# Is your data ready for AI? Find out in 103.4 seconds

A short film and a written guide to checking the data behind one AI job: pick the job, list its data, check each piece, and fix the red first.

By Hone, October 20, 2026

Format: Explainer

“Is our data ready for AI?” is a hard question to answer for a whole business. It gets much easier when you ask it about one job.

The film walks through that check in 103.4 seconds, using a plumbing firm as a hypothetical example. The written guide below covers the same four steps in a little more detail.

## Why the data matters

An AI system can only help with a job if it can reach the information that job needs, and that information is right. When either part is missing, the output can look finished and still be wrong.

In February 2025, Gartner predicted that through 2026, organizations will abandon 60% of AI projects that lack AI-ready data.

## Step 1: Pick one job

Choose a single piece of work with a clear output. In the film, a plumbing firm wants AI to draft the 40 boiler quotes Sarah writes every week. The firm, Sarah, her customers and every number in the example are invented.

A narrow job gives you something to test. “Draft a boiler quote for Sarah to check” has a clear finish line, and you can compare the drafts with quotes she has already written.

## Step 2: List the data the job uses

Write down every source the job draws on. For a boiler quote in the example, there are four.

Hypothetical example: the data behind a boiler quote

| Source | Where it is | What the check finds |
| --- | --- | --- |
| Customer emails | Shared inbox | Easy to reach. Names differ from other records, and some emails include bank details. |
| Price list | Office wall | Prices from March 2023. |
| Old quotes | Filing cabinet | Paper only. |
| Supplier prices | Trade counter | Current as of October 2026. |

Make the list with the person who does the job. They know which sources they actually use, including the ones nobody wrote down.

## Step 3: Check each piece

Ask four questions about every source on the list.

- Can the AI get to it? The old quotes are on paper, so for now the answer is no.
- Is it up to date? The price list is from 2023, so every quote built on it would come out wrong.
- Is it consistent? The inbox says J. Smith and the job sheets say Smith, John. A person knows that’s one customer. The AI only knows if the records are matched.
- Is it safe to use? Some customer emails include bank details. Decide what the AI is allowed to see before you connect anything.

## Step 4: Score it and fix the red first

Give each source a color. Green is ready. Amber needs a tidy. Red is real work.

Start with the red items, because they block the job. In the example, that’s the paper quotes. Turning paper records into usable data is work AI does well, with a person checking what it extracts.

## Where it gets deeper

Each check has more to it. Matching customer records reliably, with a score for each match and a person reviewing the uncertain ones, is its own piece of engineering. So is making sure the AI only retrieves what each user is allowed to see, and testing and monitoring the system once it runs.

That’s the work Hone does. We’re AI engineers who find where AI fits in your business, then build it and keep it running.

## Sources

- Gartner, “Lack of AI-Ready Data Puts AI Projects at Risk” (February 26, 2025): https://www.gartner.com/en/newsroom/press-releases/2025-02-26-lack-of-ai-ready-data-puts-ai-projects-at-risk

## Video: AI data readiness in 103.4 seconds

Hypothetical example: the firm, people, prices and records in the film are invented, and the jobs-per-month chart is illustrative. The 60% figure is a Gartner prediction from February 2025.

[Watch the film](https://honesystems.io/blog/is-your-data-ready-for-ai) · [Captions](https://honesystems.io/blog/is-your-data-ready-for-ai/media/captions.vtt)

### Chapters

- [0:00 — Why it matters](https://honesystems.io/blog/is-your-data-ready-for-ai?t=0)
- [0:25 — Pick one job](https://honesystems.io/blog/is-your-data-ready-for-ai?t=25.4)
- [0:31 — List the data](https://honesystems.io/blog/is-your-data-ready-for-ai?t=31.667)
- [0:40 — Check each piece](https://honesystems.io/blog/is-your-data-ready-for-ai?t=40.733)
- [1:12 — Score and fix](https://honesystems.io/blog/is-your-data-ready-for-ai?t=72.933)
- [1:28 — Where to start](https://honesystems.io/blog/is-your-data-ready-for-ai?t=88.267)

### Transcript

[0:00](https://honesystems.io/blog/is-your-data-ready-for-ai?t=0.317) Is your data ready for AI?

[0:02](https://honesystems.io/blog/is-your-data-ready-for-ai?t=2.837) Let's find out, in a hundred and three point four seconds.

