Qualifying sales opportunities with AI-generated discovery questions

Here are 10 things I now use AI for every single day to help us close more sales:

PS - free AI sales coach that helps you do all of this yourself (Link below)

1. Build call plans using P.P.O. — Purpose, Plan, Outcome. You send it the account, persona, stage, and meeting goal. It builds you a plan so you walk into every call knowing exactly why you're there, what you're covering, and what decision you're driving toward. Strong calls are designed, not improvised.

2. Turn call notes into follow-up emails in under 2 minutes. Paste in your notes and it writes a clean recap with the pain you uncovered, the business impact, the agreed next step, who owns it, and the deadline. Your buyer gets clarity. You stay in control of the deal.

3. Build discovery questions using F.A.L.L. — Frame, Ask, Listen, Layer. Give it the persona and deal context and it builds questions that make discovery feel like a real conversation. Not an interrogation. Not a checklist. The kind of call where the buyer starts selling themselves.

4. Pressure-test deals against the 3 Whys — Why anything, why us, why now. Paste in a deal summary and it tells you whether you actually have a deal or just an opportunity someone forgot to disqualify. Most pipeline problems are visibility problems.

5. Handle objections using AIA — Acknowledge, Isolate, Answer. Send it the exact objection word for word and it gives you a response that doesn't sound defensive, doesn't over-explain, and doesn't give ground you don't need to give.

6. Build multi-threading plans using the 5x8 Methodology. Tell it the account and your current contact. It helps you identify the 5 people you should be engaging and maps out how to get there. Single-threaded deals die. This is how you fix that before it's too late.

7. Test whether your champion is real or just friendly. There's a difference between someone who likes you and someone who will go to bat for you internally. It pressure-tests for Power, Pain, and Personal Win so you stop confusing access with influence.

8. Script your next steps before every call ends. Before the call, it helps you plan exactly how to confirm value, prescribe the next step, and get the next meeting booked before you hang up.

9. Clean up your forecast using real criteria. Give it your active opportunities and it classifies them as Best Case, Most Likely, or Commit based on whether budget is confirmed, the business case is built, technical sign-off is done, legal is in motion, exec alignment is real, and there is a clear path to signature.

10. Sort your day by actual revenue impact. It helps you separate what moves pipeline from what just feels productive. Prospecting, deal progression, executive access, mutual action plans, call prep, follow-up — versus the admin that fills a calendar but doesn't fill a quota.

Free AI sales coach to help you do this yourself: https://lnkd.in/epxVqjPP

If you want me to coach you directly: https://lnkd.in/exDqSB6S

What does an Agent first Sales person look like? Marc Benioff said something in the latest SaaStr Podcast that really sharpened my thinking. He said "When I now write a V2MOM* I always have a Salesforce executive and Agent with me....I like having an AI Partner...it is another tool in the toolchest.."

I've used Copilot, AonGPT, ChatGPT, Gemini (yet to fully immerse myself in Claude) for sometime to support my client interactions and sales processes for myself and the team. Getting to the crux of the problem for an enterprise sales person; deals are complex, especially at Aon. We don't struggle with a lack of capability or content but we do need to maximise the following:

The information across teams

High quality and consistent deal qualification

Utilisation of internal expertise

Our time to prepare deeply for every client interaction

Internal relationship mapping

If we get this right we always show up informed and can create tangible value for our clients.

This is how I use an agent most effectively. At Aon we use Microsoft Co-pilot so this is where I have built my agent called 'Aon Sales and Client Insights'. The goal is simple; 'Help me (and others) think more strategically before every client interaction'.

My agent

The UX is simple, I have created 7 bespoke prompts that I can choose to start my Agent from preparing a client meeting, analysing as sales opportunity, planning Aon Client Leadership support, leveraging our Human Capital and Risk Capital Structure to the next steps in a deal.

I found using AI to help you build these and the agent description and instruction really valuable. I spent time in ChatGPT explaining what I was trying to achieve with my agent to build the prompt title and system prompt. This is fully aligned with how we work at Aon. For example, ACL will not mean too much to someone in another business but at Aon, it is our superpower.

Building out the prompts

Behind this is a clear Agent Description and Instruction. This part is crucial to get right. The description explains what it is and when it should be used, so colleagues (and AI agents, if enabled) can use it effectively. The Instructions direct the behavior of the agent, including its tasks and how it completes them.

Agent Builder for System Prompt

The Instruction is 5,100 characters, I've shown a screenshot above but again, take time and use AI to help write this out. It is a critical part to the effectiveness of the AI. Especially how you want to think about the prompts i.e. for my area of work, a human capital lense is crucial.

Knowledge. What are the sources I want my agent to use to generate responses? Firstly I have allowed the agent to search all websites. In addition I have uploaded X17 specific documents that are proprietary Aon datasets and further specific sites (including Sharepoint sites) that I want it to focus in on. For example, we just released our Human Capital Trends Study, so this is one of those datasets.

So what is an example of the output? I was recently preparing for a meeting with a top 3 global asset management firm.

Using one of my prompts the Agent provided me with a comprehensive overview of the situation for this client based on their annual report and other clients notes I have. It then ran a comparison to their key objectives against the broader market by analysing 17 different Aon datasets (surveys, benchmarks and case studies that I had uploaded) and then provided me with key insights and most importantly, 4 qualification questions to help qualify the gaps in the opportunity.

What I love about this is whether you are in HR, Customer Success, Broking or Finance, this is completely scalable. I can deploy this to my sales team and we can iterate to ensure this is going to deliver best value today and in the future. It helps focus your meeting prep and reduce time looking for information.

As our CEO, Greg Case , said recently "We are a firm of 60,000 colleagues today....we do not aspire to be a 30,000 colleague firm in the future doing the same work we do today, we are committed to a firm of 60,000 colleagues using AI to deliver to deliver more value for our clients...".

For me, this is such a great demonstration of the value of AI to ultimately deliver better decisions to our clients.

I'd be curious to understand how others are using Agents in this space.

*V2MOM is a management and communication process used by the team at Salesforce. It is an acronym that stands for vision, values, mission, objectives, and measures.