Before You Buy Another AI Tool, Answer These 12 Questions

Brennan Gerle Jan 26, 2026 5:19:08 PM

A lot of leaders tell me the same thing:

“We know we need to be doing something with AI, but we don’t know where to start.”

So they:

Let a few people play with ChatGPT on the side
Buy a new AI feature in a tool they already use
Or wait, because “it’s not in the budget this quarter”

The real problem usually isn’t the tools.
The problem is not knowing if you and your business are actually ready to use AI in an effective way.

This article gives you 12 simple questions to answer before you buy anything else.

Two Things to Look At First

There are two sides to AI readiness:

You as a leader – how you think about and use AI
Your business – your processes, data, and people

If either side is unprepared, AI projects often stall, or never get past “we should do something with this.”

Let’s start with you.

Part 1: Your Personal AI Readiness (6 Questions)

These questions are about your own habits and understanding as a leader.

1. Do you use AI in your own work?

- - Do you use tools like ChatGPT or Copilot at least a few times a week?
  - Or do you mostly hear about AI from other people?

If you’re not using AI yourself, it’s difficult to lead your team through it.
You don’t need to be an expert, but you do need some hands-on experience.

If your answer is “not really,” make your first “AI project” simply using AI yourself for:

- - Drafting emails or documents
  - Summarizing long reports
  - Getting a first pass on ideas or plans

Do that for a few weeks before you think about larger automations.

2. Do you know the basics of how AI works?

You don’t need technical language. You just need to know:

- - AI predicts text based on patterns in data
  - It can sound confident and still be wrong
  - It needs clear instructions and human review for important decisions

If it still feels like “magic” or a black box, you’re more likely to either over‑trust it or ignore it altogether.

3. Can you “talk” to AI in a way that gets good results?

This is about prompting.

When you don’t like the first answer from an AI tool, do you know how to:

- - Add more context? (“I’m a COO at a 50‑person construction company…”)
  - Give an example? (“Here’s the style I want. Please match it.”)
  - Ask for a rewrite? (“Shorter, clearer, less formal.”)

Leaders who do this get much more value out of the same tools.

4. Do you know what’s safe to put into AI tools?

Many organizations are either:

- - Too relaxed (copying sensitive info into public tools), or
  - Too strict (no one is allowed to use anything)

It helps to be clear on:

- - What’s never allowed (for example, specific client names, financial details, regulated data)
  - What’s okay if it’s anonymized
  - What’s low‑risk and great for experimentation (generic text, public info, ideas)

If this isn’t clear for you, it won’t be clear for your team.

5. Can you explain to your team why you’re using AI?

People pay attention to how leaders frame change.

Can you clearly explain:

- - Why you want to use AI (time savings, quality, speed, consistency)
  - How it should help people, not quietly replace them
  - What’s in and out of bounds

When that story is clear and simple, adoption improves and resistance drops.

6. Are you ready to sponsor a small pilot, not just sign off on a tool?

AI initiatives tend to struggle when leaders:

- - Approve a budget
  - Hand it to IT or a “tech person”
  - Then step away

You don’t have to manage the details.
But you do need to:

- - Help choose a first use case
  - Remove blockers
  - Signal that this work matters

Part 2: Your Business AI Readiness (6 Questions)

Now let’s look at your organization.

7. Are your key processes clear enough to work with?

Pick a process: project delivery, job costing, customer onboarding, service requests.

Ask:

- - Could someone outside the team understand the main steps?
  - Do you know where the delays and repetitive work are?

If no one can explain the process, there’s not much for AI to improve.
You risk automating confusion.

8. Is your important data in a few reliable places?

Think about:

- - Customers
  - Projects or jobs
  - Inventory or assets
  - Tickets or issues

Is that information:

- - Mostly in shared systems (CRM, project tool, ERP), or
  - Scattered across inboxes, spreadsheets, and people’s heads?

AI and automation rely on data.
If your data is scattered or untrusted, that’s a signal to shore up the basics before bigger AI projects.

9. Do your current tools play well with AI and automation?

Questions to consider:

- - Do we already use tools that have AI built in or can connect to it easily?
  - Or would everything require custom builds and workarounds?

You don’t need a perfect stack.
But it’s useful to know whether you can:

- - Start inside tools you already pay for, or
  - Whether some upgrades are a stepping stone to where you want to go

10. How does your team really feel about AI?

Listen to what people actually say:

- - “I’ve been using it, it helps a lot with X” → curiosity and early adopters
  - “This is going to take my job” → fear
  - “This is just another buzzword” → skepticism

You don’t need everyone excited.
You do need:

- - A few open‑minded people to pilot with
  - Clear communication about what AI is and isn’t for in your context

11. Do you have any written guidelines for AI use?

This doesn’t need to start as a long policy. A one‑page set of ground rules is often enough:

- - Which tools are approved vs. not approved
  - What data is never allowed
  - When human review is required (for example, anything client‑facing, legal, or financial)

Without this, people are guessing.
Some will avoid AI. Others will experiment in ways you may not be comfortable with.

12. Do you know where a small AI experiment could help first?

Look for work that is:

- - Boring and repetitive
  - Rule‑based
  - Low risk if something small goes wrong

Examples:

- - Drafting project updates instead of starting from a blank page
  - Summarizing meeting notes and pulling out next steps
  - Sorting and tagging incoming emails or tickets
  - Turning messy notes into a first draft SOP

If you can name one or two of these, you’re ready for a focused pilot.

How to Use Your Answers

A simple way to move from reflection to action:

1. Capture your answers.
  Jot down a few bullets for each question. You don’t need a long document.
2. Pick 1–2 areas about you as a leader to improve.
  For example:
  - “I’m going to use AI three times a week for the next month.”
  - “I’m going to get clear on what’s safe vs. not safe to put into tools like ChatGPT.”
3. Pick 1–2 areas about the business to improve.
  For example:
  - “We’re going to document one core process.”
  - “We’re going to create a simple one‑page AI guideline for the team.”
4. Choose one pilot use case.
  Something:
  - Contained
  - Measurable
  - Useful

Run that pilot for 30–90 days.
Measure time saved, errors reduced, or speed improved.
Then decide whether to expand, adjust, or pause.

Make This Easier: Take the POLR AI Readiness Assessment

If you’d like help walking through this in a more structured way, I built a short assessment you can use.

You’ll answer questions like:

- How often you actually use AI in your daily work
- How confident you feel using it and asking it good questions
- How your business handles processes, data, and risk today

You can use it:

- As an individual leader – to see where you’re ready and where you want to build confidence
- For your business – to see where AI is most likely to help first

Take the assessment here:
https://www.polrai.com/assessment

After you complete it, you’ll have a clearer picture of:

- Where you’re already in good shape
- Where you may want to strengthen foundations
- And which 1–2 AI moves are worth focusing on in the next 90 days

If you’d like to turn that into a concrete plan, you can request an AI Readiness & Opportunity Audit from that page, and we can talk through what makes sense for your situation.