# AI disclosure structured by feature, model, data, and controls

> Write AI trust-center disclosures in the buyer's review order: what the feature does, which model it uses, what data touches it, and what controls sit around it.

- Canonical HTML: https://growth.iangoh.com/growth-ideas/ai-disclosure-structured-by-feature-model-data-controls/
- Source: [drata.com](https://drata.com/blog/introducing-ai-feature-items)
- GrowthDex source hub: [Drata](/sources/drata-drata-com/)
- Last checked: 2026-05-28
- Rarity: rare
- Budget: free
- Channels: Website, Security, AI Discovery
- Stages: consideration, security review, ai transparency, b2b


## Why this can grow

AI trust pages fail when they sound like marketing copy instead of review material. Drata says its AI Feature Items are organized around feature, model, data, and controls. That structure works because it matches the questions buyers already ask in procurement and security review, which makes the answer easier to scan, easier to compare internally, and easier to reuse across deals.

## Ian's take

From scaling consumer platforms across MENA and Southeast Asia, my default is to distrust growth work that only looks good in a slide. My bias is to treat this as a small market test first. Make the audience narrow, make the promise concrete, and let the first real response decide whether it deserves more work. I would run it small enough to learn quickly, then only scale the parts that real users repeat, save, reply to, or buy from. For this tactic, I would watch one clear growth signal before putting more time or budget behind it.

## Action plan

1. Define one narrow startup segment where ai disclosure structured by feature, model, data, and controls can create a measurable lift.
2. Turn the tactic into one offer, page, campaign, or workflow for the Website and Security channel.
3. Use the evidence from drata.com to set the first version of the message, format, and audience.
4. Launch a small test for 7 to 14 days with one success metric: one measurable growth signal.
5. Review the result, keep the winning message, remove weak variants, and turn the learning into a repeatable growth playbook.

## Source-backed example

Drata says its AI Feature Items use a structured narrative organized around feature, model, data, and controls.

## Adjacent tactics in the same lane

- [AI feature disclosure inside the trust center](/growth-ideas/ai-feature-disclosure-inside-the-trust-center/) - same source, 3 shared channels, 4 shared stages
- [AI governance disclosure with bias, data, testing, and oversight](/growth-ideas/ai-governance-disclosure-with-bias-data-testing-oversight/) - same source, 2 shared channels, 4 shared stages
- [Trust center canonical links over duplicate security docs](/growth-ideas/trust-center-canonical-links-over-duplicate-security-docs/) - 2 shared channels, 3 shared stages
- [NDA-verified sensitive doc access in the trust center](/growth-ideas/nda-verified-sensitive-doc-access-in-trust-center/) - 2 shared channels, 3 shared stages

## Read GrowthDex essays

Browse the plain-English essay index at [GrowthDex Blog](/blog/).

## Related GrowthDex essays

- [The trust page should answer in the buyer's order](/blog/the-trust-page-should-answer-in-the-buyers-order/) - brand trust, B2B growth, AI products

## Advisory

If you want help turning this into a working growth system, Ian Goh offers advisory at https://iangoh.com/advisory.