Fixing Bad AI Summaries: A Quick Guide for AEs
Revenue Ops
Fixing Bad AI Summaries: A Quick Guide for AEs
You just wrapped up a fantastic discovery call. The prospect shared their budget, timeline, and key pain points. Your AI meeting assistant was running, and you're counting on that perfect summary to update your CRM.
Then you open it. The summary is a mess. It missed the budget nuance, confused the stakeholders, and completely omitted the crucial next step. Now, instead of moving on to your next deal, you’re spending 15 minutes editing a summary, trying to recall details from a call that’s already fading from memory. Sound familiar?
You’re not alone. While AI adoption in sales has exploded from 39% to 81% in just two years, many Account Executives are discovering that these tools can create as much work as they save. The promise of efficiency is lost in a sea of edits and corrections.
But the problem might not be the AI itself. It’s the workflow. This guide will walk you through how to troubleshoot bad summaries and, more importantly, how to adopt a better process that makes them obsolete.
The Real Cost of Bad Summaries (Context)
At first glance, a bad summary is just an annoyance. But for a high-performing AE, it’s a significant bottleneck that erodes the most valuable asset you have: time. When you’re constantly correcting AI outputs, you’re not selling.
This issue taps into the single biggest challenge sales teams face with AI: data quality. Inaccurate data erodes trust, clogs your pipeline with bad information, and leads to flawed forecasting.
Here’s what’s really at stake:
Wasted Time: The minutes you spend fixing summaries add up. Five bad summaries a week at 15 minutes each is over an hour of lost selling time. Over a quarter, that's a full day you could have spent prospecting or closing.
Missed Opportunities: An AI summary that fails to capture a prospect's hesitation about pricing or their excitement about a specific feature can lead to a poorly tailored follow-up, costing you the deal.
Dirty CRM Data: Every inaccurate summary you begrudgingly copy-paste into your CRM pollutes your data, making forecasting unreliable and team handoffs a nightmare.
The irony is that sales reps who use AI effectively see incredible results: 81% report shorter deal cycles and 80% achieve higher win rates. The key is getting the AI to work for you, not the other way around.
Quick Fixes for Better AI Summaries (Examples)
Before we talk about ditching the summary workflow entirely, let's cover some first aid. If you’re stuck with a conversation intelligence tool for now, you can improve its output by giving it better input. Think of it as guiding the AI to the right conclusions.
Here are a few prompting hints you can use on your calls to get better results:
Be a Human Signpost: Don't assume the AI knows what's important. During the call, use verbal cues to flag key information.
State Names and Roles Clearly: AI often struggles with names, especially unique ones. When introducing people or referencing them, speak slowly and clearly. "Thanks for joining, Sarah, the Director of Operations." This helps the AI attribute comments and action items correctly.
Recap at the End: Before ending the call, do a quick verbal recap of the most important points. This gives the AI a clean, condensed version of the critical information to pull from, increasing the odds of an accurate summary.
These tips can help, but they require you to change how you naturally speak during a call. And even with perfect signposting, you're still at the mercy of the AI's ability to interpret and summarize.
The Vicious Cycle of Constant Edits
Here’s the hard truth: If your primary AI workflow involves editing, the workflow is broken.
Think about it. You bought a tool to automate a tedious task (note-taking and CRM updates), but now you’ve become a highly-paid editor for a robot. The transcription-to-summary process is inherently flawed because it introduces an extra step where context can—and frequently does—get lost.
The traditional process looks like this:
Step 1: You have a conversation.
Step 2: The AI transcribes it (potential for error).
Step 3: The AI analyzes the transcript and creates a summary (high potential for error).
Step 4: You review and manually edit the summary.
Step 5: You copy and paste the corrected info into Salesforce.
This Rube Goldberg machine of a workflow is what’s holding you back. What if you could skip steps 2, 3, and 4 entirely?
What if you could go directly from your brain to your CRM in seconds? That’s where a different approach comes in. Instead of relying on a tool to interpret what happened, you use a tool that lets you state what happened directly.
This is the philosophy behind voice-powered Salesforce tools like getcolby.com. Instead of generating a summary for you to fix, Colby empowers you to make updates with your own voice, ensuring 100% accuracy because it’s coming directly from the source—you.
Tired of fixing inaccurate AI summaries? See how you can update Salesforce in seconds with your voice.
A Better Way: From Summary-Dependent to Direct-to-CRM
Imagine this workflow instead. You finish your call. While the details are still fresh, you activate a Chrome extension and say:
"Colby, update opportunity 'Global Tech Inc Phase 2.' Client is concerned about the Q4 budget but is very interested in a phased implementation. Set the next step to send the revised proposal by end of day tomorrow and move the stage to 'Proposal.'"
In seconds, Colby parses that command and updates all the correct fields in Salesforce: the opportunity notes, the next step, the due date, and the sales stage.
There was no summary. No editing. No copy-pasting. Just a seamless, voice-powered update that took less time than reading a bad AI summary.
This direct-to-CRM approach solves the core problems we discussed:
It Guarantees Accuracy: You are the source of truth, not a machine's interpretation of a conversation.
It Saves Immense Time: What takes 10-15 minutes of editing now takes 15-30 seconds of speaking.
It Maintains Data Purity: Your CRM remains clean, accurate, and trustworthy, which is the foundation for predictable revenue and growth.
This is about more than just a cool tool; it’s about fundamentally rethinking your post-call process to eliminate friction and maximize selling time. And it goes beyond single updates. With a tool like getcolby.com, you can even perform bulk updates. For example: "Colby, find all my opportunities in the 'Discovery' stage and set a follow-up task for this Friday."
The Goal: Flawless Data and More Time to Close
Ultimately, the goal isn't to get a perfect summary. The goal is to get accurate, contextual data into your CRM as quickly as possible so you can move on to the next deal.
When your data is pristine, everything else in the sales process gets easier. Your follow-ups are sharper, your forecasts are more reliable, and your ability to close deals skyrockets. Those top-tier stats—shorter deal cycles, bigger deals, higher win rates—are built on a foundation of clean data. You can't achieve them if you're constantly fighting with your tools.
By moving away from a workflow that requires you to constantly troubleshoot bad summaries, you’re not just fixing a minor annoyance. You are reclaiming control over your time and your data.
Conclusion: Stop Being an Editor, Start Being a Closer
AI should be a tailwind, not an anchor. If you find yourself spending more time correcting your tools than using them to sell, it’s time for a change.
While prompting tricks can offer a temporary patch, the long-term solution is to eliminate the failure-prone summary step altogether. Adopting a direct-to-CRM workflow gives you the speed of AI with the accuracy of your own expertise. You get the best of both worlds without the headache of deciphering and editing flawed summaries.
Stop being your AI’s editor. It’s time to get back to what you do best: building relationships and closing deals.
Ready to ditch bad summaries for good and reclaim your selling time? Explore getcolby.com and see how a voice-first workflow can transform your Salesforce updates.