Where could AI actually fit in your business?
You don’t need to add AI everywhere.
You need to understand where it could improve the work—and where it probably shouldn’t be used yet.
iWasGonna™ helps small business owners examine their goals, workflows, people, information and existing tools before recommending a next step. That may mean an existing product, better use of current software, training or no AI change.
The objective isn’t to produce an impressive AI score.
It’s to help you make a better business decision.
Not sure whether readiness is the right starting point?
AI readiness is more than having access to AI.
A business can have ChatGPT, Microsoft Copilot, Claude, Gemini, automation tools, and dozens of other technologies available—and still not be ready to use them effectively in a particular workflow.
Readiness depends on the work surrounding the technology.
Questions like:
Is the process itself understood?
Is the work performed consistently?
Do employees know who owns the result?
Is the information AI would need available and trustworthy?
Are important decisions supposed to remain human?
Does someone know how the output should be reviewed?
Are current systems already solving part of the problem?
Is the proposed use worth changing the workflow for?
How would anyone know if the change actually helped?
Those questions come before the tool.
Start with the work you want to improve.
Start with the business activity you want to improve. You do not need a technical brief, a chosen tool or an AI Blueprint™ purchase to begin a conversation.
For example:
Instead of asking:
“Where can we use AI?”
we start with:
“What work are we trying to improve?”
What we look at
The business objective
What are you trying to improve?
Maybe it’s consistency, speed, quality, employee capacity, response time, documentation, access to information, customer experience, or reduced repetitive work.
The current workflow
How does the work happen today?
We look at what triggers the task, who performs it, which steps are involved, where information comes from, which systems are used, where decisions happen, where work gets delayed, and where corrections or rework occur.
A broken process doesn’t automatically become a good process because AI is added to it.
The people involved
Readiness depends on employee responsibilities, experience, training needs, review responsibilities, approval authority, escalation points, and who will own the process after implementation.
The information AI would need
We may examine business documents, procedures, examples, source materials, reference information, existing instructions, templates, customer or operational data, and which information is approved for use.
The important question is whether the right information is available, current, appropriate, and usable.
Existing systems and tools
Evaluate tools you already own and ready-made products before considering a custom build. Recommendations follow the business need rather than a predetermined platform.
A new tool should solve a problem—not create another software subscription.
Review and accountability
Readiness includes understanding who reviews AI-assisted work, which outputs require approval, which decisions must remain human, what happens when the answer is uncertain, when something should be escalated, and who accepts the final result.
What AI Readiness may identify
A readiness review helps identify suitable options. Scope, evidence, deliverables and fees for paid work are agreed first; implementation is a separate decision.
The appropriate next step might be:
A strong AI use case
Available evidence suggests a workflow is worth exploring. Any trial or implementation requires agreed scope, capability and review criteria.
Workflow improvement first
The process needs clarification or simplification before AI is introduced.
Better operating instructions
Employees or AI systems need clearer guidance.
Business AI training
The tools may already exist, but employees need practical training around real tasks.
AI tool evaluation
Compare existing products against the task, budget, current systems and adoption effort. The answer may be to keep a tool you already own.
AI Usage & Workflow Assessment
AI is already involved and the real question is whether the existing setup is working.
Additional evidence
There isn’t enough information yet to support a confident recommendation.
No AI change yet
AI may not currently improve the process enough to justify implementation.
That’s a useful answer too.
Not every process is a good AI candidate.
Warning signs can include:
The task itself is poorly defined
Nobody agrees what a good result looks like
Required information is unavailable
The process changes constantly
Important ownership is unclear
Errors would create unacceptable consequences
Review requirements have not been established
The proposed tool cannot reliably access what it needs
The existing process already works well
A simpler rule, template, or conventional automation would solve the problem better.
AI readiness isn’t about finding an excuse to use AI.
It’s about finding the right place for it.
How the readiness process fits our consulting method
Discover
Define the business objective and the work being considered.
Assess & Audit
Examine the current workflow and agreed evidence.
Recommend
Identify an appropriate next step.
Implement & Train
Where scope and capability are confirmed, separately agreed help may include configuration, instructions, workflows, training or bounded integrations. Specialist options are considered case by case.
Validate & Improve
Where validation is included, review a change against agreed expectations. Follow-up reviews and support are separately scoped.
Readiness should lead to a decision.
A readiness exercise shouldn’t leave you with:
“Your company scored 72 out of 100. Congratulations.”
Then what?
A useful readiness outcome should help answer:
Which business process deserves attention first?
What conditions need to be fixed before AI is introduced?
Which existing tools should remain?
What does the team need to learn?
Which information needs to be organized?
What should be tested?
What shouldn’t we change?
What evidence do we still need?
What is the next practical action?
The point is not the score.
The point is the decision.
You may already be past readiness.
If your company is already using AI inside a real workflow and your question is:
“Why are our results inconsistent?”
or
“Is this actually improving the work?”
then an AI Usage & Workflow Assessment may be the better starting point.
If you’re comparing platforms:
If your primary problem is employee adoption:
Where could AI make sense in your business?
Start with one piece of work.
Tell us what you want to improve and which tools you already use. We’ll discuss a practical next step. A paid assessment is one option, not an automatic requirement.
Or: