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So you want to become a Business AI Architect?
Interesting. First question.
Do you actually like solving business problems?
Because if you’re only interested in AI tools, this might be a little disappointing. 😂
The tools will change. The models will change. The companies making them will change.
But businesses will continue to have customers, employees, suppliers, orders, payments, decisions, and problems.
Someone has to understand how those things work together. And increasingly, someone has to figure out where AI belongs.
That’s the opportunity I find interesting.
What does a Business AI Architect actually do?
Think of someone who can sit down with a business owner and understand what they’re trying to accomplish.
Not just what software they want. What problem they’re trying to solve.
Then they can design a solution that brings together business processes, data, applications, automation, AI, and people. And make sure it works.
That’s the job. The title is optional.
In practice that means two things. Business AI Architecture: designing how the business, its systems, and its AI should work together. AI-DLC: running an AI-driven development lifecycle that takes the design from canvas to customer, with AI doing more of the building and people approving what ships.
You help enable human-in-the-lead.
Where people can focus on decision-making, direction-setting, and value creation.
Five things I’d learn first
Five things I’d learn first.
01Learn how businesses work
Sales. Finance. Operations. Procurement. Customer service.
You don’t need to know everything. But you should understand how work moves through a business, how decisions are made, and where things break down.
02Learn to question the problem
A client says they need a chatbot. Okay. Why?
What are customers asking? Where is the information? What happens after the chatbot answers?
Sometimes the solution is a chatbot. Sometimes it’s fixing the website.
03Learn enough engineering to design responsibly
APIs. Databases. Integration. Security. Workflows. Software architecture.
You don’t have to write every line of code yourself. But you should understand what you’re asking people, or AI, to build.
In an AI-DLC, AI assistants and agents write more of the code. That makes your architecture more important, not less.
04Learn when not to use AI
This one deserves its own chapter.
If a simple rule can solve the problem reliably, why introduce a probabilistic model? Use the simplest technology that meets the requirement.
05Learn how to deliver
A demo is not a business solution.
Someone needs to deploy it, secure it, support it, maintain it, and take responsibility when something goes wrong. This is where professional architecture and delivery matter.
That’s the back half of the AI-DLC: test, approve, ship, measure. From canvas to customer.
Your first practical exercise
Find a small business.
It could be a restaurant, a distributor, a repair shop, or a business you already understand. Ask three questions:
- What takes too much time?
- What keeps going wrong?
- What information do you wish you had before making decisions?
Pick one answer. Map the current process. Design a simpler version. Then ask whether AI would actually improve it.
Congratulations. You’re already beginning to think like a Business AI Architect. No expensive certification required to start thinking. 😂
Where to go next