Confidence Ladder

AI CONFIDENCEENABLE

Purpose Stage-gate AI use so teams rack up safe, fast wins before high-stakes rollout.
Intervention type Behavioural scaffolding & risk-managed adoption
Lead AI programme or team leader
Time 45 min solo, 90 min group

Expected outcomes

  • User sees a clear, low-risk path to try AI

  • Team logs measurable wins on a public ladder

  • Business gets data on speed/quality deltas

  • Org aligns risk appetite with real safeguards

What to bring to the session

  • Confidence-Ladder Board (build via the steps below)

  • Ladder Cheatsheet (below)

Steps

1 | Set up

Step 1: Build the Board
Show the Confidence Ladder (Shadow, Co-pilot, Autopilot) with a blank KPI box visible to all participants.

Step 2: Shortlist Anchor Tasks
Ask participants to identify workflows that:

  • Take ≤ 30 minutes

  • Recur often

  • Are safe to experiment with


Think about:

  • “Would failure here cause real damage?” (Yes → find a new option)

  • “Do we already have workarounds?” (Yes → good friction point)


2 | Task Selection

Step 3: Vote on One Anchor Task
Use dot voting to agree on one priority task.

Step 4: Capture the Baseline
Log baseline data using available metrics or team estimates.

Think across:

  • Time

  • Effort

  • Quality

  • Happiness

3 | Build the Ladder

Step 5: Fill in the Shadow Rung
Define how AI will support without taking over:

  • AI role

  • Human role

  • Guard-rails required (e.g. sandbox only, human approval required)


Tip: Not sure on what this rung looks like? Read the cheat sheet below.

Step 6: Define Co-pilot and Autopilot Rungs
Repeat for each level.

Step 7: Set Risk Gates
Complete the Risk-Gate for each rung:

  • Where can this run (pilot, live)?

  • What would trigger rollback?


Tip: Struggling? Use the Risk-Gate Sheet below to help.

4 | Lock the Loop

Step 8: Schedule the 3Fs Stand-up
Set a recurring 15-minute check-in using the 3Fs:

  • Facts: Did AI save time or match quality?

  • Feelings: Confidence rating (1–5)?

  • Fixes: One improvement for tomorrow

5 | Launch & Progress

Step 9: Assign Owners
Nominate:

  • Ladder Owner → runs stand-ups

  • Scorekeeper → logs metrics

Step 10: Launch the Shadow Rung
Post the ladder in Slack and start Shadow Mode today.

Step 11: Advance Based on Readiness
Only move up if:

  • AI maintains or improves quality

  • Confidence ≥ 80%

  • No rollback triggers for 2+ days

Resources

Risk-Gate Sheet

How to use

  1. Tick the highest threshold you’ll allow at this stage.

  2. Tick / fill triggers that matter for this workflow.

  3. Post the completed sheet next to your Confidence Ladder so everyone knows the fail-safes.

Ladder cheatsheet

Level 1: Shadow

AI suggests. Humans decide.
This is the safest place to start. AI can generate ideas, drafts, or suggestions... but nothing goes live.

What this looks like:

  • AI gives you headline options, summary suggestions, or draft text.

  • You decide what (if anything) to use.

  • You’re still doing the real task, AI is just a silent helper.

Examples:

  • Suggested email subject lines

  • Headline ideas for a report

  • Summary of a Slack thread

Level 2: Co-pilot

AI drafts. Humans edit.
Here, AI takes the first pass, but humans still check and approve everything before it goes out.

What this looks like:

  • AI writes the first version

  • You review, improve, and approve the final result

  • The task gets done faster, but you’re still in control


Examples:

  • First draft of a weekly update email

  • Slide deck based on meeting notes

  • AI writes a KPI report, you check the data and add commentary


Level 3: Autopilot

AI does most of the work. Humans spot-check.
Now AI runs the task by default, and humans step in only when needed. This is only for trusted, proven workflows.

What this looks like:

  • AI generates the final version automatically

  • You check 1 in every 5 outputs

  • You trust the process, but you’re still watching for red flags


Examples:

  • AI sends daily news summaries

  • AI fills in CRM records after calls

  • AI generates standard usage reports every month

Other methods within the enable block

Human-AI Performance

By Lauren A Kelly

© 2026 Alterkind Ltd. All rights reserved.
Human-AI Performance™ is a proprietary methodology developed by BehaviourStudio using our Behaviour Thinking® framework. All content, tools, systems, and resources presented on this site are the exclusive intellectual property of Alterkind Ltd.

You’re welcome to use, share, and adapt these materials for personal learning and non-commercial team use.

For any commercial use, redistribution, or integration into client work, services, or paid products, please contact lauren@laurenakelly.com to discuss licensing terms.

Icons by Creative Mahira, The Noun Project.

Thanks to Nicholas Edell, Valentina Tan and multiple VPs implementing AI for your feedback during development.

LICENSE
Based on work by Lauren A Kelly.
For commercial licensing contact: lauren@laurenakelly.com