Setting Up Your AI Sales Workflow
Build a practical, repeatable AI workflow that fits into your existing sales day. You'll leave with a concrete system for using AI before, during, and after every major sales activity.
In practice: Complex proposal: full day → 2–3 hours
Your version of this lesson adapts to your role. After the 3-minute assessment, examples, scenarios, and exercises are tailored specifically to your job function and experience level.
Personalise →The Problem with Ad-Hoc AI Use
Many salespeople try AI a few times, get inconsistent results, and conclude it is not worth the effort. The problem is almost never the tool — it is the absence of a system. Without a defined workflow, AI use is sporadic, and sporadic use produces sporadic results.
The solution is to decide in advance exactly when and how you will use AI in your sales day. Build it into your existing routines so that AI assistance becomes automatic rather than effortful.
The Three Moments That Matter
Before every customer-facing interaction, AI should be doing your prep work. Before a discovery call: research the company, the buyer's background, and any recent trigger events. Before a proposal: summarise the needs identified in discovery and draft a structure. Before a negotiation: identify likely objections and prepare responses.
During creation and communication, AI should be accelerating your output. Writing a follow-up email after a meeting: give AI your notes and ask for a draft. Updating CRM after a call: paste your notes and ask AI to extract the key fields (pain points, timeline, next step, stakeholders). Building a proposal: use AI to draft each section, then edit to your voice.
After patterns emerge, AI should be surfacing insight. Weekly: ask AI to analyse your pipeline and flag anything unusual. Monthly: give AI your activity data and ask which behaviours correlate with your won deals.
Building Your Personal Prompt Library
Effective AI users build a small library of prompts they use repeatedly — customised for their product, their typical buyer, and their sales style. A basic library might include:
- ■Pre-call research prompt — "Research [Company Name] and give me their recent news, likely business priorities, and three questions I should ask in a discovery call."
- ■Email draft prompt — "I just had a discovery call with [Name] at [Company]. Their main challenges are [X]. Draft a follow-up email that summarises what we discussed and proposes [next step]. Tone: warm but professional."
- ■Objection prep prompt — "My prospect sells [product] to [buyer] and I am pitching [solution]. Give me the five most likely objections and strong responses to each."
Save these in a document. Refine them as you learn what produces the best outputs. A well-maintained prompt library is a genuine competitive asset.
The Workflow in Practice
A structured AI-enhanced sales day might look like:
- ■Morning (15 minutes): Run your pipeline review prompt. AI flags stalled deals and surfaces the two or three most important activities for the day.
- ■Before each call (5 minutes): Run your pre-call research prompt for the prospect or account.
- ■After each call (5 minutes): Paste your notes into AI and extract CRM-ready data plus a follow-up email draft.
- ■End of week (10 minutes): Run your weekly analysis prompt to identify trends and priorities for next week.
This structure adds under 30 minutes of AI time per day while compressing hours of manual work.
Key Takeaways
- ■Ad-hoc AI use produces inconsistent results — build AI into defined moments in your sales workflow
- ■The three high-value moments are: pre-interaction prep, during content creation, and post-activity analysis
- ■A personal prompt library of five to ten well-crafted prompts is a genuine competitive asset
- ■A structured AI workflow adds 20-30 minutes per day while compressing hours of manual work
- ■Start with pre-call research — it is the highest-impact, lowest-risk entry point for most reps
Before you practise
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