[0:06](https://honesystems.io/blog/is-your-data-ready-for-ai?t=6.617) Say you run a plumbing firm, and you want AI to draft the forty boiler quotes

[0:11](https://honesystems.io/blog/is-your-data-ready-for-ai?t=11.537) Sarah writes every week.

[0:13](https://honesystems.io/blog/is-your-data-ready-for-ai?t=13.517) That only works if the AI can reach the information it needs,

[0:17](https://honesystems.io/blog/is-your-data-ready-for-ai?t=17.777) and that information is right.

[0:20](https://honesystems.io/blog/is-your-data-ready-for-ai?t=20.117) Gartner expects sixty per cent of AI projects without that to be dropped.

[0:25](https://honesystems.io/blog/is-your-data-ready-for-ai?t=25.717) Step one: pick one job.

[0:28](https://honesystems.io/blog/is-your-data-ready-for-ai?t=28.497) We'll take boiler quotes, like the one John needs.

[0:31](https://honesystems.io/blog/is-your-data-ready-for-ai?t=31.983) Step two: list the data that job uses.

[0:35](https://honesystems.io/blog/is-your-data-ready-for-ai?t=35.723) Customer emails, the price list,

[0:38](https://honesystems.io/blog/is-your-data-ready-for-ai?t=38.283) old quotes, and supplier prices.

[0:41](https://honesystems.io/blog/is-your-data-ready-for-ai?t=41.05) Step three: check each one.

[0:43](https://honesystems.io/blog/is-your-data-ready-for-ai?t=43.93) Can the AI get to it?

[0:45](https://honesystems.io/blog/is-your-data-ready-for-ai?t=45.79) The old quotes are on paper, so no.

[0:48](https://honesystems.io/blog/is-your-data-ready-for-ai?t=48.85) Is it up to date?

[0:50](https://honesystems.io/blog/is-your-data-ready-for-ai?t=50.27) The price list is from 2023, so every quote would come out wrong.

[0:55](https://honesystems.io/blog/is-your-data-ready-for-ai?t=55.55) Is it consistent?

[0:57](https://honesystems.io/blog/is-your-data-ready-for-ai?t=57.09) The inbox says J. Smith, the job sheets say Smith, John.

[1:01](https://honesystems.io/blog/is-your-data-ready-for-ai?t=61.79) You know that's one customer.

[1:03](https://honesystems.io/blog/is-your-data-ready-for-ai?t=63.93) The AI doesn't.

[1:05](https://honesystems.io/blog/is-your-data-ready-for-ai?t=65.55) Is it safe?

[1:06](https://honesystems.io/blog/is-your-data-ready-for-ai?t=66.95) Some of those emails have bank details in them,

[1:09](https://honesystems.io/blog/is-your-data-ready-for-ai?t=69.83) so decide what the AI is allowed to see.

[1:13](https://honesystems.io/blog/is-your-data-ready-for-ai?t=73.25) Step four: score each one.

[1:16](https://honesystems.io/blog/is-your-data-ready-for-ai?t=76.29) Green is ready, amber needs a tidy,

[1:19](https://honesystems.io/blog/is-your-data-ready-for-ai?t=79.93) red is real work.

[1:22](https://honesystems.io/blog/is-your-data-ready-for-ai?t=82.13) Fix the red first.

[1:23](https://honesystems.io/blog/is-your-data-ready-for-ai?t=83.83) Here, that's the paper quotes,

[1:25](https://honesystems.io/blog/is-your-data-ready-for-ai?t=85.81) and AI is good at reading those.

[1:28](https://honesystems.io/blog/is-your-data-ready-for-ai?t=88.473) There are deeper levels to all this,

[1:30](https://honesystems.io/blog/is-your-data-ready-for-ai?t=90.573) and that's where Hone comes in.

[1:32](https://honesystems.io/blog/is-your-data-ready-for-ai?t=92.913) We're the AI engineers who find where it fits in your business,

[1:36](https://honesystems.io/blog/is-your-data-ready-for-ai?t=96.753) then build it and keep it running.

[1:39](https://honesystems.io/blog/is-your-data-ready-for-ai?t=99.283) Pick a job, list its data, check it,

[1:42](https://honesystems.io/blog/is-your-data-ready-for-ai?t=102.383) fix the red.

[1:43](https://honesystems.io/blog/is-your-data-ready-for-ai?t=103.743) A hundred and three point four seconds.