Most founders think AI is this thing that can do it all, be it all. They tinker with it, like what they see, and then forget about it.
But when you build your business with AI in a deliberate and strategic way that aligns with the needs of your model, your capacity expands far beyond what is possible alone.
This is how million-dollar businesses are being built today.
Not with bigger teams.
Not with more software.
Not with longer hours.
But with systems.
How Canva became a global creative powerhouse with AI
When Canva started, it was just an idea Melanie Perkins had.
A bold idea. Make design simple. So simple that anyone could create something beautiful. Students, solopreneurs, marketers. Anyone.
At first, growth was quiet. Steady but unremarkable.
Then Canva began experimenting with AI.
Not just small features. They built Magic Studio. Magic Write, Magic Design, Magic Switch, Canva Code.
Tasks that used to take hours suddenly took minutes.
People noticed.
Monthly users jumped to 150 million. In just one year, 65 million new users joined.
Revenue exploded to 2.55 billion dollars in 2024, a 44 percent jump from the previous year. Valuation climbed to 49 billion dollars.
By 2025, 200 million people in 190 countries were using Canva. Annual revenue reached nearly 3 billion dollars.
But the numbers are only part of the story.
The real transformation was in what AI did for people.
Creativity became effortless. Ideas that once got stuck in drafts now flowed into polished designs. Resizing, writing copy, creating multiple versions all happened in minutes.
AI became more than a tool. It became a teammate.
Canva focused on what mattered most.
- Build the capabilities people need.
- Automate repeated tasks.
- Ensure outputs are consistent.
- Allow learning so AI gets smarter over time.
The result is growth that feels unstoppable, efficiency that saves countless hours, and a system that scales creativity for millions around the world.
And that is how a small idea became a global creative powerhouse.
How to decide if you should build with AI: The GROWTH Model
The GROWTH model is a simple framework to help you decide if a task is worth automating with AI and how to prioritize it.
It ensures your AI work is smart, goal-focused, and efficient, while also recognizing what AI cannot do.
Each letter in GROWTH stands for an important principle:
G – Goal-Oriented
What it means: Only use AI for tasks that have a clear business or personal goal.
Why it matters: Without a goal, using AI becomes busywork or just a novelty.
How to apply it: Ask yourself if this AI tool helps you reach your monthly, quarterly, or yearly goals. Does it improve an important workflow or solve a repeated problem?
Example: Automating proposal writing if sending proposals is critical for revenue growth.
R – Repeatable
What it means: Focus on tasks that happen often. AI is most helpful with repetitive, frequent work.
Why it matters: One-time tasks do not justify the time to train or set up AI.
How to apply it: Ask yourself if you will do this task again and again, daily, weekly, or monthly.
Example: Creating weekly social media captions, replying to standard client emails, or generating reports.
O – Outcome / ROI
What it means: The task should give measurable results like saving time, reducing costs, or improving quality.
Why it matters: AI takes time and effort to set up, so the results must be worth it.
How to apply it: Ask if the effort you put into AI will pay off in saved hours, money, or better results.
Example: An AI FAQ system that saves your team 10 hours a week.
W – Work / Task
What it means: Clearly define what the AI will do and make it structured.
Why it matters: AI works best with predictable, repeatable tasks. It struggles with vague or highly creative tasks.
How to apply it: Ask if you can clearly define the process for AI to follow.
Example: AI drafts proposal templates, but a human makes the final edits.
T – Talent
What it means: Human review is needed to ensure quality and accuracy.
Why it matters: AI can make mistakes if it is not checked.
How to apply it: Decide who will review or refine AI outputs and how it fits into team workflows.
Example: A team member reviews AI-generated reports before sending them to clients.
H – Honest / Realistic
What it means: Be realistic about what AI can do. AI improves with time and data but has limits.
Why it matters: Overestimating AI can waste time and cause poor results.
How to apply it: Ask whether you are realistic about AI capabilities and ready for the learning and initial inefficiencies.
Example: AI can draft content quickly but still needs editing to match brand voice and accuracy.
Automate with Custom AI Agents
AI is excellent at getting things started, like generating drafts, collecting ideas, and organizing information, but it cannot replace human judgment, intuition, and personal touch.
