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

Sales reps spend more time updating CRM than selling.

HubSpot's new Smart Deal Progression flips that: after every call, AI suggests CRM updates, drafts follow-ups, and surfaces next steps — using the full deal history, not just the last conversation.

Reps approve with one click. Forecasting actually works.

Check out our HubSpot Spring spotlight, linked in the comments.

As organizations struggle to turn AI into consistent execution, Allego 9 brings intelligence directly into the workflows where revenue teams operate

WALTHAM, Mass., May 5, 2026 /PRNewswire/ -- Allego, Inc., the leader in AI-powered revenue enablement, today unveiled Allego 9 at its 10th Annual Sales Success Summit, introducing a next-generation platform designed to help revenue teams turn AI into consistent execution.

Work is moving into AI tools.
But your sales data isn’t there yet.

Last week we shipped our MCP server.

And as of today, Mixmax AI is live as an official ChatGPT app. 🎉

That means your emails, sequences, and meeting transcripts are now accessible directly inside ChatGPT.

What this unlocks:
→ Prep for pipeline reviews in seconds
→ Find stalled deals hiding in your inbox and re-engage them
→ Pressure-test your sequences against what actually wins deals

Most sales tools still assume you’ll switch tabs.

AI-native selling flips that.

The work happens where you already are, and the data shows up there too.

Try it here:
https://lnkd.in/gxkygyxE

____
What’s the first thing you’d want your sales data to do inside ChatGPT?

I've built dozens of AI agents across our GTM operation.

Here’s how I decide which one to build -

Most teams think “adding AI” means dropping ChatGPT into one workflow and moving on.

That is not an agentic system.

Agents are:

→ Always-on
→ Trigger-based
→ Making decisions
→ Taking actions

No human in the loop for 90% of the low-value work.

The real question is not “which tool”.

The real question is “where in your GTM does an agent belong”.

Here is the diagnostic I use across 4 functions.

Sales

→ Time from buying signal to first outreach
→ How reps prep discovery (15 minutes of Google = agent)
→ What happens to overnight replies
→ How you choose which deals to push this week

Marketing

→ How you know which campaigns drive pipeline
→ Where competitive intel comes from
→ Time from idea to campaign live
→ Who decides inbound → sales vs nurture

RevOps

→ How clean your CRM data is
→ How many tools a lead touches before a sequence
→ Which reports still live in spreadsheets
→ What breaks when you 2x volume

Customer Success

→ How you detect churn risk early
→ What signals show expansion readiness
→ How manual onboarding feels for the team

Any answer with “too slow”, “manual”, or “we do not” is an agent slot.

Then match to 5 agent types:

→ Research: signals, company intel, tech stack
→ Enrichment: data waterfall, contacts, email verify, CRM gaps
→ Content: sequences, briefs, reports from data
→ Routing: reply tags, scoring, stage updates, alerts
→ Monitoring: churn, pipeline, anomalies, data drift

Start with one.

Pick the slowest, most repetitive, most time-sensitive workflow.

Team size rule:

→ Under 10: Routing first (reply classification or lead scoring)
→ 10–50: Enrichment first (data quality unlocks all)
→ 50+: Monitoring first (what you cannot see hurts you)

I mapped 20 concrete agent builds across Sales, Marketing, RevOps, and CS into one cheat sheet.

One of the most useful ways I’m using AI right now:

Pulling a POV from call transcripts.

By the third call, things get messy.

Different stakeholders.
New objections.
Shifting priorities.

You leave thinking:
“Where does this deal actually stand?”'

Instead of guessing…
I drop the transcript into AI and use this prompt:

"Act as a senior sales strategist. Based on this transcript:
What is the buyer actually trying to solve?
What are the real blockers (not surface level)?
Who has influence vs who just has opinions?
How urgent is this problem (1 out of 10 and why)?
What risks could stall this deal?
What should my next 2–3 actions be to move this forward?"

I use AI in every part of my sales process.

Tried almost everything out there, narrowed it down to three tools: Claude Code, Claude Cowork, and Lindy. If I'm building something from scratch, Supabase and Vercel too.

Here's exactly how I use them:

1/ Account + call prep

→ Account maps, strategic business objectives, exec behavior, investor behavior, team dynamics, recent intel. I have a full picture before every single call.

2/ During + after the call

→ Call recording pushes deal info to CRM. Champion follow-up and nudge reminders. Action items, collateral, case studies, business case drafts → AI gives me the v1, then I use it as a thought partner and collator for the final version.

3/ Deal management

→ CRM updates as deals move through stages. At-risk deal flags. Forecasting based on actual signals (emails, texts, call transcripts, usage).

4/ Reporting + dashboards

→ Pipeline visibility. Summon through Slack, text → instant reports, dashboards, insights.

5/ Coaching

→ After every single call I get coaching sent to my phone. Voice note or text. End of the week, a synthesized coaching summary. Patterns, strengths, where to sharpen, what best practice am I lacking, goals and accountability.

6/ Prospect intelligence

→ ICP refinement. What pain points resonate, what messaging lands, deal blockers, competitive intel, etc. After enough calls, AI starts showing me patterns I wouldn't catch on my own. Which personas convert fastest, what objections show up at which stage, where deals actually die.

I think most sales leaders are overwhelmed right now with when and how to use AI. There's too much noise. This is what's actually working for me.

What am I missing - what have GTM folks found most valuable?

I broke up with ChatGPT. 2 years together. Walked away.

Every session felt good. Warm. Encouraging. But my deals weren't closing faster.

I'd ask for objection handlers. Get 11 seconds of typing. Then a response that validated my approach and left me with more options than clarity. ChatGPT treated me like someone who needed support.

I needed a closer.

5 months ago, I tried Claude.

Pasted a stalled deal. Asked why the prospect went dark.

"Your last email buried the value prop. Here's the exact follow-up that reopens this conversation."

Brutal. Specific. Ready to send.

I don't need AI to validate my outreach. I need it to tell me why the deal stalled and how to unstick it.

Team Claude or team ChatGPT?

I built a fully branded company SOP in under 5 minutes the other week—finished, formatted, and ready to distribute. After a year of using AI daily as a sales professional and now a sales leader, I’ve found the gap between reps who leverage AI and those who don’t is widening fast. I use AI to: analyze pipeline/data in minutes, generate presentation decks from datasets (incl. Gemini in Slides), turn call transcripts into tailored follow-up emails and deal-review brainstorming, validate assumptions by comparing buyer personas to market indexes, and convert a short Loom walkthrough + transcript into a polished branded guide/SOP the same day—then iterate on it later.