The Easiest Way To Start Using AI In Your Business

TL;DR: If you’re stuck trying to “get started with AI”, here’s the clear path: choose one repeatable task, tighten the workflow behind it, apply a low-code tool that removes the slowest step and measure the gain within a week. This approach works to reduce risk and gives you a practical win that builds confidence and momentum across your team.

Start by fixing the work, not choosing a tool

Most AI attempts fail because the work underneath is unclear.
People rush to tools, prompt them blindly and then blame the model when the output looks odd. Here is the truth: if the task is vague, AI will behave the same way. Strip the task back. Spell out the steps. Identify where time is wasted.
Only then introduce AI. This will remove 80 percent of early 'failure.'

Choose a task that meets three conditions:

• Repeated every day or every week
  
• Boring enough that no one will complain if it changes
  
• Safe enough that errors won’t cause harm
  

If you meet these three criteria, you eliminate most of the risk while guaranteeing usability. Good examples include rewriting text, summarising long content, extracting actions from notes, producing first drafts or cleaning inconsistent data.
These tasks succeed because they already follow patterns your team understands.

Document the workflow in plain language

Before AI touches anything, write down the workflow in five lines:

1. The trigger
   
2. The inputs
   
3. The required output
   
4. The decision points
   
5. The bottleneck

This takes ten minutes and will immediately show why previous AI attempts failed.
AI doesn’t infer missing context. It needs structure. This gives it structure. Now, introduce AI at the bottleneck, not everywhere at once, people often try to automate the entire workflow at the start. That is a guaranteed way to stall.

Find the single slowest, most repetitive step and place AI there.
Nothing else.

• If the bottleneck is rewriting, rewrite.
  
• If it is summarising, summarise.
  
• If it is cleaning text, clean text.
  
• If it is extracting tasks, extract tasks.

By narrowing the scope, you make the output reliable and the value obvious.

Use low-code tools to remove manual steps quickly

You don’t need developers to build value. Low-code tools let non-technical teams place AI inside workflows with minimal effort. A simple sequence works:

1. Select the bottleneck
   
2. Build a prompt that matches the workflow
   
3. Run it on real work
   
4. Refine the inputs
   
5. Save the working pattern
   
6. Share it with the team

This replaces hours of manual work with a repeatable action the team can trust.

Measure the change immediately

A pilot is only useful if you measure the right thing.
Track: Time saved, Errors avoided, Clarity gained, Rework reduced

Do this for one week.
If the result improves, keep it.
If not, adjust the workflow, not the tool.

Scale by moving sideways, not upwards. When the first use case stabilises, expand to the next natural step in the same workflow.

Meeting notes → project summaries
Drafts → reports
Data clean-up → categorisation
Customer queries → triage notes

By moving sideways, the team learns one pattern at a time and confidence compounds. This is how capability compounds.  Build capability before committing to bigger automation. Anyone can buy an AI tool. What matters is whether your team knows how to use it.

Capability is built through:

• Clear workflows
  
• Small wins
  
• Safe pilots
  
• Shared prompt libraries
  
• Routine refinement

Once these habits take hold, larger automation becomes obvious and low-risk. And importantly, you avoid buying tools you’re not ready to use.

FAQ

Q: What’s the first step if we feel overwhelmed?
A: Choose one task. Not a workflow, not a department—one task.

Q: How do we know if AI is helping?
A: Track the time saved and the rework avoided. If both improve, you’re on the right path.

Q: Why not start with a large project?
A: Early mistakes are cheaper when the stakes are low. You learn faster and avoid damaging real work.

Q: What skills do we need to start?
A: Clear instructions, the ability to review outputs and a stable workflow. No coding required.

Q: When should we escalate to deeper automation?
A: When you have three or more stable use cases and the team can maintain them independently.

If your business wants clarity on the right tasks, the right workflows and the right low-code AI builds, the AI Fundamentals Masterclass, AI Bootcamp and AI Strategy Roadmap give you the structure and support to introduce AI safely and with confidence.