Skaled Consulting

Most GTM teams aren’t short on AI ideas. They’re testing assistants. Building workflows. Trying automations. Looking for places AI can reduce manual work across sales, marketing, and CS. But many of these pilots never move forward for one of three reasons.

Skaled’s AI GTM Pulse data clearly shows the gap: 86% of GTM teams use AI daily or on almost every task, but only 33% have AI automations that complete GTM tasks for them. That means many teams are AI-assisted, but not AI-integrated.

Nearly every company is investing in AI and Generative AI, yet most are struggling to turn that investment into measurable impact. The disconnect is a lack of a clear AI GTM strategy.

Most sales teams are optimizing for more dials. Buyers are screening more calls than ever. That’s the disconnect. Speed-to-lead matters. But forcing conversations before buyers are ready? That’s where conversion dies. So we decided to rethink it. We’ve partnered with Orum 🥇 to help GTM teams connect faster and smarter - without burning out reps or annoying buyers. This isn’t just another dialer conversation. It’s about what happens before, during, and after the call. Why this matters: → Parallel dialing that increases live conversations without increasing headcount → AI-powered insights that help reps prioritize the right prospects → Real-time coaching and analytics to improve performance at scale Orum helps teams do what most can’t: Turn activity into actual conversations. And conversations into pipeline. We’re working with teams right now who are seeing: More connects. Better conversations. Cleaner conversion into real opportunities. Not because they’re working harder. Because they’re working the right way. If your outbound motion still relies on brute force… It’s time to rethink the system. Want to see how top teams are modernizing outbound with Orum 🥇? 👉 https://lnkd.in/gQzXa3xv)

We’re two days away from the AI GTM Pulse Debrief. Here’s what we thought was true before running the survey: 1. Most reps are already using AI daily 2. Almost none of that usage is standardized 3. Automation is still rare 4. Ownership is unclear across GTM BUT The survey has wrapped up, and we’re about to find out if we were right. This debrief is where we: 1. Validate (or challenge) these assumptions 2. Show where the gaps actually are 3. And explain what it takes to move from isolated wins → repeatable impact No recycled reports. No vendor bias. Just the data given to us from GTM professionals and leaders. If you’re responsible for revenue, you should see this. 👉 Register now (or get the recording after): https://lnkd.in/gKVte3tN

Quick question: Who owns AI inside your GTM org? RevOps? Sales? Marketing? IT? Everyone? No one? This is one of the most important (and most overlooked) questions in AI adoption. Because what we’re seeing across teams is simple: No owner = no adoption. No adoption = no scale. No scale = no ROI. And that’s exactly why initiatives stall. Not because of tools. Not because of budget. Not because of “change resistance." Because no one owns the process of turning AI into a system. We included this in the AI GTM Pulse for a reason. Ownership is one of the strongest predictors of whether AI ever impacts pipeline, conversions, and cycle time. All the things it promises. Join us on May 6th as we break down what the data actually shows. And what ownership should look like across GTM. 👉 Register for the debrief: https://lnkd.in/gKVte3tN P.S. Can’t make it? Register, and we’ll send you the recording.

When we started running the AI GTM Pulse survey. Some early signals were clear. 1️⃣ AI usage is high 2️⃣ But it’s not embedded into processes That’s the adoption gap. We say adoption is high because everyone uses AI in their day-to-day for small tasks, but can we really classify this as organizational AI adoption? From our first few questions: - Most respondents are using AI regularly - But far fewer have it built into daily GTM processes We’re just not making it past the individual usage level. Next questions dug into: successful AI pilots, who owns it, and what people are measuring. We’ll connect all of this in the webinar debrief: https://lnkd.in/gKVte3tN P.S. Can’t make it? Register, and we’ll send the full breakdown + recording if you can’t attend live.

We’re about to validate (or break) a few assumptions about AI in GTM: Common Assumption: “AI is widely adopted across teams.” Challenge: Usage is high... but mostly at the individual level. Operationalized AI is another story. Common Assumption: “We’re pretty advanced in what we’re using.” Challenge: Most teams are still one-off prompting and using one-off assistants, not creating workflows that eliminate the human in the loop. Common Assumption: “Automation is absolutely happening.” Challenge: True workflow automation is rare. Most don’t know what it looks like. Common Assumption: “AI initiatives failed because the tech wasn’t there yet.” Challenge: They fail because of ownership, enablement, and measurement. This is the pattern we’re seeing: → Individuals are ahead → Teams are inconsistent → Leadership thinks they’re further along than they are That gap is why AI projects keep stalling. Agree or disagree? We’ll find out soon at the end of our AI GTM Pulse survey. 👉 Join the debrief and see how close we are: https://lnkd.in/gKVte3tN P.S. Can’t make it? Register, and we’ll send the full breakdown + recording if you can’t attend live.

AI GTM maturity isn’t your tech stack. It’s how deeply AI is embedded into workflows, decisions, and outcomes, and most teams overestimate where they actually are. So where are you really? Vote now on the original post: https://lnkd.in/gGyNX4S7 💻 Join us on May 6th as we break down all AI GTM poll results and exactly what to do about it: Over the last 4 weeks, we’ve been running the AI GTM Pulse to separate perception from reality. What we'll cover in the debrief: https://lnkd.in/gKVte3tN → Where teams actually are vs. where they think they are → Why pilots stall and never scale → What the top teams are doing differently → How to move from experimentation to real GTM impact

The teams seeing ROI from AI did one thing differently: they tied it to an outcome from day one. Have you tied AI to at least one business outcome? Vote now on the original post: https://lnkd.in/gzxw6CzD 💻 Join us on May 6th as we break down all AI GTM poll results and exactly what to do about it: https://lnkd.in/gKVte3tN