Jake Dunlap's Recent LinkedIn Posts

Most people are better off reading one book and actually doing something about it…vs reading 25 to check a box The same goes for buying revenue tech I hear all too often.. “We’ve invested in 6 AI tools this year… and I can’t point to a single one that moved revenue.” Six tools. Zero measurable pipeline lift. That’s not an AI problem. That’s a prioritization problem. Everyone says they’re “doing AI.” But less than 49% of B2B GTM teams actually use AI in daily workflows. Not pilots. Not experiments. Real operational usage. And here’s where it gets worse: → 62% of sales orgs say they’ve adopted AI → Only 25% report high impact → 95% of generative AI pilots fail → 77% of sellers missed quota in 2025 So what’s happening? Most teams are buying tools without deciding what problem they’re solving. They automate random tasks. They test trendy features. They stack tech on top of broken workflows. By month three? → Reps are context-switching more → Forecasting is still inaccurate → Pipeline velocity hasn’t changed → Finance is questioning every invoice More AI doesn’t equal more revenue. Unfiltered AI equals more complexity. Here’s what the best teams do differently: They force every AI initiative through three questions: → Will this shorten deal cycles? → Will this increase conversion by X%? → Will this free up measurable capacity? If it can’t tie to revenue or efficiency, it doesn’t get funded. They also use a simple impact-effort filter: → High impact / Low effort = move now → High impact / High effort = plan properly → Low impact / High effort = kill it And they assign ownership. No owner = no adoption. No adoption = no impact. AI is a multiplier. If your data is messy, it multiplies chaos. If your workflows are inconsistent, it multiplies dysfunction. If leadership isn’t aligned, it multiplies confusion. The companies winning with AI aren’t buying more tools. They’re brutally disciplined about what they implement. So before you ask, “What AI should we add next?” Ask this: What revenue problem are we actually solving and do we have the operational maturity to solve it?

If your GTM plan for 2026 is “buy more AI tools,” you’re about to waste a year. The real shift isn’t AI. It’s that lower-funnel optimization is tapped out and teams are finally being forced up-funnel. Because you can’t: sequence your way to demand “conversion hack” your way to growth or pipeline-wash your way through a tougher market Level Equity's new report makes the trend hard to ignore: Marketing spend allocated to TOF + brand is up +29% YoY Enterprise companies ($50k+ ASP) are allocating ~30% of budget up-funnel Why? Because the bottom of the funnel is full of diminishing returns. The top is where the leverage is. And the proof isn’t subtle: Companies running multi-channel nurture saw: +58% more website traffic +53% higher Lead → MQL conversion +40% higher website conversion That’s not a tactic. That’s a system compounding. Now here’s the nuance most people miss: 29% of companies are generating pipeline from LLM-driven efforts… …but organic search and tradeshows are still dominant. Translation: AI isn’t “replacing” GTM. AI is becoming the execution layer that makes your GTM system actually run. The winners won’t be the teams with the most AI tools. They’ll be the teams with the best AI-enabled GTM system: Humans-in-the-loop content that earns attention (not spam) AI-driven enrichment + prioritization (so reps stop chasing junk) Workflow automation across nurture + follow-up (so nothing leaks) Multi-channel orchestration (so buyers feel you everywhere) Clean attribution (so you stop guessing what worked) That’s the stack. So the real question for 2026 isn’t “what AI tool are we buying?” It’s: Are we building demand… or trying to squeeze another 2% out of a funnel that’s already dry? Full report in the comments.

Your AI strategy is probably failing Not because of the technology Because you’re treating AI like a shiny new tool instead of a new way to run your business Over the last 3–4 months I’ve seen the same pattern across rev orgs: → “Did you see this AI tool?” → “We’re testing 7 different platforms.” → “We’re building an AI strategy.” Translation: lots of curiosity, almost zero operational change. That’s the AI paradox. Everyone’s experimenting. Almost no one is actually changing how work gets done. If you want AI to drive real results in 2026, do these 4 things: → 1. Start with ONE workflow Stop trying to roll AI out to the entire team. Pick one process. Prospect research. Call summaries. Proposal creation. One workflow. Done extremely well. → 2. Track a real metric If you can’t measure it, it’s just a cool demo. Time saved. Pipeline created. Win rate improvement. You need a clear before vs. after delta. → 3. Change the mindset LLMs aren’t a new tool. They’re a foundational shift in how problems get solved. It’s not “here’s a new app.” It’s “we used to do this task in 6 steps…now it’s done in 30 seconds.” → 4. Deploy and reinforce Most AI initiatives die here. Leaders announce the tool. Everyone nods. Two weeks later… nobody uses it. Adoption requires accountability and reinforcement. This is how the job is done now. The companies that win with AI in 2026 won’t be the ones testing the most tools. They’ll be the ones that systematically redesign how work happens. Curious… What’s ONE workflow in your org that AI could completely change right now?

