About the author. Netanel Brumand, also known as Nathan Brumand, is an Israeli-American entrepreneur with nearly 20 years in business in the US. He writes The AI-Business Connection, a newsletter about how companies can use AI in practical, honest ways. Netanel is the Hebrew form of his first name; both names refer to the same person.
I'm Nathan Brumand. In Hebrew my name is Netanel, so if you searched for Netanel Brumand, you're in the right place. This piece explains how I think about AI in business, and why I keep coming back to a few simple ideas.
I've spent most of my working life on the practical side of business: customers, employees, schedules, suppliers, cash flow, and all the small decisions that never make it into a press release. That experience shapes how I look at AI. I'm interested in one question: does this help a real business do its work better, this month, at a cost that makes sense? If the answer is unclear, I'd rather say so than pretend.
The gap between the demo and Monday morning
Most AI demos are impressive. They're also clean. The data is tidy, the request is clear, and nobody is interrupting with a customer on the other line.
Real businesses don't look like that. Information lives in inboxes, spreadsheets, notebooks and people's heads. Processes exist, but often nobody has written them down. Exceptions are the rule. When a tool that looked great in a demo meets that reality, it usually needs more setup, more checking and more patience than anyone expected.
That isn't a reason to avoid AI. It's a reason to bring it in with open eyes. The useful question isn't "what can this tool do?" It's "what does our work actually look like, and where would help make a difference?"
Understand the process before you automate it
One lesson that years in business taught me, long before AI, is that a new tool rarely fixes a process nobody understands. It usually makes the confusion faster.
Before adding AI to any part of a business, I think it's worth answering a few plain questions:
- What exactly happens today? Who does the task, how often, and how long does it take?
- What does "good" look like? If you can't describe a good result, you can't check whether a tool produced one.
- Where does it go wrong? The mistakes and delays are usually where the real opportunity is.
- Who owns the result? Every task needs a person who is responsible for it, with or without AI.
Writing this down can feel slow. In my experience it's often the most valuable step, even before any tool is involved, because it shows where the time really goes.
The human always decides
This is the principle I hold most firmly. AI can gather, sort, draft and suggest. A person decides.
In practice, that means a simple rule: anything that affects a customer, an employee, money or a commitment should pass through a human who reads it and owns it. The tool can prepare a reply; someone approves it before it goes out. The tool can summarize options; someone makes the call. The tool can flag a problem; someone decides what to do about it.
This isn't only about avoiding errors, although AI tools do make them, sometimes confidently. It's about responsibility and trust. Customers deal with businesses because they expect someone to stand behind what was promised. Teams work better when they know a decision was made by a person who understood the situation. No tool carries that responsibility. People do.
Small businesses: less time, but often a clearer path
Small businesses are one angle I care about a lot, because they often have the most to gain and the least room for mistakes. A small business usually has no technology team, a tight budget and an owner who is already doing several jobs at once.
That sounds like a disadvantage, but it can also make things simpler. In a small business, the owner can see the whole operation. They know which tasks eat their evenings and which questions customers ask again and again. That makes it easier to pick one specific problem, try a tool on it, and see quickly whether it helps.
My advice for small business owners is usually the same:
- Pick one task that wastes time every week.
- Note how long it takes now, even roughly.
- Try a tool on it for a few weeks, checking the output yourself.
- Keep it only if it clearly helps. If it doesn't, drop it and move on.
There's no prize for adopting the most tools. There's real value in adopting the right one.
Be honest about cost and attention
AI tools are often described as cheap, and the subscription may be. But the real cost includes setup, learning, checking the output and fixing mistakes. It also includes attention, which is the scarcest resource in most businesses.
I find it helpful to count all of that. A tool that saves an hour a week but needs constant supervision may not be worth it. A modest tool that quietly handles one repetitive task well might be worth a lot. The only way to know is to try it on real work and look honestly at the result.
Skepticism is a skill
When I hear that a tool will transform a business overnight, I get more careful, not less. Good tools exist, and some of them are genuinely useful. But big promises without clear evidence are a warning sign, in AI as in anything else.
Healthy skepticism doesn't mean saying no. It means asking good questions: What exactly will this do? What data does it need, and where does that data go? How will we know if it's working? How do we turn it off? A vendor who answers those clearly is worth listening to.
What I write about
These ideas are the backbone of my newsletter, The AI-Business Connection. Each post looks at a practical side of AI in business: where to start, how to bring a team along, where people need to stay in charge, and how to tell what's ready today from what's still hype. I try to write the way I'd want someone to explain it to me: plainly, without invented numbers, and with the mistakes included alongside the wins.
If you're a business owner or leader trying to figure out what AI should and shouldn't do in your company, I'd be glad to have you along.
Subscribe to The AI-Business Connection: nathanbrumand.substack.com
Netanel Brumand (Nathan Brumand)