TrustSignal

AI-powered reputation assessment for advertising teams that measures consumer sentiment toward AI-generated ads and guides disclosure and messaging decisions to better align with trust expectations.

The Problem

“Advertising teams lack a reliable way to calibrate disclosure and messaging for AI-generated ads against real consumer trust expectations”

Organizations face these key challenges:

1

Advertisers often assume consumer comfort with AI-generated ads without evidence

2

Survey findings are fragmented across vendors, decks, and spreadsheets

3

Open-ended feedback is time-consuming to analyze manually

4

Disclosure wording decisions are inconsistent and difficult to standardize

Impact When Solved

Improves consistency of AI-ad disclosure decisions across campaignsReduces brand trust risk before campaign launchTurns survey and open-text sentiment into actionable messaging guidanceAccelerates research-to-decision cycle for creative and brand teams

The Shift

Before AI~85% Manual

Human Does

  • •Collect survey results, decks, spreadsheets, and open-text feedback from past research
  • •Review consumer sentiment manually and identify trust or disclosure concerns
  • •Debate disclosure wording and messaging choices across campaign stakeholders
  • •Decide launch approach based on judgment, limited research, and prior experience

Automation

  • •No consistent AI support in the legacy workflow
  • •Limited automation for aggregating fragmented research inputs
  • •Minimal analysis of open-ended feedback at scale
  • •No repeatable recommendation engine for disclosure or messaging decisions
With AI~75% Automated

Human Does

  • •Set campaign objectives and define the audience, channel, and disclosure decision to evaluate
  • •Review AI-generated trust findings and choose the final disclosure and messaging approach
  • •Approve high-risk or ambiguous recommendations with brand and legal judgment

AI Handles

  • •Aggregate survey responses, open-text feedback, and campaign context into a unified trust assessment
  • •Detect sentiment patterns, segment audiences by trust profile, and quantify disclosure sensitivity
  • •Recommend disclosure prominence, wording options, and messaging angles for each audience segment
  • •Generate evidence-backed summaries, decision memos, and alerts for elevated trust risk before launch

Operating Intelligence

How it works

AI runs the first three steps autonomously.

Humans own every decision.

The system gets smarter each cycle.

Confidence95%
ArchetypeRecommend & Decide
Shape6-step converge
Human gates1
Autonomy
67%AI controls 4 of 6 steps

Who is in control at each step

Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

Loop shapeconverge

Step 1

Assemble Context

Step 2

Analyze

Step 3

Recommend

Step 4

Human Decision

Step 5

Execute

Step 6

Feedback

AI lead

Autonomous execution

1AI
2AI
3AI
5AI
gate

Human lead

Approval, override, feedback

4Human
6↺ Loop
AI-led step
Human-controlled step
Feedback loop
TL;DR

AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.

The Loop

6 steps

1 operating angles mapped

Operational Depth

Free access to this report