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Practical reading on AI for business — without the hype.
What AI actually means for small businesses
Most AI tools business owners encounter are one of three things: language models, workflow automation, or data classification. Here is what each category is good for and what it cannot do.
How to decide if an AI tool is worth trying
Before subscribing to another tool, run through these five questions: What specific task does this automate? Who reviews the output? What happens if it is wrong? What does it cost per hour of work saved? What data does it access?
Why AI-powered is not a feature — it is a starting point
The term AI-powered in a product description tells you very little. What matters is what the AI does, what it decides autonomously, what data it accesses, and whether a human reviews its output before it affects your business.
The five most common reasons AI implementations fail
Most AI projects fail for non-AI reasons: unclear ownership, no testing with real data, skipped training, no documentation, and solving the wrong problem. Here is how to avoid each one.
Fix the process before you automate it
Automating a broken process gives you faster broken results. The most valuable thing we do in a consultation is identify where the real problem is — and it is often upstream of where the client thinks it is.
When you actually need a CRM and when you do not
CRM is often the first thing people reach for and the last thing they actually needed. Here are the signals that indicate a CRM would help — and the signs you should solve a simpler problem first.
Ready to apply this to your business?
General reading only goes so far. The assessment is how we learn enough to give you specific answers.