How We Solved Meeting Overload with AI: From Forgotten Action Items to Automated Task Management

Cluttered mind after all those morning meetings

Ever spent your morning in back-to-back meetings, only to sit down for focused work and realize you've completely forgotten the action items from your first call?

At TensorOps, this scenario resonated with nearly everyone. When we conducted a company-wide brainstorming session on workplace pain points, meeting overload and lost action items emerged as one of the most pressing daily challenges our team faced.

The question became: how do you solve this systematically across an entire organization?

The Problem: When Meetings Multiply, Memory Fails

In today's remote-first world, meetings have multiplied exponentially. What used to be a quick hallway conversation now requires a scheduled 30-minute call. The result? Days packed with back-to-back meetings where critical action items slip through the cracks between calls.

Our team was drowning in this cycle. Important decisions were made, tasks were assigned, but by the time people had a moment to breathe, the details had already faded. We needed a systematic solution, not just better note-taking habits.

The Only Viable Solution: AI Meeting Intelligence

When we looked at this problem, it became clear there was really only one scalable solution: AI that could transcribe calls and automatically extract action items.

Manual note-taking doesn't work when you have back-to-back meetings. Asking people to "just be better at taking notes" isn't a systematic solution - it's wishful thinking. We needed technology that could handle the cognitive load of tracking action items across multiple conversations.

Also, we are selling solutions around AI, we should pray what we preach right?

Why We Chose Fathom (And What to Look For)

We started by evaluating several AI meeting tools in the market - Jamie, Granola, Fathom, Notta, and others. While most offered basic transcription out of the box, Fathom offered a bit more for around the same price point.

Our requirements were:

• Seamless call recording: record calls across Google Meet, Zoom, and Teams

• Team plan with easy user management and per recording access

• API or Zapier integration for custom integrations

  
  

Fathom emerged as our top choice because it delivered on all these fronts and on top of it transcribes meetings and ,straight out of the gate, produces action items for each meeting.

We could've gone for a different tool that would just record the call and build a system that would transcribe the call (using voice to text model) then extract action items (using LLMs) but Fathom offered all of this for a similar pricing (or close to similar) of tools which only offered recording capabilities so we decided to give it a try and see how it fared.

The Solution

We ended up with the following flow:

1. Fathom processes the meeting and identifies action items with assignees

2. Slack notification sent to each assignee with their specific tasks

3. Human confirmation required - assignees verify the tasks are correct

4. Automatic task creation - confirmed items are added to Google Tasks

5. Tracking and follow-up - tasks are now part of each of the assignees' workflow

   
   
   
   

A sketch of the flow can be seen bellow. We used Zapier because Fathom still hasn't an API and only offers an integration with Zapier to integrate with ones systems. Then, once we extract the meeting info plus action items to our databases in GCP, we use a couple of scripts hosted in GCP Cloud Functions to send the slack message, get the confirmed action items, update the databases, and send the final action items to Google Tasks.

The slack confirmation was added because the action items created from Fathom still had some regular issues and to make sure people didn't end up with wrong action items or action items not assigned to them. This allowed to re-direct action items to the correct assignee or even re-write the assignee. We also found out that just having this message pop up on Slack after the meeting helped people not forget their tasks and the outcome of meetings.

(this a classical example of why most AI systems still need an human in the loop)

Sketch of the flow

Results and feedback

The adoption has been incredible. Our team went from regularly missing action items to having a systematic, trackable approach to meeting follow-ups.

Key improvements we've observed:

• Faster meeting follow-up - tasks are assigned within minutes

• Better accountability - everyone knows exactly what they committed to

• Less meeting fatigue - people can focus on discussion rather than frantic note-taking

  
  

The best indicator of success? The immediate messages I get whenever the system goes down - people have become completely dependent on this workflow.

Getting Started: Your Turn

Want to implement something similar? Here's our recommended approach:

1. Audit your meeting pain points - survey your team about what frustrates them most

2. Design your solution - evaluate based on your specific needs and requirements

3. Start small - pilot with one team before rolling out company-wide

4. Build feedback loops - ensure the system actually solves the problem, not just automates it

5. Iterate based on usage - the best workflows emerge through real-world testing