Jake Dunlap

2025 will be the year EVERY company must implement Generative AI in their revenue org. I personally am seeing time savings for SDRs, AEs, and AMs of 20-30% per role and predict that we will see quality of sales conversations go up by 40% or more.

We have developed a new category of consulting designed to help your company see these results in just weeks/months: AI-enabled Revenue Transformation

My deep passion for the science and art of sales has fueled my journey over the past 12 years as the founder and CEO of Skaled, a globally recognized sales consulting firm. According to G2, we have outperformed industry giants like McKinsey in Management Consulting and Accenture in Sales Consulting due to our mix of strategic foresight and tactical follow through.

We’ve consistently driven a 10-20% increase in qualified opportunities, reduced sales cycles by 8%, and enhanced overall team productivity by 20% within the first 60 days of engagement. Our approach is methodical and data-driven, ensuring that every strategy we implement translates into tangible business results.

With a team of over 30 elite professionals and access to a vast network of industry experts, we specialize in aligning sales and marketing to create scalable, replicable processes. We leverage cutting-edge generative AI technology to automate critical functions like follow-up, data entry, and task management, freeing your teams to focus on what truly matters—closing deals and driving growth.

As the USA Today bestselling author of Innovative Seller, I’ve helped to shape the future of sales, offering insights and strategies that resonate with both seasoned executives and the next generation of sales leaders. My work has been recognized in the New York Times, Forbes, Inc., and HuffPost. 

Check out my YouTube: Jake Dunlap to discover over 500 sales, revenue and AI for Sales videos: bit.ly/2Qu3niE

Highlights:

	• USA Today Bestselling Author of Innovative Seller - #21 in all books
	• First VP of Sales at Glassdoor (acquired for $1.2 billion - May 2018)

Chief Executive Officer

Everyday we help companies operationalize key aspects of their sales and marketing organization.  As CEOs, Senior Execs, and Sales people, our world is changing so rapidly and keeping pace is extremely hard.  We help with both strategic and tactical support through various phases of scaling and when larger organizations are looking to re-invent or stay relevant with their current marketing and sales strategies.

Here are a few of our clients in key verticals:

Enterprise Technology and Services:
Microsoft / GLG

Hospitality/Customer Service Tech:
Duetto / NoWait (acquired by Yelp) / Stella Service

HR Tech:
LinkedIn / ADP / The Muse / Grovo / ConveyIQ / Wayup / Vettery / Paypro

Education/Legal Tech:
Newsela / Bodhala / Hire an Esquire / Allovue / Codio / Busylamp

Real Estate/Financial Services Tech:
Breather / Nestio / Honest Buildings / Hightower / Everplans / CredSimple / Captalys / ReThinkCRM

Sales Technology:
Outreach / SalesLoft / Everstring / Lead Genius / Terminus / Discoverorg / Emissary.io / Redbooks / Speek / 15Five / Honey

Advertising and PR tech:
BounceExchange / SaleMove

Services:
Dom & Tom / Betts Recruiting / Moxie / Palantir

The worst advice in sales training is also the most common "People buy from people they like."

This feel-good sound bite has probably cost more deals than any other sales myth.

Modern B2B buyers don't care if they like you.

They care if you can solve their problems.

Buyers are evaluating solutions, not salespeople. Look does it help to be both….10000%

But most will take competence over charisma all day

Here's what actually drives purchase decisions: 
➡️ Understanding their business better than the competition. 
➡️ Demonstrating clear ROI with specific, measurable outcomes. 
➡️ Proving you can implement successfully with minimal risk.
➡️ Providing social proof from similar customers. 
➡️ Making the buying process easier, not harder.

The best sellers I track aren't the most likeable. They're the most helpful.

They don't try to be your friend. They try to be your guide. 
They don't focus on building rapport. They focus on building confidence. 

Stop trying to make buyers like you. Start trying to make them trust you.

Trust comes from competence, not connection.

