EP 35 - Don't Trust AI with Your Numbers!
"It really highlights how quickly AI and trusting it fully can really scale chaos so quick." Welcome back to the Business and Bytes Podcast! In this episode, host John Hansman and co-host Lexi talk about numbers, and why you should be careful how much you trust AI with them. Lexi shares a real story: an AI tool ran a large set of company numbers, and they came back looking right overall, but they were slightly off throughout and one year was almost exactly doubled. Nobody would have caught it without checking against the real numbers. John and Lexi walk through how to use AI with numbers without getting burned. Break big jobs into small chunks and check each one before moving on. Test new automations somewhere they can't touch your live data. Give the AI the same written process your team already follows. And keep checking its work for months, not days. They also cover picking the right AI tool for the job, setting guardrails for employees, and the growing talk about taxing AI, plus why every AI project needs to show it's actually saving or making money. If you're using AI for anything where the numbers have to be exactly right, this one's for you. Trust, but verify. Support the show by subscribing to our Facebook Account: https://www.facebook.com/businessandbytes What's covered: A real story: AI numbers that looked right, until one year came back doubled Why "close enough" isn't good enough for financial or health data Checking AI's work in small chunks instead of all at once Test first: keep new automations away from your live data Turning your written processes into instructions for AI Testing AI is ongoing, not a one-time thing Different AI tools are good at different jobs Guardrails for how employees use AI Taxing AI, usage costs and making sure AI actually pays for itself Final thoughts: trust, but verify






