• Internal AI champions play a vital role in helping teams explore and adopt new ways of working.
• But being a champion can be isolating, especially when everyone assumes you have the answers.
• Coaching provides a safe space for champions to reflect, navigate ambiguity, and build influence without needing to be “the expert.”
• Support isn’t just about skills — it’s about confidence, connection, and clarity.
• If you want adoption to spread, invest in the people carrying the message.

Who Are Your Internal AI Champions?

They’re usually the ones who lean in during early workshops. The ones who say:

“I gave it a go over the weekend and it worked!”
“Could we try this in our team?”
“I showed it to a colleague and they loved it.”

We’ve written before about what makes a great AI champion. They’re not always the most senior. They’re not always in tech.

But they’re often the spark that moves an organisation from talk to action.

Why Champions Need Coaching, Not Just Tools

Once a champion is identified, the temptation is to give them some training, access to AI tools and maybe a toolkit — and ask them to go forth and share what they know.

But here’s the thing:

They’re still figuring it out, too.

They often feel:

• Uncertain — “Am I doing this right?”
• Exposed — “Will people think I’m the expert now?”
• Stuck — “This would work, but we’d need buy-in from above.”
• Frustrated — “There’s interest, but no one is making space for it.”

Coaching gives them a space to say these things out loud — and work through them.

What Does Coaching Actually Offer?

It’s not about training. It’s about thinking.

A well-timed coaching conversation can help a champion:

• Reflect on what’s working (and what isn’t)
• Reframe challenges in a more constructive way
• Make sense of internal dynamics or politics
• Prepare for conversations with leaders or sceptics
• Stay connected to their own curiosity and motivation

And sometimes, it’s just a space to say:

“This is harder than I thought — and I’m not sure what to do next.”

That’s where confidence grows.

When Everyone’s Figuring It Out, Champions Feel the Pressure

One of the most common patterns we see?

Champions are excited at first — but after a while, they start to doubt themselves.

Why? Because as interest in AI grows, so do the questions… and expectations.

People start turning to the champion for answers. For reassurance. For direction.

And the champion’s internal voice often says:

“I was just experimenting. I don’t really know.”

Without support, that doubt can quietly shut things down.

Champions Don’t Need More Content — They Need Coaching

Of course they’ll benefit from shared resources, toolkits, or prompt guides.

But if you want them to grow as confident, influential enablers of change?

What they really need is:

• Space to reflect
• Somewhere to bring questions
• Encouragement to be curious, not certain
• A place to test ideas without the pressure to perform

That’s what coaching offers.

Why This Matters for the Whole Organisation

Supporting your champions isn’t just about them. It’s about momentum.

Because champions who feel:

• Heard → are more resilient
• Equipped → are more influential
• Supported → are more consistent
• Connected → are more likely to stay engaged

And champions who keep going help others keep going, too.

Let’s Explore AI Together

In our Explore AI Together programme, we coach internal champions through the messy middle — not just with tools, but with time to think.

We create space for reflection, support decision-making, and help build confidence in the face of uncertainty.

If you’re developing champions inside your organisation, let’s talk about how to support them in a way that lasts.

• AI adoption isn’t about making big bets — it’s about testing what works in real situations.
• Small, focused experiments reduce risk and build confidence across the team.
• You don’t need a strategy doc to get started — just a clear challenge, a few willing people, and space to learn.
• Think of experiments like sprints: short, structured, and user-centred.
• Teams don’t need AI expertise — they need permission to try.

Not Sure Where to Start? That’s the Point.

The biggest blocker to AI adoption isn’t the tech — it’s the pressure to get it right. Many teams don’t start because they don’t know where to start.

“We’re waiting for the right use case.”
“We don’t want to get it wrong.”
“We’re just watching what others do first.”

That’s exactly why small, structured experiments are so useful. They give you a way to learn as you go — and build confidence through doing, not just talking.

What Makes a Good AI Experiment?

AI experimentation doesn’t need to be complicated — in fact, the best experiments are the simplest.

Here’s what we’ve found works well:

• Real task: Something someone is already doing
• Clear goal: What are we trying to learn or improve?
• Quick cycle: A few days or weeks, not months
• Willing team: Volunteers who are open and curious
• Low risk: Mistakes are fine — that’s the point

It’s not a case study. It’s a test.

How to Choose What to Experiment With

Start by asking:

• “What’s slowing us down?”
• “Where’s the friction?”
• “What’s repetitive or draining that we wish was easier?”