Custom AI agents let you automate repetitive tasks, maintain consistency, and save time and money while you focus on higher-level decisions and creativity.
They turn AI into a reliable team member explicitly trained for your workflows, voice, and goals.
Once you understand why to build them, the DRIVE model shows how to do it effectively.
DRIVE Model
The DRIVE model is your step-by-step framework for building AI agents, custom GPTs, or any AI-driven system that actually works for you.
It’s more than just throwing prompts at AI. It’s about designing intelligent workflows that save time, increase output, and maintain quality.
D – Define: Start by clarifying exactly what you want to build and what the ideal outcome looks like.
Without this, your AI agent may deliver results that are good enough but not aligned with your goals.
Define your purpose clearly. What problem should the agent solve and what result will mean success?
R – Research: Gather the best knowledge base for your agent.
Whether it’s internal data, industry benchmarks, or expert examples like Y Combinator’s pitch deck templates for proposals, ensure your AI has high-quality references to learn from.
This ensures its output is accurate, relevant, and actionable.
I – Innovate: Craft the prompts, instructions, or workflows that your AI will use.
This is where creativity meets technical setup. Even if prompt engineering seems tricky, start with simple prompts and iterate.
Innovation here is about experimentation with your tools.
V – Validate: Test your agent across diverse scenarios to confirm it delivers at least 80 percent of the desired results.
Avoid giving garbage inputs because AI learns from what it’s fed.
Validation ensures your system is reliable and efficient without wasting your time.
E – Execute: Deploy your AI agent and refine it over time.
Continuous feedback, minor adjustments, and team oversight keep it aligned with your goals.
Even if it never reaches perfection, it can handle repetitive tasks, saving hours and thousands of dollars in resources while you focus on higher-impact work.
When to use DRIVE:
- Building a custom GPT, AI assistant, or tool for repetitive tasks
- Designing AI workflows for content creation, proposals, or social media
- Scaling business operations without hiring extra staff
- Optimizing time-intensive processes where quality and consistency matter
DRIVE turns AI from a novelty into a strategic team member. You don’t just speed things up.
You create systems that reliably deliver results, freeing you to focus on decisions, strategy, and growth.
Where AI ends and where humans begin: The 80% Model
The 80% Model helps you understand the natural boundary between what AI is good at and what you are good at.
AI is excellent at getting things started. It can collect information, outline ideas, generate first drafts, and explore options faster than any human.
This early stage of work is usually the slowest part of any project, and AI can handle it with ease.
Think of this as the first 80 percent. It gets the work moving, removes the blank page, and builds the base layer.
The remaining 20 percent is where your human judgment matters.
This is the stage where quality is defined. You adjust the tone, refine the message, correct inaccuracies, add personality, and make sure the work reflects your standards.
This is also the part that requires intuition, taste, and emotional intelligence, which AI cannot replicate.
The model is simple:
AI speeds up the creation.
You ensure the outcome is precise, relatable, and aligned with your brand.
Together, they produce work that is fast and high quality without expecting either side to do something it is not built for.
Reflection Prompts
Where am I currently spending the most time that does not directly generate revenue?
Which tasks do I repeat so often that automation could save hours or days per month?
What workflow frustrates my team or clients the most?
Which single process, if automated, would free me to focus on growth and strategy?
What is my highest-value use of AI next month?
Are there areas where AI can support learning and improvement over time?
Your Action Steps
Pick one business goal you want to move in the next 30–90 days.
List your repetitive tasks that relate to this goal.
Choose one task to automate first using AI.
Decide if it needs a custom AI or an off-the-shelf tool
Let AI do the first 80% and you or your team refine the last 20%.
Test for one week: see if it saves time or improves results.
Iterate or expand to the next task once it works.
Let’s build it together
This December, I’m running the From Chaos to Million Challenge.
If you want to set a clear vision, create priorities that cut through confusion, draft your first product, stack up offers for maximum impact, and build a marketing plan that generates predictable income, come join me for this three-day challenge.
It runs from Thursday, 11th December to Saturday, 13th December 2025 (8 am PST / 8 pm Dubai / 4 pm London).
You’ll get live sessions, actionable workbooks, and frameworks to help you take real steps toward your first six-figure business and beyond.
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Love. Ajit