A VP of Sales told me last week they’re “not ready for AI” IT has most tools blocked Too risky. Too early. Too messy. I hear this constantly Not from bad companies From cautious ones that mistake hesitation for strategy The usual objections roll out fast: → “We need to protect our brand voice.” → “What if it hallucinates?” → “Our customers want a human touch.” Cool Your customers actually want speed and relevance AI gives you both Here’s what their competitors are doing instead: AI does the research. Humans do the thinking. AI drafts the message. Humans sharpen the insight. AI handles admin. Humans have better conversations. No one is replacing sellers They’re removing the garbage work that makes sellers sound robotic in the first place. While this leadership team debates risk, their reps are still spending 30–40% of their week on research, data entry, and CRM hygiene. Meanwhile, competitors are walking into calls prepared, curious, and actually present. The irony? The teams “worried about sounding robotic” are the ones forcing reps into templated outreach and rushed conversations. The window for “getting ready” closed months ago. Stop asking if you’re ready for AI Start asking how long you can compete without it

Your 2026 GTM hiring plan is probably broken already Not because you’re under-hiring Because you’re hiring for the wrong signals Degrees. Titles. “10+ years experience.” None of those predict performance anymore What does? → Adaptability beats experience (92% of hiring managers agree) → Skills-based hiring is 5x more predictive than degrees → T-shaped operators outperform siloed specialists → Fractional leaders are scaling faster than full-time org charts → And the fastest-growing GTM role? GTM Engineers + AI-fluent operators AI didn’t just change how GTM teams execute. It changed who actually wins in those roles. The best teams aren’t hiring resumes. They’re hiring systems thinkers who can learn fast, work cross-functionally, and operate with AI as a baseline. That’s why we broke down the 5 GTM hiring trends shaping 2026 - with real data and what we’re seeing inside high-growth revenue orgs at Skaled. If your hiring model still looks like 2021, you’re already late Blog link in the comments Which of these shifts is your team actually built for right now?

Most companies talking about their “AI strategy” are lying to themselves They’re not building a strategy They’re piling AI on top of an already messy GTM system and calling it innovation. Hard truth: Stop pretending you’re going to build this entirely in-house. Most companies can’t. Had a great conversation on The Cheat Code & Friends Podcast with Justin Gray, Josh Wagner, and Sean Kester about why this keeps happening. Here’s the real issue. 1. AI is moving too fast for your internal team to keep up. Most companies still haven’t fully figured out the RevTech stack they already own. Now leadership wants agents, automation, copilots, orchestration, prompts, data layers, governance, enablement, and ROI tracking. That’s not a strategy. That’s executive fantasy. The playbook is changing constantly. If your team is learning it only between internal meetings and fire drills, you are already behind. 2. Your ops team does not have the bandwidth. You hire a RevOps lead. Maybe an AI ops person. Maybe you dump it on sales enablement or marketing ops. Then what happens? Day one: “Can you fix routing?” “Can you clean up Salesforce?” “Can you stand up this dashboard?” “Can you evaluate 4 AI tools?” “Can you build automations?” “Can you train the team too?” So now the person who was supposed to help architect the future is buried doing tickets and patchwork. That is how companies become experts in last quarter’s technology. And that’s the trap: They think they’re building internal capability. What they’re actually building is internal lag. If you really want to do this in-house, two things have to be true: Your team needs actual protected bandwidth to study what’s changing outside the company. And someone needs to own relentless experimentation, not “we’ll test some stuff when things slow down.” Because things are not slowing down. If you don’t have both, you are not building an AI strategy. You are reacting. Slowly. Had a great time unpacking this with Justin, Josh, and Sean on The Cheat Code & Friends Podcast. The episode dropped today. Full link is in the comments.

Most sales managers are about to have a very uncomfortable experience with AI Because for the first time… We can actually see if you’re coaching or just talking A VP of Sales told me last week: “AI is finally going to fix our coaching problem.” I asked him one question. “What exactly are your managers coaching to today?” Silence. Because here’s the uncomfortable truth. AI won’t fix bad managers. It’s going to expose them. For years a lot of managers survived on… vibes. Pipeline reviews based on gut feel. 1:1s that turn into therapy sessions. Forecasts built on rep optimism. “Feels like a $200K deal.” “Prospect sounded excited.” “Good momentum.” None of that is coaching. That’s professional guessing. Now AI shows you everything. → Stage conversion rates → Deal slippage patterns → Talk-to-listen ratios → Follow-up gaps → Pipeline with zero quantified pain The data is sitting right there. Which means managers can’t hide anymore. If AI shows: → Rep A converts 12% from Stage 2 → 3 → Rep B loses every deal without multi-threading → 40% of pipeline has no economic impact …and the 1:1 still sounds like: “So… how are things going?” That’s not a tools problem. That’s a manager problem. Here’s the shift happening right now: Average reps are getting better because of AI. Average managers are getting exposed because of AI. Because once the data is clear, two things become obvious fast: → Who can diagnose → Who can’t The future of sales leadership isn’t about being the most experienced person in the room. It’s about being the best operator in a data-rich environment. So here’s the real question for revenue leaders: If you turned full visibility on tomorrow… Would your managers level up? Or get exposed? If you're thinking about what this shift means for your team, let’s chat through it - DM me or comment SHIFT and we’ll find time