I partner with forward thinking B2B CEOs/CROs/CMOs to transform their business with AI-driven revenue strategies | USA Today Bestselling Author of Innovative Seller

AI training is the new “Sales Kickoff high”

Everyone attends

Everyone nods

Everyone goes back to their desk… and uses it twice.

Then they go right back to the 2018 playbook

That’s the entire game in 2026:

Curiosity + consistency

Not “which AI tool is best”

Not “what prompt should I copy/paste”

The reps (and SEs) who win are the ones who turn AI into an everyday habit… not a one-time experiment.

Here’s the part most sellers miss:

AI’s real power isn’t prospecting

It’s pre-sales

Discovery. Point of view. Tight demo narrative.

Turning a “qualification call” into a validation session.

That’s where teams close 10–30% more (and most orgs have no idea why).

Tomorrow’s episode of AI Powered Seller drops with David Maloof

We get tactical on:
→ How AI-assisted discovery actually works
→ How pre-sales + AEs stop tripping over each other and start attacking deals as a unit
→ How to use transcripts + feedback to rebuild demo stories fast
→ Why “I don’t have time” is officially dead (3 minutes is the new standard)

If your process still starts with:
“What keeps you up at night?”
…you’re already behind.

"We need better leads" is usually code for "our follow-up process is broken" or “I thought my job was to only deal with layups”

I just reviewed lead response data for a company complaining about lead quality.

Marketing was generating 200+ qualified leads per month. Sales was responding to 23% of them within 24 hours.

Speed matters more than script.

The companies with the highest lead-to-opportunity conversion rates respond within 5 minutes.

Not 5 hours. Not end of day. 5 minutes.

But most sales teams treat inbound leads like they're doing them a favor by calling back.

"I'll get to it when I finish these other calls."

Meanwhile, your competitors are already having conversations with those prospects.

The best lead response systems I've seen work like this:
Minute 1: Automated email confirmation 
Minute 2: Text message with calendar link 
Minute 5: Phone call from AE 
Hour 1: Video follow-up if no contact 
Day 1: LinkedIn connection with personal note

Your leads aren't bad. Your response time is.

Marketing can't fix what sales won't follow up on.

New year. Same playbooks.

That gap is about to get expensive.

AI isn’t moving at planning speed. It’s moving at execution speed.

AI isn’t just evolving. It’s outpacing our team’s ability to adapt.

We just dropped a deep-dive on where AI actually stands heading into 2026. What tools are saving reps time, what features are driving revenue, and where the next wave of innovation is going to hit.

Here’s what stood out to me:
⚡ 28% of sellers are already saving 5+ hours per week using GenAI like ChatGPT.

📈 Reps using AI in prospecting are booking 10% more meetings in the first month.

🧠 Adoption isn’t just about automation. It’s about skill development, onboarding, and personalized messaging at scale.

And the gap between prompting and strategy-driven GPTs is widening fast. The winners in 2026 won’t be the teams who use AI.  It’ll be the teams who train it to sell like they do.

If you’re still treating AI like a “nice to have” as you kick off the year, you’re going to get smoked by someone who turned it into a competitive advantage months ago.

Check out the full report below or DM me for the breakdown.

State of AI

Your CRM is making your sales team dumber

Every time a rep updates an opportunity stage without understanding WHY the buyer is moving forward, you're training them to be process followers instead of deal strategists

Guess what MEDDPIC or MEDDICC or whatever Ps and Cs doesn’t actually track if your people ran a good call or now which is the wild part

Most CRMs track what happened.

They don't track why it happened.

Stage: Discovery Complete ✓ 
Why they agreed to move forward… [blank]

Stage: Proposal Sent ✓ 
What convinced them we're the right solution… [blank]

Stage: Negotiation ✓ 
What competing priorities might derail this… [blank]

Your reps are updating stages like they're checking boxes 
They have no idea what's actually driving buyer behavior.

