Want to implement AI? Start with the most boring task in your business.
Everyone’s jumping straight into the sexy AI stuff. Let ChatGPT write my marketing copy!” “Automate my entire sales process!”
Stop it.
You’re starting in the wrong place. Here’s the thing: if you want AI to actually work for your business, start with something stupidly simple.
Start with AI meeting note-takers.
Why meeting transcripts beat marketing automation
Meeting transcripts are different. They’re low stakes, high value, and they teach you how AI actually works with your specific business data.
Most people want AI to solve their biggest problems first. They’re trying to get AI to write entire marketing strategies or handle complex customer service scenarios.
But here’s what happens: they get frustrated when the AI doesn’t understand their business context, produces generic outputs, or misses critical nuances.
You probably spend way more time in meetings than you’d like—MIT research says it averages 23 hours a week. And 67% of professionals admit their notes don’t cut it. AI transcription tools can capture 95%+ accuracy rates while freeing you to focus on the conversation itself.
I actually do still take meeting notes because I’m generally doing a better job of pulling out the most actionable things. But what I really love these AI note takers for is getting the transcripts.
These transcripts are pure gold.
The tool landscape (what you need to know)
Here’s the breakdown of the main players:
SuperNormal: Clean interface, good AI summaries, integrates well with CRMs. $30/month. This is what I use.
Otter.ai: Most popular option, solid transcription accuracy, good for team collaboration. Starts at $17/month.
Fireflies.ai: More advanced analytics, conversation intelligence features, good for sales teams. Around $20/month.
Rev: Human + AI transcription, highest accuracy but more expensive. Good if precision matters more than speed.
The tool matters way less than building the habit. Pick one that integrates with whatever video platform you’re already using.
How to get started (week-by-week implementation)
Here’s exactly how to roll this out without overwhelming yourself or your team:
Week 1: Foundation setup
Pick a tool and connect it to your calendar or video platform. Critical first step: Always ensure you have explicit consent from all attendees before you start recording and transcribing. Most tools have settings to automatically announce recording to participants.
Test it on one internal meeting first. See how the transcription quality looks, make sure the integration works.
If you’re working with sensitive or regulated data, make sure your transcription tool encrypts recordings, stores data securely, and complies with your industry’s privacy requirements.
For businesses in regulated industries, verify your chosen tool meets compliance requirements (GDPR, HIPAA, etc.) before processing any sensitive conversations.
Week 2: Capture everything
Turn on transcription for every client call, team meeting, vendor discussion. Don’t be selective yet; just capture everything.
After each meeting, download the transcript. Don’t analyze it yet, just get in the habit of saving it somewhere organized.
Week 3: Basic AI analysis
Take your transcripts from week 2. Paste them into ChatGPT or Claude one at a time.
Ask these three questions for each transcript:
- “What were the key commitments made in this meeting?”
- “What concerns or objections came up?”
- “What should I follow up on?”
Save the AI responses with each transcript.
Week 4: Pattern recognition
Now you should have 8-12 analyzed transcripts. Paste all the AI summaries into another AI prompt:
“Looking at these meeting summaries, what patterns do you see? What concerns come up repeatedly? What commitments do I make most often? Where do conversations tend to get stuck?”
This is where it gets interesting. You’ll start seeing your own patterns, your clients’ patterns, and opportunities you’ve been missing.
What I actually do with transcripts (and what you can adapt)
I’ll take the transcripts, put them into AI, and ask things like:
- “What did we actually commit to in this meeting?”
- “What were their main concerns or objections?”
- “What action items came out of this discussion?”
- “What patterns do you see across my last five client calls?”
The AI catches stuff I missed. It spots patterns I didn’t see in the moment. It organizes commitments way better than my handwritten notes.
But here’s where you can take this further: I build knowledge bases for each client and reference back to meetings when there’s confusion or misunderstandings.
When a client says, “I never said that”? You have a transcript.
When you need to prep for a follow-up? You can query your meeting history for context and previous concerns.
When you want to understand what’s working in your sales process? AI can analyze dozens of calls and tell you which approaches get the best responses.
This has allowed me to kind of offload my memory. It made every conversation I’ve had searchable, every commitment documented.
Common implementation problems (and how you can avoid them)
Problem 1: Terrible transcription quality
If your transcripts are full of gibberish, the AI analysis will be useless.
How to fix it: Check your audio setup. Use a decent microphone, minimize background noise, speak clearly. According to Rev’s accuracy research, 90% of transcription failures are audio quality issues, not AI issues.
Problem 2: Generic AI responses
If the AI keeps giving you vague summaries like “The team discussed project timelines,” you’re not asking specific enough questions.
How to fix it: Get more specific. Instead of “What did we discuss?” ask “What specific deliverables did the client request? What was their timeline? What concerns did they express about the budget?”
Problem 3: Information overload
You’re capturing everything but not organizing it in a way that’s actually useful.
How to fix it: Create a simple folder structure: Client Name > Meeting Date > Transcript + AI Summary. Or use tags if your tool supports them. The key is being able to find stuff later.
Problem 4: Team adoption resistance
Your team thinks this is extra work or doesn’t trust the technology.
How to fix it: Start with just your own meetings. Show them specific examples of how it helped you remember commitments or prep for follow-ups. Let them see the value before asking them to change their workflow.
Advanced strategies (once you’ve mastered the basics)
Building client intelligence
After 3-6 months of transcripts with a client, you can ask AI: “Based on all these meeting transcripts, what are this client’s biggest priorities? What concerns come up repeatedly? What communication style works best with them?”
This becomes incredibly valuable for onboarding new team members or preparing for big meetings.
Sales process optimization
If you’re in sales, you can analyze your win vs. loss calls. Ask AI: “What’s different about the conversations that led to closed deals versus the ones that didn’t convert?”
You’ll start seeing patterns in objections, timing, or presentation approaches that you never noticed before.
Project post-mortems
At the end of projects, you can review all the meeting transcripts with AI: “What could we have communicated better? Where did scope creep start? What early warning signs did we miss?”
This turns every project into a learning opportunity instead of just moving on to the next one.
Why this transforms everything else
Here’s what’s really powerful about starting here: once you see how useful it is to have searchable records of every business conversation, it changes how you think about every other process in your business.
Suddenly you start asking: “What other routine stuff could AI handle?” “What other data am I generating that I’m not using?” “Where else can I stop trying to remember everything?”
Maybe you start transcribing your internal brainstorming sessions. Maybe you use AI to analyze customer support tickets. Maybe you begin documenting your sales calls to understand what actually closes deals.
The transcripts are just the beginning. They’re teaching you how to work with AI using your actual business data, not generic examples from blog posts.
Remember: the goal isn’t to replace your thinking during meetings. It’s to augment it. The AI handles the tedious task of capturing everything verbatim, freeing you up to focus on higher-level thinking, reading the room, and building rapport during the conversation.
Your next step
Pick a meeting transcription tool. Any tool. Set it up for your next client call.
After the meeting, take the transcript and paste it into ChatGPT or Claude. Ask it:
- “What were the key commitments made in this meeting?”
- “What concerns or objections came up?”
- “What should I follow up on?”
Do this for one week. I guarantee it’ll change how you think about AI in your business.
Because you don’t need AI to write your marketing copy or automate your entire sales funnel. You need AI to help you remember what happened in the meeting you had yesterday.
I’d start there. It’s low effort, super high return. And it’ll likely change how you think about every other process in your business.