Two Sundays ago, a VP of Sales I know was on his laptop at his kid’s soccer game. Not because he wanted to be. Because it was “forecast week.” He wasn’t coaching. He wasn’t thinking about strategy. He was chasing grown adults for CRM updates, cleaning up pipeline, and rebuilding the same forecast slides everyone pretends to trust. That’s the job now. And it’s insane. 60% of Sales Manager time is getting burned. Not on revenue. Not on coaching. On admin, pipeline clean-up, and babysitting updates. Most managers are spending 15–20 hours a week doing stuff that shouldn’t exist: Manually reviewing deals like a detective Writing recap emails no one reads Building forecast decks that go stale in 24 hours Guessing which reps actually need coaching Sitting through 1:1s with vibes… not data That’s 800+ hours a year per manager. At a $150K salary, that’s roughly $72K of leadership time lit on fire. And the worst part? We’ve all just accepted it as “part of the job.” It’s not. It’s a broken system we normalized. Here’s what’s changed: AI can remove 40–60% of that load in 30 days—without a massive “transformation project.” What it looks like in the real world 1) Pipeline Reviews (no more deal detective work) - we have an AI Agent that reviews 100% of deals the EXACT way you would AI flags deals that are fake or drifting: -No real number / no quantified pain -No access to buying committee -Timeline slipping (but not reflected) -Stage aging that doesn’t match activity -Managers stop interrogating reps and start making decisions. 2) Coaching Prep (real coaching, not “how’s it going?”) Instead of showing up blind, AI shows up with receipts: -Conversion rates by stage -Talk-to-listen ratios -Stalled deal patterns -Deal risk drivers by rep -Now coaching is 30 minutes of impact, not 90 minutes of wandering. 3) Forecasting (data, not rep emotion) AI analyzes: -historical close rates -velocity + stage aging -activity quality -prior slippage patterns No more optimism. No more “I feel good about this one.” Just reality. One client freed up 12 hours per manager per week in 6 weeks. They didn’t hire more reps. They increased coaching capacity. Revenue followed. So if your managers are still spending Sundays updating Salesforce… You don’t have a talent problem. You have a systems problem.

80% of reps are “using AI" Only 13% are actually building agents That gap is about to decide who hits quota in 2026 Most sellers think typing “write me a prospecting email” into ChatGPT makes them AI-enabled. It doesn’t There are 5 levels of AI proficiency in frontline sales: → Level 1: Ad Hoc User – random prompts, generic outputs → Level 2: Skilled Prompter – structured inputs, consistent drafts → Level 3: Assistant Builder – custom GPTs trained on playbooks → Level 4: Agent Builder – automated workflows across CRM, Slack, email → Level 5: AI Multiplier – scales it across the entire team Levels 1-3 are personal productivity. Levels 4-5 change revenue. Teams using AI effectively are seeing a 47% productivity lift and saving 12 hours per rep, per week. That’s not “cool tech.” That’s an extra day and a half of selling time. Here’s the problem. Most reps are stuck at Level 1 pretending they’re advanced because they use ChatGPT twice a day. Meanwhile, the top 10% are building systems that: → Auto-prep meetings the second a Calendly link is booked → Draft objection responses trained on their exact pricing model → Enrich accounts and generate tailored outreach before they log into Salesforce That’s the difference between dabbling and dominating And this isn’t about coding Low-code tools + the right frameworks = leverage most teams don’t even realize is possible. Next week, we’re running our AI Sales Certification for reps and managers. Hands-on build sessions that move you from Ad Hoc User → Assistant Builder → Agent-level thinking. If you’re serious about future-proofing your career (or your team), this is the skill. Link is in the comments - DM me and I'll throw you a discount code

You’re losing deals you should be winning Because your sales reps are still doing everything manually… The future of selling is AI-assisted selling Not just for prospecting The entire revenue workflow From the first outbound message all the way to growing the account. Here’s what that looks like now: → Account research generated in seconds → AI builds personalized outbound messaging → Snippets pushed directly to email or your sales engagement platform → Discovery prep built instantly before the meeting → Every deal insight stored in one place Then the real magic happens. After the call: → Transcript analyzed automatically → Deal strategy generated → Risks and threats surfaced → Follow-up email written for you No scrambling for notes. No forgetting key details. No deals slipping through the cracks. This is exactly what tools like Journey AI are doing right now. One workspace. AI assisting you through the entire deal cycle. Which raises a real question for sales teams in 2026: Why are reps still juggling 10 tools and 50 manual steps to run a deal? That’s how opportunities get missed. That’s how deals get lost. The teams winning right now are using AI to run the entire sales motion faster and smarter. If you want to see what that looks like… Check out Journey AI - link in comments