The best sales managers I know have added one custom field that changes everything 
→ Buyer motivation for this stage progression

And then we use AI to summarize and gut check this and call out threats around this as well 💥

This forces reps to document the actual driver 
Instead of "We sent a proposal," they write "CFO confirmed budget approval and wants to see ROI projections."

Instead of "Discovery complete," they write "Security team identified three technical requirements that we uniquely solve."

When reps understand buyer psychology, they can predict next steps.

Your CRM should be building deal intelligence, not just tracking activities.

Generic is officially dead

Not underperforming

Not “less effective”

Dead.

AI can already write a decent email

AI can already personalize at scale

AI can already sound like every other seller in your market

Which is exactly why AI-generated personalization won’t cut through the noise in 2026

The only thing you’ll have left is you

Your judgment

Your point of view

Your ability to make the last 10 percent better than everyone else

That’s the shift

Higher quality work

Done faster

With the human nuance as the differentiator

In my new episode of AI Powered Seller that just dropped, I review the biggest shifts we saw in 2025 and what they actually mean for selling in 2026

Not theory

Real patterns

And what to change now before everyone else catches up

I’ve got opinions on this
Interested to hear what’s working for you 👇

Check out the episode here: https://lnkd.in/gezm4brV

Your team doesn’t need more AI tools

They need AI they’ll actually use when deals are on the line

Back in November, we ran our first AI Sales Certifications for managers and reps
It worked for one simple reason

We removed the intimidation factor

Most people aren’t blocked by AI’s potential

They’re blocked by “this feels too technical for me”

One rep summed it up perfectly

They came in with “zero to little knowledge about AI agents” and still walked out confidently building real tools because complex ideas were broken down into practical, usable steps

That’s the bar

So we’re running it again

🚀 Next session starts in February

What you walk away with in 3 weeks
→ Managers clone their best thinking into AI
→ Reps build a personal AI stack that knows their product, territory, and deals
→ Research, prep, and data entry stop eating selling time
→ Coaching and deal strategy become systematized
→ No code. No technical background. No theory-only slides

This isn’t “try this prompt”

You build Custom GPTs, Gemini Gems, and AI Agents that fit how you sell

Managers close the process vs. production gap
Reps get a digital intern handling the busy work

⏰ Sign up before January 17th and get $150 off
👥 Team pricing available

Check out the links below and DM me with any questions
Managers 👉 https://lnkd.in/gsuQVGCT
Reps 👉 https://lnkd.in/g5vjXdEk

Open article: AI Sales Rep Certification | Sales Agents & Advanced GenAI by bit.ly

AI Sales Rep Certification | Sales Agents & Advanced GenAI

AI fluency won’t get you promoted in 2026

But it will get you passed over

Two VP of Sales candidates

Candidate #1
→ Big-name logos on the resume
→ Ran the “proven” sales playbook
→ Talks about tools, process, and headcount

Then I ask one question

“How are you getting 20% more revenue with the same team?”

No mention of AI

No chance

Candidate #2
→ “Here’s how AI replaces admin work”
→ “Here’s how we personalize without scaling volume”
→ “Here’s how reps perform like 2–3 people”

That’s the hire

This is what I break down on the next AI Powered Seller episode

2026 is the year the gap shows up on the org chart

Who moves up

Who stalls

And why AI fluency decides it

If a candidate doesn’t bring up AI unprompted, do you trust them to lead a team right now?

I want to hear how you’re thinking about this
Drop your take in the comments 👇

Jonathan Moss

Turning GTM into a revenue factory through recurring impact & helping GTM leaders do the same | GTM Executive leveraging AI ✨ | Keynote Speaker & Advisor | Podcast 🎙️ Host |

I created the Revenue Nervous System™ a framework for building intelligent, self-improving growth engines that learn, adapt, and scale. The IMPACT+ Framework™ is how you implement it: a structured approach for embedding AI across the revenue lifecycle and turning strategy into execution.

I help Founders, Business Executives and Go-to-Market leaders transition to AI-native GTM and architect Agentic Growth Systems that eliminate friction and turn AI into measurable performance outcomes across their business.

