Hi Reader,
After a client strategy session, I usually have a lot of information to sort through. A 60- or 90-minute conversation can include decisions we've made, challenges we've uncovered, recommendations I've given, next steps for the client, and things I've promised to send afterward.
Before I started using AI for this, I would spend hours going back through the conversation, reviewing my handwritten notes and emails we'd exchanged, creating my own summary, and making sure I hadn't missed anything.
AI has made that part of my work much easier. I have a specific prompt and framework I use to analyze the transcript and pull out the information I need. Depending on the client and project, I can also give it my notes, emails we've exchanged, and other information that gives it more context.
I even ask it to show me where it found certain things in the conversation. Instead of starting from scratch, I can now start with a pretty solid first draft.
But I don't send that draft to my client without reviewing it first. Not because it's necessarily wrong. In fact, a lot of the time, it's remarkably accurate. The problem is that accurate isn't always enough.
THE OPENING SIGNAL
AI doesn't have to get something wrong for us to need to change it.
When the output is obviously bad, we know we need to fix it. The harder part is recognizing when something is accurate and well-written, but still doesn't reflect everything we know about the client or situation.
WHAT ACTUALLY MATTERS
I've had AI-generated client recaps that accurately captured what was said but still needed to be changed. Sometimes it gave too much weight to something that wasn't really the most important part of the discussion. Sometimes it missed the nuance behind what a client was saying. And sometimes the next steps were technically correct, but I knew they needed to be framed differently based on where that client was at that moment.
AI now does a significant amount of that initial organizing and synthesizing for me. I still review what it gives me, but I'm starting from a much better place instead of doing all of that work manually.
And that matters for more than saving time. It gives me more capacity for the part of the work that actually needs me: thinking about the client, noticing what matters, deciding what needs more attention, and making sure I'm giving them what they need next.
There are things I know because I've actually worked with this person. I know what we've talked about before, what they've been working through, what deserves a little more encouragement, when I need to be more direct, and when something that came up doesn't actually need to make it into the follow-up.
AI has access to the information I give it. I have access to the relationship.
Client communication is more than the transfer of information. A recap, proposal, follow-up, check-in, or response to a problem all shape the client experience. Saving time is valuable, but making sure the final communication serves the client and the relationship is what matters.
ONE SMALL MOVE
The next time AI helps you create something a client will receive, give it one more review before you send it.
Don't just check whether the information is accurate. Look at what AI emphasized, what it left out, what you're asking the client to do next, and whether any context you know from working with this person should change what they receive.
Then ask yourself: “Does this give my client what they need from me right now?”
You may not need to change anything. The point is to review the output as the person responsible for the client experience, not simply as the person approving an AI draft.
WORTH PAYING ATTENTION TO
I read an article this week about the role AI is beginning to play across the entire customer journey, from discovery and shopping to customer service and follow-up.
What caught my attention wasn't another example of what AI can do. It was the author's argument that human oversight is becoming more important as AI becomes more involved in the customer experience.
I think that's an important shift in how we talk about AI. The conversation has focused so much on what we can hand over to it that we don't always talk enough about what good oversight actually looks like.
For a small business, that doesn't necessarily mean adding another complicated review process. It means remembering that when AI touches something your client or customer experiences, your judgment and knowledge of the relationship still matter.
Worth reading: AI Across the Customer Journey: Why Human Oversight Is the New Competitive Edge
I'm curious where this is showing up in your business. Are you using AI to help with client emails, proposals, follow-ups, recaps, or something else? And where do you still find yourself stepping in and changing what it gives you?
Hit reply and tell me. I'd love to hear how you're handling that line between letting AI make the work easier and making sure the communication still serves the relationship.
Talk soon,
Lucy
P.S. If you're trying to figure out where AI can make your business easier without losing the judgment and personal touch your clients value, that's exactly the kind of thing we can work through in a Spotlight Strategy Session.