I was on a call with a CRO who told me, “We’ve made AI our #1 initiative for 2026.” Board bought in. Budget approved. Internal task force assembled. So I asked him: “What does your AI strategy actually increase?” Started talking about tools. Mentioned copilots. Mentioned automation. Mentioned a few pilots. But couldn’t answer the question. That’s the problem. Most GTM teams don’t lack AI. They lack a sentence. “In 2026, our AI strategy will increase ______ by ______.” Pipeline? Win rate? Rep capacity? Cycle time? If you can’t finish that sentence, you don’t have a strategy. You have activity. That’s why so many teams are stuck in: → endless experimentation → pilot purgatory → isolated wins that never compound AI is being layered on top of GTM. It’s not embedded inside it. So we built a 2026 AI GTM Playbook that forces clarity. It’s called PLAN. P → Prioritize what matters Identify the AI linchpin. The one workflow where improvement compounds across revenue. Not 10 experiments. One lever. L → Launch fast Speed > perfection. You don’t design AI in slides. You refine it in motion. A → Drive adoption If sellers don’t use it in real deals, it doesn’t exist. Adoption is behavior change. Not enablement decks. N → Normalize AI in GTM This is where scale happens. AI becomes infrastructure. Reviewed alongside pipeline. Owned like any other revenue lever. AI doesn’t create leverage by itself. It amplifies whatever system you already run. Strong system? It compounds. Weak system? It exposes you. If you’re a GTM leader and you can’t clearly define what AI is supposed to increase… Book time with me. I’ll help you identify the one workflow to start with, what to kill, and how to get to measurable impact in the first 90 days Comment PLAN and I’ll DM you the framework, or just message me “PLAN” and we’ll set up a quick working session.

Your hiring process is about to get disrupted Not by recruiters By AI This week on The AI Powered Seller, I sat down with Krissy Manzano, CEO & Founder of Blueprint Expansion, to break down how AI is completely reshaping recruiting and hiring. And most sales leaders aren’t ready. We talked about: → AI screening candidates before a human ever looks at a resume → How candidates are using AI to game your interview process → Why traditional hiring signals are becoming useless → The risk of building teams that look great on paper… but can’t actually sell Here’s what actually happens in most companies: A candidate interviews. Then 4–6 execs sit in a room and say: “Yeah, they were solid.” “I liked them.” “I don’t know… something felt off.” That’s not a hiring process. That’s vibes. Krissy breaks down how AI, when used inside a GOOD, structured interview process, eliminates that ambiguity. → Standardized scoring based on competencies → Pattern recognition across top performers → Real data instead of memory-based opinions → Clear signals on adaptability and AI fluency AI shouldn’t replace human judgment. It should sharpen it. Because in an AI-first sales world, hiring “pretty good” reps won’t cut it. This episode drops TOMORROW, link in comments

Last night at 8:47pm about 10,000 sellers did the same thing Finally done with calls, and instead of shutting the laptop they are staring at a blank follow-up email thinking: “Okay… what do I even say that doesn’t sound like every other rep on earth?” So they do what everyone does now: They paste the call notes into ChatGPT, get a clean email in 12 seconds, hit send, and feel productive. Next morning? No reply. Deal still stalled. Pipeline still ehh Same anxiety, just faster. That’s the AI productivity trap sales reps are walking into. AI is helping reps move faster… at the exact work that doesn’t move revenue. Yes: Emails are faster Proposals are faster Recaps are cleaner But if you’re honest… your number didn’t change and if AI just helps you do the “rep busywork” faster, you don’t win more deals. You just become a more efficient version of average. Here’s what real AI leverage looks like for a rep: 1) It tells you what to do next — not just what to write AI flags the real risk: Use RepGPT inside JourneyAI for free and you can see what I mean (just give it a call transcript) No quantified business problem No power / no access to the buying committee No timeline tied to a business event No mutual plan Stage doesn’t match behavior Now you’re not “following up” and instead you are running a deal. 2) It upgrades discovery — so you stop losing to “no decision” Instead of “Any questions?” AI arms you with: the 3 assumptions the buyer is making that are likely wrong the CFO metric you need to anchor on (margin, cash, risk, payback) the one uncomfortable question that exposes whether this is real That’s how deals actually move. 3) It helps you qualify out faster (and you feel richer) You know the deals I mean: Great conversations… “lots of interest”… then ghosted. AI helps you spot it early and cut it: less pipeline, more wins. One client reduced pipeline volume by 28%. Revenue went up 19%. That’s productivity. Not more activity. Better decisions. So here’s the real question for reps: Are you using AI to write better emails…or to win the deal you’re about to lose?