At Experity, I serve as EVP & GM for Patient Engagement and Care Agent, the industry's first AI-native clinical intelligence platform. We're transforming how urgent care connects with patients through a multi-agent system that automates communication, personalizes engagement, and unifies clinical + commercial workflows across 3,000+ clinics.

Think of it as the Orchestration and Routing Layer for Healthcare: where data, context, and intelligence finally work together.

Beyond Experity, I work with founders, executive teams, and AI-native startups on growth architecture, GTM execution, and multi-agent system design.

Quick professional stats:
→ 87% median growth rate across all of my roles
→ $1B+ capital raised across portfolios
→ Scaled revenue $0 → $15B
→ Backed by Sequoia, Lightspeed, GTCR, Warburg Pincus, SoftBank

Core expertise: Revenue Nervous System™ | IMPACT+ Framework™ | Agentic AI Growth Strategy | AI-Native GTM | Patient Experience & Healthcare AI

Executive Member

2.5 million patient conversations in 60 days. Not over a year. Not projected. Done. 𝗪𝗲 𝗮𝗿𝗲 𝗵𝗶𝗿𝗶𝗻𝗴 𝗮 𝘁𝗲𝗮𝗺!
 
Care Agent just crossed that mark....1M+ users, 2,000+ clinics....and we're still in the opening act.
 
Here's what nobody talks about in healthcare AI: Everyone's building copilots. We went after something different.
 
The 60% of staff time lost to phone tag. Manual workflows. Printing paper that goes straight into the recycling bin.
 
When you see that same pattern across thousands of clinics and millions of patient visits? It stops being a local problem. It's an industry design flaw.
 
So we built the solution. 
 
𝗡𝗼𝘄 𝘄𝗲'𝗿𝗲 𝗵𝗶𝗿𝗶𝗻𝗴 𝗼𝘂𝗿 𝗳𝗶𝗿𝘀𝘁 𝘁𝘄𝗼 𝗿𝗼𝗹𝗲𝘀 𝘁𝗼 𝘀𝗰𝗮𝗹𝗲 𝗶𝘁:
 
→ 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 –  Lead acquisition and growth initiatives across current and emerging market segments
 
→ 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗔𝗰𝗰𝗼𝘂𝗻𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗿 – Drive impact and value realization across our install base through growth, retention, adoption, usage, and product feedback aligned with our customers business goals and top priorities. 
 
What makes this different:
 
You'll operate like you are building a startup, but with the resources of a platform company behind you. 

Lean team. Big mandate. Shared services across marketing, RevOps, enablement, support, etc.
 
Being AI-native in how you work isn't a nice-to-have. It's table stakes. 

You'll be selling an AI-powered future while using AI to outperform traditional approaches in your own role every day.
 
This is the fastest-growing business in our organization. One of our strategic big bets.
 
If you want to transform how 40M+ annual patient interactions happen...reducing friction for both patients and the people who care for them.. let's talk.

🚨 I am not going to answer LinkedIn DMs or Comments. Here is the assignment. 

→ Find someone in my network, that I know, that will vouch for you. 𝘜𝘯𝘭𝘦𝘴𝘴 𝘺𝘰𝘶 𝘢𝘭𝘳𝘦𝘢𝘥𝘺 𝘬𝘯𝘰𝘸 𝘮𝘦. 
→ Have them reach out to me on your behalf as a recommendation. 
→ Include why you want to tackle this problem for the industry, how you are using AI today, and what impact your experience and skillset can make with our customers and team. 

#𝗛𝗶𝗿𝗶𝗻𝗴, #𝗥𝗲𝗰𝗿𝘂𝗶𝘁𝗺𝗲𝗻𝘁, #𝗝𝗼𝗯𝗦𝗲𝗮𝗿𝗰𝗵, #𝗖𝗮𝗿𝗲𝗲𝗿𝘀, #NowHiring

EVP @ Experity | AI-Native GTM Architect | Revenue Nervous System™ | Care Agent | Healthcare AI

Look ma I made it! 

