Insights, guides, and updates
A staff member built a brilliant practice management dashboard with AI. One problem — the data that would make it work lives in three systems that don't talk to each other. That gap between vision and architecture is the same gap every CAS practice is hitting. The fix isn't more training. It's building artifacts that prove your team can do the work.
Most of the tools CAS practices pay for aren't doing anything AI can't do — they're formatting engines that take data you already have and present it the way someone expects it. Two real engagements proved the point: a QBO year-end that normally required a ledger in Xero, and a working trial balance request that normally required Caseware. Both replaced in an afternoon with purpose-built agents.
During a webinar on AI-powered client coaching, a colleague shared a 25-question diagnostic survey in Excel. It was ugly, had scoring errors, and looked like what it was — a spreadsheet pretending to be a tool. Thirty seconds of prompting later, it was a polished interactive HTML page that captured, scored, and analysed responses. The quality ceiling on what you hand your clients just disappeared.
I built an AI skill for something completely unrelated to accounting — booking flights — and learned more about context engineering in two hours than months of client work had taught me. The first draft captured my obvious preferences. The corrections surfaced knowledge I didn't know I had. That's the encoding gap, and it's the reason most firms' AI stays mediocre.
PwC launched a subscription AI platform that lets clients access tax, financial analysis, and due diligence intelligence — without the hourly bill. When the largest firm in the profession stops selling hours, every firm below them inherits the pricing question. The answer isn't panic. It's building.
Sequoia named accounting as a $50-80B disruption target. Learn the four strategic moves to absorb the disruption instead of being displaced by it.