A VP of Sales told me last week they’re “not ready for AI” IT has most tools blocked Too risky. Too early. Too messy. I hear this constantly Not from bad companies From cautious ones that mistake hesitation for strategy The usual objections roll out fast: → “We need to protect our brand voice.” → “What if it hallucinates?” → “Our customers want a human touch.” Cool Your customers actually want speed and relevance AI gives you both Here’s what their competitors are doing instead: AI does the research. Humans do the thinking. AI drafts the message. Humans sharpen the insight. AI handles admin. Humans have better conversations. No one is replacing sellers They’re removing the garbage work that makes sellers sound robotic in the first place. While this leadership team debates risk, their reps are still spending 30–40% of their week on research, data entry, and CRM hygiene. Meanwhile, competitors are walking into calls prepared, curious, and actually present. The irony? The teams “worried about sounding robotic” are the ones forcing reps into templated outreach and rushed conversations. The window for “getting ready” closed months ago. Stop asking if you’re ready for AI Start asking how long you can compete without it

I was on a call with a CRO who told me, “We’ve made AI our #1 initiative for 2026.” Board bought in. Budget approved. Internal task force assembled. So I asked him: “What does your AI strategy actually increase?” Started talking about tools. Mentioned copilots. Mentioned automation. Mentioned a few pilots. But couldn’t answer the question. That’s the problem. Most GTM teams don’t lack AI. They lack a sentence. “In 2026, our AI strategy will increase ______ by ______.” Pipeline? Win rate? Rep capacity? Cycle time? If you can’t finish that sentence, you don’t have a strategy. You have activity. That’s why so many teams are stuck in: → endless experimentation → pilot purgatory → isolated wins that never compound AI is being layered on top of GTM. It’s not embedded inside it. So we built a 2026 AI GTM Playbook that forces clarity. It’s called PLAN. P → Prioritize what matters Identify the AI linchpin. The one workflow where improvement compounds across revenue. Not 10 experiments. One lever. L → Launch fast Speed > perfection. You don’t design AI in slides. You refine it in motion. A → Drive adoption If sellers don’t use it in real deals, it doesn’t exist. Adoption is behavior change. Not enablement decks. N → Normalize AI in GTM This is where scale happens. AI becomes infrastructure. Reviewed alongside pipeline. Owned like any other revenue lever. AI doesn’t create leverage by itself. It amplifies whatever system you already run. Strong system? It compounds. Weak system? It exposes you. If you’re a GTM leader and you can’t clearly define what AI is supposed to increase… Book time with me. I’ll help you identify the one workflow to start with, what to kill, and how to get to measurable impact in the first 90 days Comment PLAN and I’ll DM you the framework, or just message me “PLAN” and we’ll set up a quick working session.

Most companies still onboard reps like it’s 2012. If a new rep needs 9–12 months to “get it,” you don’t have an onboarding plan… you have a revenue leak. Here’s the real shift we’re seeing right now: AI as an Onboarding Accelerator. Not to replace managers. To compress time-to-competence. In this clip from the AI Powered Seller Podcast, I break down what it looks like in practice: → ICP + Persona mastery in Week 1 Reps can role-play a VP of Finance 25 times before their second Friday. They learn what each persona actually cares about without risking live deals. → Positioning without the 53-feature brain dump AI trains reps to lead with the 3 messages that matter for that industry…not recite a product sheet. → Objection “at-bats” before it counts Every team has 3–5 objections that show up in almost every deal. Why are reps hearing them for the first time on real opportunities? Or in some terrible role play with someone who ALSO doesn’t know what these people do? We’re seeing teams cut ramp time 30–50%. If your ramp is 6 months, what happens when it’s 3? If you’re hiring 10 reps this year…the math real. That’s not an enablement win. That’s revenue acceleration. I put together a deck: Top 5 AI ROI Use Cases for Frontline Sellers (it’s getting shared like crazy). Comment “ROI” and I’ll send it over. And if you want the full breakdown, the full AI Powered Seller episode is linked in the comments. Why are we still accepting a year for reps to “figure it out”?

There’s one word sales reps love more than anything Leverage We talk about it constantly “Leverage partners” “Leverage marketing" “Leverage our network" “Leverage our champions" When I was a frontline seller I was obsessed with it. How do I close more deals with less effort? Find a partner. Find a channel. Find a shortcut. Always thinking about leverage. And now we have the biggest leverage tool ever created. AI. But most sellers are using it for things like: → Writing an email → Summarizing a document → Cleaning up a LinkedIn post Sweet. Meanwhile the real leverage is sitting right in front of you. Stop entering data into your CRM. Seriously Why are sellers still doing this? Finish a call… Open Salesforce… Write notes… Update fields… Send follow-ups… That’s not selling. That’s admin work pretending to be selling. The leverage move is simple: → Call recording gets pulled automatically → CRM fields update automatically → Slack notifications sent automatically → Follow-up email drafted automatically All from the call transcript. No typing. No copying notes. No wasting 30 minutes after every meeting. And yes… your CRM data probably sucks right now. But you know why? Because humans are terrible at updating CRMs. AI isn’t. So if you’re serious about leverage in 2026… Stop talking about it. And start automating the work that isn’t actually selling.