Then try a simple challenge-based structure:

“How might we use AI to help us [insert task] in less time, with less stress, or with better results?”

It might be:

• Drafting internal updates
• Analysing post-event feedback
• Structuring a proposal
• Writing a first version of a policy
• Summarising a call or meeting

If the outcome helps someone think more clearly or work more efficiently, you’re in the right place.

Think Like a Sprint, Not a Project

You don’t need a project plan or roadmap to experiment. You need:

• A rough idea
• A couple of real users
• A short window of time
• A follow-up moment to ask: “What worked? What didn’t? What now?”

If you’ve used design thinking before, this will feel familiar. It’s not about building the perfect solution — it’s about learning quickly, together.

Use AI as a Thinking Partner, Not Just a Tool

In all our experiments, we invite teams to interact with AI tools as collaborators — not as systems to be trained or mastered.

You can prompt tools like ChatGPT with:

• “How could we approach this differently?”
• “What are three different ways we could test this idea?”
• “Can you summarise key insights from our notes so far?”

And then you can ask:

“What do we still need to decide for ourselves?”

That’s where the thinking happens — and that’s where trust grows.

Why Small Experiments Lead to Big Shifts

A single experiment won’t change your organisation. But the impact goes beyond the test itself.

Done well, a small experiment:

• Builds team confidence
• Sparks new ideas
• Makes AI feel real, not abstract
• Gives leaders something to build on

And maybe most importantly:

It turns people from spectators of change into participants in it.

Let’s Explore AI Together

If you’re not sure how to begin, start by running a small, safe experiment that matters to your team.

At Maine Associates, we help teams frame meaningful challenges, choose the right tools, and run practical tests that build confidence.

Our Explore AI Together programme is built around experimentation, not just education.

Want to try something real — and see what happens? Let’s start with a conversation.

• AI tools don’t “know” your situation — they only respond to what you give them.
• Many weak outputs are the result of unclear or missing context, not poor technology.
• You can dramatically improve results by giving your AI tool a simple background brief.
• Framing matters: tell the tool what role it’s playing, who it’s helping, and what you’re trying to do.
• Good prompts are generous with information — not just clever with words.

Why Does AI Sometimes Miss the Mark?

Ever had an AI response that felt:

Too generic?
Off-target?
Like it didn’t “get” what you were trying to do?

Chances are, it wasn’t the tool — it was the lack of context.

AI doesn’t come with a memory of your business, your team, or your preferences. It works with what you give it — and if you don’t give it enough, it fills in the blanks with something average.

What Do We Mean by Context?

In a conversation with a colleague, you don’t have to re-explain:

• What your business does
• Who your customers are
• What tone you like
• Why you’re working on this task in the first place

But with an AI tool, you do.

Think of it like working with a smart intern on day one.
If you don’t brief them, they’ll guess — and get it wrong.

Examples: How Context Changes Output

❌ Basic Prompt:

“Write a welcome email for our new subscribers.”

✅ With Context:

“You’re writing a welcome email for a new subscriber to our monthly business strategy newsletter. They’re mostly time-pressed SME owners who want practical advice in a warm, informal tone.”

Result:
The second version isn’t just better written — it feels closer to your voice and intent.

❌ Basic Prompt:

“Summarise this meeting.”

✅ With Context:

“You’re a team assistant creating a summary of a cross-functional product meeting. Focus on decisions made, questions raised, and next steps. Keep it to three bullet points per topic.”

Result:
Less ramble, more relevance.

What Kind of Context Should You Include?

Here’s a quick framework you can drop into almost any prompt:

1. Who’s the audience?
   • “This is for my client / board / junior team / newsletter subscribers…”
2. What’s the purpose?
   • “I’m trying to clarify, simplify, persuade, or explore…”
3. What role should AI play?
   • “Act like a strategist / editor / facilitator / analyst…”
4. What output do you want?
   • “Summarise in bullet points / give step-by-step actions / suggest three options…”

Try This Prompt Template

“You are [role]. You are helping me [goal]. The audience is [description]. Please format the output as [structure or style].”

Example:

“You are a strategist helping me plan a team workshop. The audience is senior leaders who are curious but sceptical about AI. Please format the output as 3 high-level talking points followed by 2 actionable suggestions under each.”

Why This Matters

When people say “AI isn’t very good,” what they often mean is:

“AI didn’t read my mind.”

But it’s not supposed to.

AI is at its best when it’s treated as a smart assistant with zero context — and given what it needs to succeed.

Better inputs = better outcomes.

