Encouraging sales team to use generative AI

This guide explores practical strategies for helping sales teams to start using AI tools effectively.

Sales professionals report spending 70% (yes, 70!) of their time on tasks that aren't actually selling. AI can handle a lot of these tasks and therefore has the potential to make a huge impact. Yet many sales teams struggle to actually use AI successfully.

In this guide, we'll show you simple ways to introduce AI workflows and tools to your sales reps that will:

• Make daily work easier

• Work well with existing processes

• Keep the personal connection in sales

Whether you manage a team or want to improve your own sales process, this guide will help you use AI with confidence while keeping your client relationships authentic.

🎯 The challenge of adoption

Sales has always been relationship-driven, with success depending heavily on personal connections and human intuition.

Yet today's sales professionals face mounting pressure to do more with less time. This pressure creates an interesting paradox. 81% of sales teams are either experimenting with or have fully implemented AI. However, many still struggle with effective adoption. The reason often lies not in the technology itself, but in how it's introduced and integrated into existing workflows.

Resistance often stems from:

• Concerns about complexity

• Fear of replacement, and

• Uncertainty about how the technology integrates into daily workflows.

For instance, sales reps may feel skeptical about whether AI can generate high-quality client proposals or handle email personalization without losing the "human touch.”

Let’s look at some ways you can help your sales reps get comfortable with using and integrating AI into their daily work.

⚡ Quick wins show immediate, practical value

The quicker you can demonstrate how effective AI can be, the more likely you are to get buy in from your team. Start with workflows or processes where you can use AI quickly and with a tangible impact.

Here are some actionable ideas:

A. Chat with your product docs

Digging through documentation to answer prospect questions is a time-sucker of a task for sales reps. There’s always the risk too that reps give misinformation if they’re unable to find the answer they need quickly enough.

Using AI to “chat” with product docs solves these issues, giving sales reps a quick and easy way to locate information they need so they can focus more time actually selling.

This concept involves feeding product documentation into an AI tool so sales reps can ask natural language questions about product features, specifications, use cases, etc. and get immediate, relevant answers instead of having to manually search through documentation.

How to introduce it to your team:

Getting started is easy—just open up ChatGPT or Claude, upload product documents and ask questions. Questions your sales reps might ask:

• Technical or feature questions, e.g. "What's our guaranteed uptime SLA?” or "Does feature X work on mobile devices?”

• Integration questions, e.g. "What's required to set up SSO?”

• Security or compliance questions, e.g. "Where is customer data stored?”

• Use case questions, e.g. "What industries use feature X the most?” or "Find examples of customers using our API for Y”

• Implementation questions, e.g. "What's the migration process from [competitor]?”

• Competitive comparison questions, e.g. "What's different about our reporting capabilities vs [Competitor]?"

Bonus: Make a knowledge base for repeated use

The above steps are great for getting started, but uploading documents every time you want to ask a question gets repetitive pretty quickly.

Instead, you can create a Project in Claude (or a GPT in ChatGPT) where you upload all the documentation once, then chat to the AI whenever needed. Whenever your product docs change or are updated, you just need to re-add them to the Project or GPT to keep it up to date.

B. Automate meeting summaries and follow-ups

Turning client conversations into actionable follow-ups: crucial, but time-consuming. Sales reps often spend valuable selling time trying to capture key points from calls and craft the perfect follow-up message. AI can do all of this work in minutes, and can often have a better eye for detail than a human.

Here's how to introduce it to your team:

1. Start with meeting notes‍
   Have reps use an AI tool like Granola or Otter to transcribe their next few sales calls. Ask them to also type some rough notes—bullet points or scattered thoughts will work fine.

2. Show the transformation
   In your next team meeting, take someone's transcript and rough notes (with permission of course) and demonstrate how AI can turn them into polished content. Use a prompt in ChatGPT such as: 'Transform these meeting notes into (1) a clear summary of key points discussed (2) a list of action items for both parties and (3) a professional follow-up email that references specific conversation points.'

3. Customize by meeting type
   ‍Show your team how to adjust the approach based on the meeting context:
   • Discovery calls → Focus on synthesizing prospect pain points and needs
   • Product demos → Emphasize capturing specific features that resonated
   • Negotiations → Concentrate on documenting agreed points and next steps

The 'wow moment' happens when reps see unstructured transcripts and notes transformed into well-structured, professional documentation in minutes rather than hours.

Bonus: Create an automated follow-up system

Develop this by building a workflow that automatically summarizes calls and emails them to your reps. Using an automation tool like Lindy, you can create an AI personal assistant that will join your meetings, take notes, and send you email summaries.

This will allow your sales team to focus on what matters—turning up to calls and doing a great job of selling—knowing the time-consuming admin is taken care of by AI.

C. Automate CRM entries

Most modern CRMs now include AI capabilities that can save hours of manual work. For example, Salesforce Einstein can automatically log emails, update records, and suggest the next best actions. These tools are perfect "quick wins" since they're already integrated into your existing workflow.

How to do it:

1. Start with email logging
   Show reps how their CRM's AI can automatically capture emails and create contact records. Have them try it with their next few prospect conversations - they'll see contact details, company information, and interaction history populate automatically.
   