Level Equity just dropped one of the most useful GTM benchmark reports I’ve seen this year. Their 2026 GTM Insights Report pulls data from 34 growth-stage companies across their portfolio. And the headline? Pipeline → Closed Won conversion is up +37% YoY. Overall win rates improved +33% YoY. Enterprise win rates (>$50k ASP) jumped +65%. That’s not incremental. That’s structural improvement. But here’s the part most people will gloss over: Outbound teams had to target 74% more prospects to book a meeting than in 2023. More volume. More activity. More AI-assisted outreach. So what separated the top performers? According to the data: → Centralized prospect lists = 2.8X higher meeting conversion → 200+ dials/week = 3.4X higher booking conversion → AI-driven enrichment = 2X higher booking conversion AI didn’t replace fundamentals. It amplified them. That’s the big takeaway from Level Equity’s data. AI is increasing outbound efficiency. But the companies winning are the ones who tightened targeting, cleaned data, enforced standards, and embedded AI into workflow. Not just “gave reps ChatGPT.” You don’t fix your funnel math? You just automate inefficiency faster. Major credit to Level Equity and the NextLevel Operations team for putting real numbers behind what most of the market is speculating about. If you’re running GTM between $10M–$100M ARR, this report is worth your time. Question for you: Did your conversion rates improve because of better strategy… Or just more activity? Read the full report here: https://lnkd.in/e7MJ-CWD

“Paying your reps to ‘earn their stripes’ is just paying them to waste time” For decades, sales leaders believed reps needed to “grind” through admin work to build discipline Updating CRMs. Writing manual follow-ups. Prepping for calls by scrolling LinkedIn and guessing buyer intent. That mindset is officially dead → 60–70% of a seller’s day is now automatable with AI (This is McKinsey not me so I don’t want to hear the “Did this really happen comments”) → The average rep spends only 35% of their time in actual conversations. → AI-powered sellers are reclaiming 11–12 hours every week to focus on selling, not spreadsheets. Reps who still think “manual means meaningful” are falling behind while others are closing more deals in less time simply because they’ve handed off the busywork to AI Assistants. So ask yourself: Are you buying effort or outcomes? 👉 See how fast you can deploy AI Assistants inside your org: meetjourney.ai

If I talk to one more leader who brings up Clay or Gong and says “Oh yeah…we are all over AI” I might lose it Both are great purchases…but they aren’t an AI Strategy Step zero looks like this: We buy tools that solve 1-2 parts of the 100 AI could solve ChatGPT writing emails Random prompts getting tested “AI-powered” tools getting bought Reps left to “figure it out” That’s not a strategy. That’s experimentation. And here’s the reality: almost everyone is still there. Enterprise. Mid-market. VC-backed. PE-backed. Most teams are stuck at step zero because they never answer one question: What revenue outcome is AI supposed to move? Because if you can’t measure it in: ramp time pipeline quality conversion rates cycle time win rate manager coaching effectiveness …it’s not an AI strategy. It’s a productivity toy. Here’s Step One Pick ONE revenue outcome and operationalize ONE workflow that hits it — with a baseline and a scoreboard. Not 12 use cases. Not 50 prompts. One measurable workflow. One adoption target. One metric that moves. Here are 3 Step One options that actually drive ROI: Ramp Time (fastest win) AI role-plays + objection practice + persona training so reps get “at-bats” before real deals. Metric: time-to-first-meeting, time-to-first-oppty, time-to-first-closed-won. Pipeline Quality (highest leverage) AI enforces qualification standards (MEDDICC-lite, ICP fit, deal risks) and flags junk early. Metric: stage conversion, % opps that advance, pipeline slippage rate. Manager Coaching (quiet multiplier) AI turns calls + CRM into coaching prompts and “next best coaching action” each week. Metric: coaching frequency, rep improvement trends, forecast accuracy. That’s Step One: stop “doing AI” and start building a measurable revenue workflow. That’s why I built a deck: Top 5 AI ROI Use Cases for Frontline Leaders It’s getting shared because it’s not theory — it’s operational. Workflows tied to revenue outcomes. This week’s episode of AI Powered Seller breaks down all 5 use cases — what to implement, how to measure, and how to roll it out without chaos. If you want the deck, comment ROI and I’ll send it.