Let’s Explore AI Together

At Maine Associates, we help teams build real-world confidence with AI — not through theory, but through hands-on learning.

If your team’s been disappointed by AI results, it might be a context problem — not a capability one. Let’s explore how smarter prompts can unlock better thinking.

• Confidence with AI grows from small wins using approachable tools
• Early experiences with AI should feel useful, relevant, and rewarding
• Simple tools are powerful gateways to curiosity and deeper capability
• Introducing AI as a thinking partner reduces fear and builds trust

In our last post, we explored why successful AI adoption starts with mindset—curiosity, experimentation, and a willingness to think differently.

But once that mindset is sparked, the next step is key:

Give people a simple tool, a small win—and watch their confidence grow.

We’ve seen it time and again: the right tool, introduced at the right moment, flips the switch.

Suddenly, AI isn’t abstract or intimidating. It’s useful. Approachable. Even empowering.

What Does That Confidence Moment Look Like?

It usually starts with a raised eyebrow. Then a smile.

Someone sees an AI tool complete a task in seconds—something they usually dread—and says:

“I didn’t know I could do that.”

That moment signals more than just convenience. It’s a shift in belief. A rethinking of what’s possible.

We’ve seen it happen with tools like:

• Otter or Fathom for meeting summaries
• ChatGPT for transforming rough ideas into polished writing
• Canva’s AI tools for simplifying creative work

They may seem basic. But that’s the point. These tools lower the barrier and invite people in.

How Does Confidence Change Behaviour?

After that first positive experience, we often see:

• People try the tool again—this time for a more ambitious task
• They share it with a colleague
• They begin asking more strategic questions, like:
  

  “Could this help with that client report?”
  “What else can I automate?”

This is how confidence grows—from relevance, not theory.

It starts with a tool that works in a way they understand, on a task that matters to them.

Why Introduce AI as a Thinking Partner, Not a Threat?

One of the biggest barriers to AI adoption is fear—fear of doing it wrong, being judged, or being replaced.

That’s why we frame AI tools as thinking partners.
Not as decision-makers, but as:

• Problem-solvers
• Idea-expanders
• Creative collaborators

It’s not about replacing human thinking. It’s about extending it—with control and clarity.

Are Simple Tools Really Enough to Build Capability?

Yes—but not because they’re simple. Because they’re relevant.

We don’t teach tools as an endpoint. We teach them as gateways to:

• A stronger sense of agency
• A willingness to experiment
• Deeper curiosity about what’s possible next

Real capability grows from small, supported steps—especially when those steps feel meaningful.

Want to Help Your Team Build Confidence with AI?

If you’re looking to introduce AI in a way that builds confidence—not confusion—we can help.

Our AI Training & Skills Development programmes meet people where they are, using practical tools to:

• Spark new thinking
• Build trust
• Encourage experimentation

Let’s start with what your team is already curious about.

• AI adoption starts with simple, meaningful wins that feel relevant to your team’s daily work.
• Use cases that solve real, repeatable problems help build trust and capability.
• These five examples are easy to pilot, low-risk, and often overlooked as strategic starting points.
• Small successes with foundational tools can unlock a mindset shift toward experimentation.
• AI works best when introduced as a thinking partner, not just an automation tool.

Where Should Teams Start with AI?

When organisations first explore AI, it’s easy to get pulled toward high-impact or high-profile use cases — marketing automation, customer support bots, or entire workflow overhauls.

But most teams don’t need a revolution to get started.

What they need is a real task, a small success, and a better way to think about what’s possible next.

These five practical use cases are ideal for early-stage AI adoption — because they’re grounded in day-to-day reality. They’re simple to test, relevant to real needs, and powerful enough to shift the way people think about AI.

What Are the Best Use Cases for Building Confidence?

1. Onboarding and Internal Knowledge Sharing

The challenge:
New starters have lots of questions. Existing team members lose time answering the same ones.

The opportunity:
Use AI to create a simple internal chatbot or assistant trained on onboarding documents, FAQs, and team processes.

Why it builds confidence:
AI becomes a helpful colleague — not a complex system — and the benefits are felt immediately.

2. Internal Communications and Drafting Support

The challenge:
Crafting clear, well-judged internal messages takes time — and tone really matters.

The opportunity:
Use AI to draft or review announcements, updates, and meeting follow-ups, especially when nuance is important.

Thinking partner tip:
Ask AI: “Can you suggest a more inclusive way to say this?” or “How might this land with someone in operations?”