84% of executives believe agentic AI will transform their business.

Only 5% have defined success metrics for it.

Harvard Business Review just dropped their agentic AI research—623 executives surveyed on expectations, readiness, and results.

The gap between belief and execution is massive.

→ 74% say AI is very important to their organization 
→ Only 26% say they're effective at using it for business outcomes

That's a 48-point gap between PowerPoint strategy and operational reality.

The report also confirms what I've been saying: this isn't a technology problem.

The biggest barriers cited? 
→ Lack of talent/skills (48%) 
→ No clear roadmap (46%)

Not infrastructure. Not budget. People and strategy.

The technology works. The human systems often don't.

The winners won't have the best technology.

They'll be the ones who understood earliest that agentic AI requires reimagining processes—not just automating them.

This is not a technology project but a business transformation. 

What you don't want to do is take an existing business process and put it on a shiny new toy of a tech stack. Then all you've done is made an expensive business process.
 
I see this constantly. Companies automate broken workflows and wonder why they're not getting 10x results.
 
I use "directed autonomy"—where agents can act independently within defined parameters, but humans remain in the loop for oversight, exception handling, and learning.
 
→ For routine workflows: fully autonomous 
→ For context-dependent workflows: shared control 
→ For high-impact workflows: always a human in the loop with escalation pathways
 
The goal isn't to remove humans. It's to give them superpowers.

90% of executives expect their industry will use agentic AI.

Only 34% are actually using it today.

→ 36% achieved greater organizational productivity 
→ 35% achieved better data-driven decision making  
→ 33% achieved cost savings 
→ 26% achieved better customer experience
 
The differentiators aren't what you'd expect.
 
Leaders don't have better technology budgets. They have better clarity. 
 
Strategy integration: 13% of leaders have agentic AI fully integrated into organizational strategy vs. just 1% of laggards.
 
Success metrics: 10% of leaders have well-defined success metrics vs. 1% of laggards.
 
Workforce understanding: 66% of leaders say employees understand the value of agentic AI vs. 24% of laggards.
 
The technology works. The human systems often don't.
 
Thanks Harvard Business Review for having me.

A year ago, 80% of my AI usage went through ChatGPT.
 
Today? It's down to 10%.
 
Claude runs 60% of my workflow. Manus handles 25%. And the shift had nothing to do with which model is "smarter."
 
Here's what actually changed:
 
I stopped being a consumer. I started being a builder.
 
ChatGPT is incredible for conversations. Ask a question, get an answer, move on. It's the best consumer AI product ever made.
 
But I'm not having conversations anymore. I'm building systems.
 
With Claude, I can: 
→ Create skills that persist across every conversation (my voice, my frameworks, my preferences—always loaded) 
→ Connect to real databases through MCP servers 
→ Build and deploy actual web apps with Claude Code 
→ Execute tasks through Cowork instead of just talking about them
 
With Manus, I can: 
→ Deploy multi-agent teams that research, synthesize, and format complex deliverables 
→ Automate recurring tasks with agents that coordinate 
→ Generate presentations with proper visuals—not just text
 
The mental model shift:
 
ChatGPT = AI that answers questions 
Claude = AI that builds systems 
Manus = AI that orchestrates agents
 
The "which AI is best" debate misses the point entirely. It's like asking whether a hammer or screwdriver is the better tool.
 
The answer depends on what you're building.
 
If you're still routing 100% of your AI work through a single tool, you're probably leaving massive value on the table.
 
The question isn't "which AI should I use?"
 
It's "what am I trying to build—and which tool was designed for that?"

I have 14,000 followers on LinkedIn and I can't reach most of you.
 
That's the quiet frustration nobody talks about. 

You made a deliberate choice to follow me. 

You said "yes, I want to see this person's content." 

And LinkedIn's algorithm basically shrugged and said "cool story, here's a post from someone's click bait asking you to comment for something you rarely receive."
 