Most sales managers are about to have a very uncomfortable experience with AI Because for the first time… We can actually see if you’re coaching or just talking A VP of Sales told me last week: “AI is finally going to fix our coaching problem.” I asked him one question. “What exactly are your managers coaching to today?” Silence. Because here’s the uncomfortable truth. AI won’t fix bad managers. It’s going to expose them. For years a lot of managers survived on… vibes. Pipeline reviews based on gut feel. 1:1s that turn into therapy sessions. Forecasts built on rep optimism. “Feels like a $200K deal.” “Prospect sounded excited.” “Good momentum.” None of that is coaching. That’s professional guessing. Now AI shows you everything. → Stage conversion rates → Deal slippage patterns → Talk-to-listen ratios → Follow-up gaps → Pipeline with zero quantified pain The data is sitting right there. Which means managers can’t hide anymore. If AI shows: → Rep A converts 12% from Stage 2 → 3 → Rep B loses every deal without multi-threading → 40% of pipeline has no economic impact …and the 1:1 still sounds like: “So… how are things going?” That’s not a tools problem. That’s a manager problem. Here’s the shift happening right now: Average reps are getting better because of AI. Average managers are getting exposed because of AI. Because once the data is clear, two things become obvious fast: → Who can diagnose → Who can’t The future of sales leadership isn’t about being the most experienced person in the room. It’s about being the best operator in a data-rich environment. So here’s the real question for revenue leaders: If you turned full visibility on tomorrow… Would your managers level up? Or get exposed? If you're thinking about what this shift means for your team, let’s chat through it - DM me or comment SHIFT and we’ll find time

I started my last software evaluation exactly like this “Before we start…here’s how you compare to your top 3 competitors, what we think fair pricing is based on public comps, and the ROI model we’ll use internally. Tell me where we’re wrong.” I wasn’t being arrogant. I was doing what 30-40% of buyers are doing today already and just not telling reps. I built it in 10 minutes with JourneyAI Meanwhile, the rep was probably toggling between LinkedIn and Salesforce like it’s 2018… five minutes before the meeting. Then had prepped a bunch of MEDDPICCDPICAPECIPC qualification questions and was completely unpreapred. Here’s the uncomfortable truth: Your buyer often knows more about your product than your rep does. Gen AI made that possible. B2B buyers aren’t “learning from sales” anymore—they’re arriving pre-educated: 70%+ prefer self-serve research before talking to sales 80%+ have mostly defined requirements before the first call They’re showing up with: → competitive comparisons → pricing benchmarks → ROI models → negotiation strategies And it’s not because they’re brilliant. It’s because they have a tireless analyst in their pocket now. The old advantage in sales was information asymmetry. That’s dead. So what’s the new edge? Judgment. Diagnosis. Reframing. Quantifying impact in CFO language. If your seller can’t: quantify the cost of inaction tie value to a CFO-level metric (cash flow, margin, payback period, risk) reframe the problem beyond the buyer’s initial “requirements” …then they’re not leading. They’re just confirming what the buyer already researched. AI is upgrading average buyers every day. Is it upgrading your reps… or exposing them?

Paying reps to “earn their stripes” is just paying them to waste time For years, sales leaders confused suffering with skill Updating CRMs by hand Writing follow-ups from scratch Scrolling LinkedIn pretending it’s “research.” That logic made sense in 2005. It’s indefensible in 2026. → 60–70% of a seller’s day is now automatable with AI. That’s McKinsey, not vibes. → The average rep spends ~35% of their time actually talking to buyers. → AI-powered sellers are getting back 11–12 hours a week by dumping the busywork. Here’s the uncomfortable truth: Manual work doesn’t build grit. It builds inefficiency. The reps winning right now aren’t working harder They’re delegating faster - to AI assistants that don’t forget, don’t complain, and don’t burn selling hours on spreadsheets. While some teams still worship “effort,” others are closing more deals with fewer calls and shorter cycles. So be honest: Are you paying for activity… or paying for results?

“If someone can game your interview with AI, your interview process sucks.” Tune in to this week's episode of AI Powered Seller with CEO & Founder of Blueprint Expansion Krissy Manzano. Now, read that again If a candidate can use ChatGPT to: → Script perfect answers → Anticipate your questions → Sound strategic for 45 minutes And you can’t tell… You’re not assessing skill. You’re rewarding rehearsal. Most sales interviews are predictable. “Tell me about a time…” “What’s your biggest weakness?” AI has already prepped them. Then the exec team debrief sounds like this: “I liked them.” “Good energy.” “Seems sharp.” That’s not a hiring system. Krissy breaks down how to build an interview process that tests real thinking - not memorized answers. If AI can beat your hiring process, what does that say about your standards? Episode drops TODAY. Subscribe to the pod in the comments Would your interview hold up against AI?