3. Meeting Summaries and Action Tracking

The challenge:
Key ideas get lost in messy notes (or aren’t written down at all).

The opportunity:
Use tools like Otter, Fathom, or Fireflies to auto-generate summaries with clear action points.

Why it works:
People instantly see the benefit — and it builds trust in AI as something that helps them, not watches them.

4. Making Sense of Raw Input

The challenge:
Workshops, surveys, and team discussions create a flood of sticky notes and documents — but not always clear insight.

The opportunity:
Use ChatGPT or similar tools to analyse raw notes, surface patterns, and generate useful summaries.

Confidence booster:
AI becomes a co-analyst — helping your team reflect, prioritise, and move forward faster.

5. Structuring Presentations and Reports

The challenge:
Blank-page syndrome. Reports and decks take longer than they should.

The opportunity:
Use AI to help structure rough thinking into a first draft — not to replace insight, but to get things moving.

Voice-of-user:
The light-bulb moment: “I didn’t know I could use AI to organise my ideas — it’s like a sounding board.”

How Do You Know Where to Begin?

Start by asking:

• “What’s slowing us down?”
• “What feels clunky or repetitive?”
• “Where do people spend time that AI could simplify — even slightly?”

Then choose one area to explore — ideally something:

• Low risk
• Easy to measure
• Frequently repeated

That first use case isn’t just about saving time — it’s about building belief.

Remember: It’s Not About the Tool — It’s About the Shift

These examples may seem simple. But they work.

Because they meet teams where they are — not where the AI industry wants them to be.

Small, practical use cases create the confidence needed to explore bigger ideas down the line.

And that’s what makes adoption sustainable.

Let’s Explore AI Together

At Maine Associates, we help teams identify meaningful use cases and build confidence through low-risk experimentation.

Our Explore AI Together programme starts with what’s real and relevant — and builds a path from early success to long-term capability.

Want to spot the right use cases for your team? Let’s start with a conversation.

• Great AI prompts start with clarity, not cleverness.
• Before asking ChatGPT anything, ask yourself: What’s the job to be done?
• Prompts work best when they reflect your actual goal — not just what you want written.
• Whether you’re exploring, deciding, or creating, the key is to think before you prompt.
• Clarity in = clarity out.

Why Do Some Prompts Work Better Than Others?

If you’ve ever thought:

“This AI output isn’t what I wanted…”
“That’s not how I would’ve said it…”
“It feels generic or off…”

You’re not alone.

But it’s usually not the model — it’s the framing.

Before diving into prompt hacks or fancy structures, start with this question:

What’s the job I want AI to help with?

That simple shift unlocks better results — and better thinking.

Think Like a Designer, Not Just a User

When you approach AI with vague instructions like:

• “Write me a plan”
• “Give me some ideas”
• “Summarise this”

…it’s a bit like asking a colleague to “just do something with it.”

But when you clarify what you’re trying to achieve, the prompt becomes much more useful.

What Does “Job to Be Done” Mean in Prompting?

It’s about the real outcome you want.

For example:

• Do you want ideas you can act on today — or just a list of possibilities?
• Are you trying to structure your thinking — or get an actual draft?
• Do you need help seeing blind spots — or confirming what you already know?

Let’s Look at an Example

❌ Vague Prompt:

“Write a social media strategy for my business.”

✅ Purposeful Prompt:

“Help me outline three different social media strategies based on my goals: brand awareness, lead generation, and community engagement. I’ll choose one and ask you to expand it.”

Why it works:

• It frames the job — to compare strategic approaches.
• It gives context — the desired outcomes.
• It sets up a two-part conversation — instead of a one-shot reply.

Common AI Prompt Jobs We See

Here are a few jobs your next prompt might be doing — whether you realise it or not:

• Clarify my thoughts
• Help me explain this
• Surface blind spots
• Offer structure
• Generate examples
• Reframe a challenge
• Help me compare options
• Find gaps or risks
• Create a first draft

The more intentional you are about the job, the better the outcome.

Try Starting with These Questions

Before prompting ChatGPT or any other AI, pause and ask:

• “What am I really trying to do here?”
• “What would success look like from this prompt?”
• “Is this about speed, support, insight, or structure?”

Then write the prompt as if you’re asking a thinking partner — not a magic machine.

Let’s Explore AI Together

At Maine Associates, we help teams move beyond templates and tools to build confidence, capability, and curiosity with AI.

Our AI workshops and coaching sessions focus on thinking with AI — not just using it.

Ready to write better prompts by getting clearer on what matters? Let’s start with a conversation.