I've been creating content for years now. 

Sharing frameworks from 21 years of scaling companies. 

Breaking down AI-native GTM strategies that are actually working. 

Having real conversations about what's broken in how we build revenue systems.
 
And maybe 3-5% of you see any of it.
 
So I'm changing the model.
 
I'm moving my daily content to Substack. 

Not because LinkedIn is dead—it's still where the professional conversation happens. 

But because I want to actually reach you.
 
Here's what's shifting:
 
𝗦𝘂𝗯𝘀𝘁𝗮𝗰𝗸 → Daily content. AI news analysis that cuts through the hype. AI-Native GTM frameworks. Deeper dives on what I'm seeing across GTM, Technology, and Business. The stuff I used to post here but couldn't guarantee you'd see.
 
𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 → A couple posts a week. The highlights. The bigger takes. The conversations worth having publicly.
 
If you've found value in what I share here, I'd love to have you join me over there.
 
The newsletter is free. The content is the same me—candid, tactical, occasionally wrong in interesting ways.
 
Link is below and in the featured section.
 
And I'm genuinely curious: am I the only one feeling this? What's your experience trying to reach the people who actually chose to follow you?

Open article: J Moss | Substack by substack.com

Healthcare isn't losing patients to competitors. It's losing them to expectations.
 
My kids don't remember a world where you had to hail a cab on a street corner. Or call a hotel front desk to book a room. They tap an app. The car appears. The door unlocks.
 
They're not "channel-native"—they don't think about which website, phone number, or portal to use.
 
They're service-native. The interface IS the service.
 
Uber isn't competing with taxis on price or speed anymore. The app experience became indistinguishable from the transportation itself.
 
Same with Airbnb. The booking interface didn't just improve accommodations—it became the accommodation experience.
 
Healthcare hasn't figured this out yet.
 
We're still asking patients to: 
→ Navigate portal logins 
→ Call during "business hours" 
→ Fill out the same form five times 
→ Wait on hold just to ask a simple question
 
And then we wonder why they're frustrated.
 
The urgent care industry sees 200+ million patient visits a year across 14k+ clinics. 

What we've learned building 𝗖𝗮𝗿𝗲 𝗔𝗴𝗲𝗻𝘁 at Experity is pretty clear:
 
The future isn't omni-channel. It's no-channel.
 
Younger generations don't care 𝘩𝘰𝘸 they get care. Text, voice, chat—doesn't matter. They just want it to work. Instantly. On their terms.
 
The clinics winning right now aren't the ones adding more channels.
 
They're the ones collapsing all those channels into a single intelligent interface that adapts to the patient.
 
Not "there's an app for that."
 
"There's an interface for 𝘮𝘦."
 
What's the last healthcare experience that actually felt modern to you?

Snow day! Will be stuck here for the next 3-4 days! 

Excited to hang with the fam, sled, work with Claude Code and Cowork, and watch some movies/shows! 

Much needed after a long week.

"Can we be your Guinea pig?"
 
Those five words stopped me in my tracks.
 
We were mid-demo with Midwest Express Clinic —one of the fastest-growing urgent care operators in the Midwest.
 
I'd just shown them our Patient Engagement solution with Care Agent. 

Lab results delivered via webapp powered by a LLM. 

Discharge docs sent automatically. 

One unified chat instead of different ones that make clinics "look like scammers" (their words, not mine).
 
And before I could even finish the walkthrough, their team jumped in:
 
"How soon can we have this?"
 
Here's what struck me about the conversation.
 
They didn't ask about features first. They didn't ask about pricing first.
 
They went straight to the pain points that actually matter:
 
→ Patients calling back 24 hours after a visit asking for work notes 
→ Lab results getting lost in the shuffle 
→ Wasted time playing phone tag 
→ Higher costs without higher reimbursement leading to lower margins
 
Then they said something that reminded me why we built Care Agent in the first place:
 
"Reducing calls, improving experience for patients and staff, improving margins all would be a huge win."
 