2025 made one thing clear: AI tools aren’t the problem. Lack of structure is. So we built an AI Certification that doesn’t start with prompts - it starts with how revenue teams actually work. Colin Van Exel joins the AI-Powered Seller pod to talk about the value he got from the course. The Skaled AI Certification is designed to help reps and managers: -Build AI confidence from the ground up -Learn best practices before advanced workflows -Apply AI directly to real sales motions -Move from experimentation to execution — fast This isn’t “watch a demo and figure it out later.” It’s structured, paced, and built for real-world adoption. Next cohort: February 19 – March 5 Early bird pricing ends February 5 Reps: https://lnkd.in/g5vjXdEk Managers: https://lnkd.in/gsuQVGCT DM us for team pricing AI isn’t the future of revenue. Execution is. Pumped for this course!

81% of sales teams are “using AI" Only 26% have scaled it to real ROI That gap should bother you Because it means most companies aren’t running AI They’re running pilots Board decks say “AI-powered.” Reps are still doing the same work. Revenue hasn’t moved. That’s not an experimentation problem That’s a readiness problem AI GTM readiness isn’t about buying tools It’s about whether your organization can actually absorb and operationalize them. Here’s what real readiness looks like: → You’ve defined the exact revenue problem AI is solving → Your data is clean enough to trust → Sales, RevOps, Marketing are aligned → Someone owns the rollout → Success is tied to pipeline, CAC, cycle time, or rep capacity If you can’t clearly answer those? You’re not ready. And that’s why 95% of AI pilots fail. Most teams make one of five mistakes: They buy tools before defining the use case They wait for “perfect data” and never start They ignore bad data and automate garbage They launch pilots with no path to scale They hope AI will fix a broken sales process AI is a multiplier. If your GTM motion is messy, AI makes it messier faster. If your data is unreliable, AI spreads bad decisions at scale. If leadership isn’t aligned, adoption dies quietly. Here’s the uncomfortable reality: Executives drive 41% of successful AI adoption. Individual contributors drive just 14%. This is a leadership issue. Not a tooling issue. The companies actually winning with AI did three things first: → Cleaned up “good enough” data (not perfect, usable) → Picked one high-leverage use case tied to revenue → Assigned a real owner with authority to drive adoption They didn’t try to automate everything. They operationalized one thing well. Then scaled. AI is no longer optional in GTM. But neither is discipline. So before you ask, “Which AI tool should we add?” Ask this: Is our GTM engine ready to scale intelligence… Or are we about to automate dysfunction? I’ve linked our most recent AI GTM Playbook in the comments for you, check it out and let me know what you think

Your frontline managers are wasting 60% of their week on non-coaching work So yeah… your “sales playbook” isn’t the problem. Your manager operating system is. I’m giving away my Frontline Manager Playbook as a slide deck you can steal and run this week. It’s the 5 highest-ROI AI plays that slot into how managers already work - without rebuilding your whole rhythm: → save time → standardize coaching → catch pipeline risk earlier → stop forecast from becoming story time (avg accuracy is ~75%… aka 1 in 4 commits miss) What’s inside the slides: → AI Onboarding Accelerator Ramp reps faster by turning your ICP, top win situations, landmines, and “what good looks like” into a rep-askable brain. → 1:1 Memory + Running Rep Log Eliminate recency bias. Auto-generate 1:1 agendas, track commitments, and stop coaching from resetting to zero every week. → AI Personal Development Plans (12–16 weeks) Real skill plans with weekly drills + evidence requirements… not “get better at discovery.” → LeaderGPT Package your deal framework, stage exit criteria, win stories, and pricing guardrails so every manager coaches the same way. → Pipeline Risk Radar + Forecast Coaching Green/Yellow/Red risk with “why” + “what to do next,” plus forecast questions that force evidence over vibes. Here’s one use case - if you want the full report, comment AI Leader and I’ll send it your way What’s the biggest thing stealing your managers’ time right now: coaching… or everything around coaching?

You don’t lose deals at the end of the quarter You lose them 30 - 60 days earlier… you just didn’t see it Most forecast calls are theater. Rep says it’s “strong.” Champion is “engaged.” Decision is “imminent.” Then it slips. The average forecast accuracy is 75%. That means 1 in 4 commits miss. If your CFO ran at 75% accuracy, they’d be fired. But in sales, we call it normal. The problem isn’t effort. It’s signal detection. Risk is sitting in: → Single-threaded deals → No documented decision process → Vague next steps → No financial urgency → Stage aging with no movement But no one connects the dots early enough. This is where AI should live. Not writing cold emails. Catching risk before it becomes a surprise. A simple AI risk model can: → Score every deal Green / Yellow / Red → Explain exactly why → Identify what’s missing → Suggest 3 actions this week → Draft the email to lock next steps Now your forecast isn’t story time. It’s evidence-based coaching. And when you reduce slip rate and stage aging, revenue follows. If you’re serious about tightening forecast accuracy and building a real AI risk radar inside your pipeline… Book time with me We’ll walk through your current forecast process, pressure test a few live deals, and see where the real gaps are. If it makes sense to work together, we’ll talk next steps. If it doesn’t, you’ll still leave with clarity. Drop “RISK” in the comments or DM me and let’s chat