ROAI(Return on Applied AI)
The ROAI newsletter delivers practical AI tips, a few great links, and an honest look at what's actually working in business right now — every Thursday, from some of the humans at AI Front Desk.
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From some of the humans behind AI Front Desk.
Handing your team AI tools isn't the same as getting them to use it well. Brian Holmes on why AI results are a change management problem, the Monday spreadsheet that gave us back hours, and how to start with your own team.
Building with AI went fine. Understanding what we'd built well enough to trust it was the hard part. Jake Hodges on keeping a human in the loop, where a person has to look, and what the research says about checking AI's work.
We measured it across every location in one franchise group. When the booking agent said up front that it was AI, escalations ran 28% lower. Beth Boley on why, plus a two-minute test of your own enquiry form.
Most people don't know they're on a path from chatting with AI to building with it. Jake Hodges maps the four steps, why skipping ahead costs you, and one thing to try at each step.
A weekly research task that used to cost a day now takes fifteen minutes. Brian Holmes on Scheduled Tasks, which tools run them, and four boring tasks worth setting up this week.
AI agents are mostly people, not tokens. What McKinsey found when it costed out the whole job, why scale makes the math work, and the number you should ask for before the next vendor pitch.
AI adoption programs do not fail because people are not excited. They fail when the people who are ready to build are not given room in the workday to do it. Plus a practical guide for giving someone that room, a new Applied AI session for marketers, and the stories behind the hours AI saves.
The first line of the pitch was a lie. Brian Holmes on why the best AI projects start with a real problem, what to ask before the next demo, and the signals that separate useful tools from agent washing.
I had AI put together two great reports and thought I'd figured it out — then the third came back garbage. The Harvard study that explains why 19% of AI users perform worse than people who never opened the tool. Plus a free tool to map which parts of your job are most exposed, the reason the same prompt gives different answers, and what Gallup found when it asked 22,000 workers about their daily AI habits.
A customer loves our AI receptionist so much she reads its conversations to her husband at dinner. Murphy Tiggelaar on customer obsession, the five questions that surface what customers actually need, and a prompt that makes AI argue against your own business.
There's a new word for something you've probably already felt. AI output that looks polished but means nothing — no real thinking, no decision, just a shell that leaves you to do the actual work. Brian Holmes on how to spot it, stop producing it, and what to do when it lands on your desk.
The AI never stops encouraging you. Every idea you float, it tells you is brilliant. Jake Hodges on why that's the most dangerous thing it can say — and what happened when blank pages hit production. Plus two Applied AI sessions and four stories on brains, bots, and Lloyd's of London.
Almost every AI tool you use is 'closed' — you rent it. Open source is the hedge. Plus two Applied AI sessions on responding to reviews and starting with open source models, what Congress is doing about AI on Main Street, and a paid AI job that requires no degree.
Pick one task, run it ten times without touching it, then move to the next. Plus two Applied AI sessions on email/calendar and responding to reviews, and what 81,000 Anthropic users said about where AI actually pays off.
AI hype is cooling, and that's not a bad thing. Plus two Applied AI sessions on email/calendar and responding to reviews, why your team is probably pasting customer data into AI, and what PwC found about who's actually winning with AI.
I checked. The latest AI model is genuinely impressive. It also still won't sound like your front desk unless you tell it who you are. One example, two responses, and a lesson that matters more than any benchmark.
Stop re-explaining yourself to AI. Set your context once and every answer comes back sharper, faster, and in your voice. Plus: the AI 101 monthly session and a tool to show what slow follow-up is costing you.