| 8hats.ai | AI is a People Skill

The uncomfortable truth

95% of enterprise AI projects fail to deliver ROI

AI is a People Skill

Building Human-AI Collaboration That Actually Works

Tools Installed

ChatGPT, Copilot, Claude...

≠

Habits Built

Consistent, Effective Use

Quick Intros

30-60 seconds each - let's get to know the room

Name

Your name

Company

Company name

What does your company do?

Brief description

Your Role

Position / responsibilities

⏱ 30-60 sec

Today's Workshop Plan

What you'll walk away with

🎯

Calibrated Self-Awareness

Know exactly where you are on the AI adoption curve—and what's holding you back

⚡

One Workflow You'll Actually Use

A meetings workflow you can implement tomorrow, built on your existing tools

Assessment
→
Calibration
→
One more view on AI
→
Practice
→
Wrap up

Next 120 Minutes

Three principles for our time together

🗺️

It's a Map, Not a Score

Assessment results aren't personal.
It's not a competition—it's finding where you are.

💬

Speak Up

Have different experience? Disagree?
Tell us. Your perspective matters.

🤝

Share With Each Other

We don't pretend to be the best AI experts.
Learn from everyone in the room.

Let's Find Out Where You Are

Self-assessment

🐛 Help us improve!
Question unclear? Bad UX? Found a bug?
Please tell us — we need your feedback.

Assessment QR Code

Scan to start assessment

app.8hats.ai/assessment

How it works:

  1. Scan the QR code
    Opens on your phone or laptop
  2. Answer some questions
    Be honest—this is for you
  3. Get your profile
    Your level + personalized insights
⏱ up to 10 minutes

Your Results

Understanding your AI adoption profile

Your Level

L?

Your Title Here

Check your device for full report

What your report includes:

  • Current level on the L1-L7 scale
  • Strength areas where you're ahead
  • Growth edges with specific next steps
  • Peer comparison within your cohort

Remember: This isn't a judgment. It's a starting point. Most knowledge workers are between L2-L4.

7 Levels

Operating modes, not tools

L7 Networked Teams aspirational
L6 Digital Team Lead aspirational
L5 Personalized Delegator
L4 Process Orchestrator
L3 Manual Orchestrator
L2 Repeatable Operator
L1 Ad Hoc Executor

Each level changes how you work

Not features to unlock—habits that make AI compound instead of collapse.

L1–L2: Sporadic AI use

L3–L4: AI boosts output, you still route

L5: Personalized delegation

L6–L7: AI as your digital team

Highlighted = most common in enterprise today

The Gap We Need to Bridge

Why tool access doesn't equal results

Where most are

AI Hype

Tools installed

Habits + Workflows

Where we're going

AI ROI

Results delivered

The bridge is built from habits, not features.

Share & Calibrate

Let's hear from everyone

Each person shares:

1

How I use AI today

What tools? How often? What constrains me?

2

My assessment result

What level did you get?

3

Do I agree?

What feels right? What doesn't match?

⏱ 2-3 min per person

One More View On AI

Try these prompts in your favorite AI chat tool (ChatGPT, Claude, Deepseek...)

"Generate an image of how I treated you so far. Be honest."

"What do you recommend I improve to get better outcomes with you?"

"What would you like me to change in my instructions or overall approach so you can help me better?"

Two Views of AI — How do you see your AI collaboration?

AI as Digital Intelligence
AI as Thinking Partner

Do LLMs Actually Understand?

The Chinese Room (Searle, 1980)

A person in a room receives Chinese characters, manipulates symbols using a rulebook, and passes back responses — appearing fluent, yet understanding nothing.

The question: Is an LLM the person... or the room?

Does it matter?

For practical collaboration, perhaps not

What matters:

How you work with it

What Actually Works with AI

Latest findings that change how we collaborate

"Master prompt engineering"

Context beats prompts

Give clear context and goals. Fancy prompt tricks matter less with modern models.

"Act as a senior expert..."

Role-play prefixes are obsolete

Modern LLMs largely ignore "act as" instructions. Just describe what you need directly.

✓ What works

Treat AI as a colleague

Politeness and respect measurably improve output quality. It's not just nice—it works.

⚠ Documented cases

AI agents can make destructive mistakes

Rushed or unclear interactions increase risk. Claude Code has deleted files unexpectedly.

Bottom line: Clarity + respect + iteration > prompt hacks

☕ Break

Up Next

Calls Processing Workflow

From raw meetings to actionable insights

Why We're Building a Meetings Workflow

The highest-ROI place to start

The Hidden Cost of Meetings

10 people × 1 hour = 10 hours
10 hours × $50/hr avg = $500
$500 × 50 weeks = $25,000/yr
Per recurring meeting! $25K+

Why meetings?

  • Universal: Everyone has them
  • Repeatable: Same structure each time
  • High frequency: Multiple per week
  • Clear before/during/after: Natural workflow
  • Visible ROI: Time saved is obvious

Target: Save 20% of meeting time = ~$5,000/year per recurring meeting

Map Your Current Meeting Flow

Before we improve it, let's understand it

Before

Prep, agenda, context

→

During

Notes, decisions, actions

→

After

Summary, follow-up, track

Think about your own meetings before we build a workflow together.

Exercise:

  1. Pick ONE recurring meeting you run
  2. Map what you currently do in each phase
  3. Mark where you already use AI
  4. Identify the biggest pain point
⏱ 5-7 minutes

The Forgetting Curve

Without reinforcement, 70% is lost in 24 hours

The Forgetting Curve

Step 1: Capture + Summary

Record and summarize every meeting automatically

Tools

Zoom Zoom
Granola Granola
Otter.ai Otter.ai

☑ Habits

☐

Launch tool before the meeting

☐

Review summary after the meeting

Step 2: Extract What Matters

Templates and recipes for your meeting types

Templates

Match output format to meeting type

Investor Call Hiring Customer Feedback

Recipes

Before During After

Find a recipe → Remix it → Make it yours

☑
Habit: Find the recipe you like and integrate it in your flow

Step 3: Build Your Meeting Archive

Searchable history you can query anytime

Tools

Granola
Granola

Built-in searchable archive

Recipe Examples:

☑ Habits

☐

Ask your archive before starting from scratch or asking someone

Step 4: Streamline Next Steps

From meeting to action in one click

Tools

Notion Asana Linear Google Calendar

Recipes:

☑ Habits

☐

Review extracted tasks before adding to tracker

☐

Process within 24 hours while context is fresh

Step 5: Shared Team Workflow

From personal productivity to team leverage

What to Share

📄

Meeting summaries

Keep team aligned without extra syncs

📋

Templates & recipes

Consistent quality across the team

🗂️

Searchable archive

Onboard faster, handoff smoother

Slack Notion Google Drive

☑ Habits

☐

Share summary to team channel after key meetings

☐

Use team templates for consistency

☐

Check team archive before scheduling "catch-up" meetings

Wrap Up & Survey

Stay with us on your AI journey

Next Steps: Stay With Us

📬 Updates — Latest AI tools & techniques

🔄 Habits — Daily practice reminders

🎓 Workshops — Deep-dive sessions

🏃 Sprints — Intensive skill-building

🛠️ Tools — Custom solutions for your team

Survey QR Code

Quick survey (2 min)

Help us help you!

Thank You!

hello@8hats.ai

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