   See how HubSpot's Smart CRM automates tasks like email logging and contact record creation.
   ‍

2. Enable smart suggestions
   Demonstrate how AI can suggest the next best actions based on similar deals. For example, Einstein analyzes successful past deals to recommend which prospects to contact next or what actions typically lead to won opportunities.
   
   Read more on using Salesforce Einstein’s ‘Next Best Action’ feature.
   ‍

3. Use automatic field updates
   Show how AI can update fields like opportunity status, deal stage, or next steps based on email content and meeting transcripts. This keeps records current without manual entry.
   
   Learn how Momentum automatically captures call notes and syncs them to your CRM.

🎯 30-day implementation plan

Successfully integrating AI into your team isn’t just about introducing tools. You’ll want to encourage a culture where AI enhances rather than disrupts your team's selling motion.

Companies using AI for sales have:

• Are 1.3x more likely to see increased revenue

• Reduced call time by 60%

• Reported 47% higher conversion rates

But achieving these kinds of results requires careful planning.

Here’s a 30-day plan for getting started using AI in your sales team:

Week 1: Create an AI champions network

1. Choose 2-3 reps who are enthusiastic about new technology, and invite them to try out new AI workflows. We recommend starting with the sales tutorials in the Ben’s Bites catalog.

2. Ask them to document and share their successes and learnings. Use their experiences to refine processes before wider rollout.

3. These reps can also become pillars of help for other employees to ask questions and lean on for AI-related advice.

Week 2: Build systems that make knowledge sharing effortless

1. Have the rest of the team start experimenting with easy tasks that AI can handle like the ‘Quick wins’ discussed earlier in this article.

2. Set up a dedicated Slack channel and encourage your team to share AI tips and wins. Create a searchable knowledge base of proven prompts and workflows.

3. Schedule monthly 'AI office hours' where reps can get help.

4. Document common pitfalls and solutions; share them regularly.

Week 3: Track and share metrics that demonstrate real impact

1. Start measuring how AI is impacting work, e.g.
   • Time saved per rep per week
   • Quality improvements in client communications
   • Response rates to AI-enhanced content
   • Deal velocity changes

2. See ‘Measuring AI's impact on your sales team’ below for further details.

Week 4: Remove any friction points

1. Make sure you have clear guidelines in place covering appropriate AI use

2. Create easy-to-follow templates for common tasks

3. Integrate AI tools with existing CRM workflows

Week 5: Turn AI adoption into a team sport

1. Create friendly competition around AI usage and results

2. Recognize and reward innovative AI applications

3. Share success stories in team meetings

4. Gamify the learning process with challenges and rewards

📊 Measuring AI's impact on your sales team

To know if AI is truly helping your sales team, you need to track both adoptions (are people actually using it?) and results (is it making a positive difference?). Here's how to measure both:

1. Set up quick feedback loops
   ‍Create some simple ways of collecting insights. These might be less measurable and more ‘to give you a feel’ for how much AI is being used. For example:
   • Add a quick emoji reaction system in your team's AI tips channel (👍 for "saved me time", 🎯 for "helped close a deal", etc.)
   • Do 5-minute round-robins in weekly meetings where reps share one AI win
   • Track which prompts and templates are being copied/reused most often

2. Track time saved
   ‍Measure how AI is speeding up common tasks. Total this up and monitor how it changes weekly. This will not only prove AI’s value; it can be incredibly motivating for reps to see just how much time they’re getting back.
   • Track time spent on proposal creation (before vs. after AI)
   • Measure average response time to client emails
   • Count the number of follow-ups sent within 24 hours of calls
   • Monitor template usage and customization rates

3. Monitor quality indicators
   ‍Look for things you can track that are clear markers of improvement. For example:
   • Compare email response rates between AI-enhanced and traditional emails
   • Track prospect engagement metrics (meeting acceptance rates, proposal review time)
   • Monitor client feedback on communications and proposals
   • Analyze meeting notes quality and completeness

4. Create a simple monthly scorecard
   ‍Rather than tracking everything, pick 3-4 key metrics that matter most. Ask ChatGPT to help you put together a scorecard template, and for help completing it each month. Metrics you might choose from include:
   • Email response rates
   • Meeting acceptance rates
   • Time to first response
   • Time saved per week
   • Number of prospects contacted
   • Proposals generated
   • Client feedback scores
   • Email personalization levels
   • Follow-up completion rates

⚠️ When things go wrong: A troubleshooting guide

Problem: The team seems overwhelmed or resistant

What you might see:

• Reps avoiding AI tools
• Confusion about which tool to use when
• Frustration with learning new systems

Quick fixes:

• Scale back to just one tool and use case
• Set up daily 15-minute AI office hours
• Share specific examples of how other reps saved time

Problem: AI outputs aren't reliable or safe

What you might see:

• Client information appearing in prompts
• Inaccurate or off-brand communications
• AI being used for sensitive decisions

Quick fixes:

• Create a simple checklist for reviewing AI outputs
• Share examples of good vs. risky prompts
• Set up clear boundaries for AI use cases

Problem: Duplicated effort and inconsistency

What you might see:

• Everyone is creating their own versions of the same prompts
• Different approaches to similar tasks
• Uncertainty about when to use AI

Quick fixes:

• Create a central prompt library
• Schedule weekly shares of AI wins and workflows
• Document clear guidelines for AI vs. manual tasks"