. - [ ] The metric definition matches my team's documented definition. - [ ] The period, start and end dates and granularity are correct. - [ ] No figure appears that I did not supply.

Claims - [ ] The draft describes what the chart shows without asserting a cause. - [ ] Any untested explanation is labelled as untested, or removed. - [ ] Words such as "because," "due to," "driven by" and "proves" are absent, or backed by analysis I can point to. - [ ] The draft contains no calculated values (changes, percentages, averages) that I did not compute and verify myself.

Caveats - [ ] Known data issues and tracking changes are stated. - [ ] The caveat is as strong as my validation supports, with no excess hedging and no overstatement. - [ ] Flagged missing facts are filled in or deliberately left out.

Audience and context - [ ] Tone and level of detail suit the reader. - [ ] Nothing confidential is included beyond what the audience may see. - [ ] The text has not been submitted anywhere before my review. - [ ] I am comfortable putting my name next to this explanation.

Whether this workflow helps is a question for your own work, so measure it. The useful measure is time to reviewed output: the span from starting the explanation to having read, corrected and approved text that is ready to use. Drafting speed alone can mislead, because a quick draft that needs heavy correction may take longer overall.

A simple way to run the comparison:

1. Pick comparable charts. Choose explanations of similar complexity, such as simple trend charts with one caveat each. Avoid comparing a simple chart with a complicated one.
2. Define the start and end. Start when you open the destination field to begin the explanation. End when you finish your review checklist and accept the text.
3. Count everything in between. Include speaking, waiting for the draft, fixing transcription errors, filling flagged gaps and the full checklist review.
4. Record both methods. Time several explanations with your current method and several with the cursor workflow, using the same reviewer (you) and the same checklist for both.
5. Tally corrections. Note what you had to fix: misheard figures, unsupported wording, missing caveats. Frequent corrections suggest your spoken inputs need to be more explicit.
6. Compare across a spread. One fast or slow instance tells you little.

If the cursor workflow does not shorten your time to reviewed output for a given kind of chart, keep your existing method for that kind.

Online transcription supports 99+ languages, so you can speak your inputs in a supported language appropriate to you and your reader. This is a transcription capability. It is not a translation feature, and it does not guarantee that AI output will be available or equally strong in every language. Transcription has its own mode, setup and access requirements, so you cannot assume it is available just because AI is, or the reverse. Read the draft in the language you intend to use before accepting it.

AI requests need an internet connection. If your connection is interrupted, offline English transcription is only a fallback, and only if it has been configured in advance. It is not something to assume. AI formatting and AI requests do not work offline, so you would structure the explanation by hand until you are back online.