AI for the Skilled Trades

For tradespeople, most of AI's value is in language work, not the physical job. General chatbots such as ChatGPT, Claude and Gemini, and the AI features added to field-service platforms like ServiceTitan, Jobber and Housecall Pro, can turn rough notes, voice memos and photos into estimates, job summaries, invoice descriptions and follow-up messages. For a one- or two-person shop where the owner does the books at night, that time saving is real. Quoting works best when you give the AI your own numbers. A model doesn't know your local material prices, labor rate, markup or how long a job takes you, so if you leave them out it fills the gaps with plausible guesses. A good approach is a saved template: your rates, standard line items and exclusions, plus the job notes. You still check every figure. Code lookups need the most care. Building codes are adopted and amended locally, and editions change. The National Electrical Code, for example, is revised every three years, and a jurisdiction may enforce an older edition with local amendments. A model can misquote section numbers, mix up editions or state a rule with confidence when it's wrong. Use AI to learn what a rule is about and where to look, then check the adopted code and, when in doubt, ask the inspector. The license holder is responsible for the work, not the software. A common misconception is that AI will soon replace electricians and plumbers. Hands-on trade work happens in unstructured places like crawlspaces, attics and old houses with undocumented wiring. The job depends on touch, sound, smell and judgment, and every site is different. Robots still struggle with this, a pattern often linked to Moravec's paradox: skills that are easy for people, like moving around in a messy space, are hard for machines. So AI mostly changes the office side of the trades, not the tools on the belt.