That's it. That's the whole game.
 
Not "give us shiny AI." Not "we want a chatbot."
 
Just: help our people more time taking care of patients and us be able to run our operations more efficiently.
 
What I love about working with operators like Midwest Express is they don't need to be sold on the vision. They're living the chaos every day. They just need tools that actually work.
 
So yeah—we're building this thing together. 

Customer feedback shaping every feature. Real clinics testing real scenarios with real patients.
 
No vaporware. No press release promises. Just working software solving actual problems.
 
There's nothing better than a customer who says "we want to be first."
 
That's how you know you're building the right thing.

450+ GTM leaders signed up.
 
That should tell you something about the state of AI training right now.
 
Here's the problem: 

Most AI education is still stuck in 2023. "Intro to prompting." Generic overviews. Death by slides.
 
Meanwhile, the operators actually transforming their revenue engines? 

They're operating at a completely different speed. Building systems. Automating workflows. Shipping agents that do real work.
 
The gap is widening every month.
 
So Andy Jolls and I wanted to build something different.
 
𝗔𝗜 𝗶𝗻 𝗚𝗧𝗠 𝗦𝗰𝗵𝗼𝗼𝗹 𝗮𝘁 Pavilion launches January 21st. Hands-on-keyboard. Practical. Built for leaders who need to implement—not just understand concepts.
 
We assembled a faculty of practitioners who are actually doing this work:
 
→ Liza Adams 
→ Crystal Black 
→ Josh Carter 
→ Jonathan M Kvarfordt, MBA 
→ Ryan Staley 
→ Scott Wueschinski 
→ John Williams  
 
90-minute interactive sessions. No passive learning.
 
What we're covering:
 
• AI GTM Team Hiring & Organizing
• AI Literacy Credentialing
• AI Tools in Action (real workflows, not product demos)
• Agents: From Prompt to Autonomous Action
• Growth Strategy Design
• Recurring GTM Process Automation
• The AI-First Revenue Engine (90-day implementation plan)
• Vibe Coding 101 & 201
• State of AI in 2026
 
This isn't theory. It's the playbook.
 
Link in comments. (Pavilion members only—if you're not a member, this might be your reason to join.)
 
What's the one AI skill you wish your GTM team had built six months ago?

40 million Americans are asking ChatGPT health questions every single day.
 
Not Google. Not WebMD. ChatGPT.
 
And here's the part that should wake up every healthcare executive: 7 out of 10 of those conversations happen after clinic doors close.
 
They're telling us something we don't want to hear.
 
The healthcare system has created a massive demand vacuum. And AI just walked in to fill it.
 
Look at the data from OpenAI's report:
 
Wyoming—the least populated state—has the highest rate of health-related AI messages from "hospital deserts." 

Rural communities are sending 600,000+ health messages per week. 

Nearly 2 million weekly messages are just about insurance and billing—people trying to decode medical bills and fight claim denials.
 
This isn't WebMD symptom-checking. This is AI-assisted self-advocacy.
 
The conventional take? "AI is coming for healthcare." That misses the point entirely.
 
AI isn't replacing healthcare. It's showing up where healthcare isn't.
 
11 PM on a Tuesday when your kid has a fever. 

Saturday morning trying to understand what "copay after deductible" actually means. 

The 30-minute drive to the nearest hospital when you need answers now.
 
That's when patients turn to AI. Not because they prefer it. Because they have no other option.
 
And here's what's really happening: 66% of physicians now use AI too (up from 38% last year). 

This isn't a patient-versus-provider story. 

It's the entire healthcare ecosystem saying the current system can't meet demand.
 
OpenAI just launched ChatGPT Health—encrypted, HIPAA-aligned, connected to your actual medical records. 

They built it with 260+ physicians across 60 countries.
 
The front door to healthcare is changing. 

The question is whether we're going to fight it or redesign around it.

We are trying to help solve this for patients and providers at Experity with Care Agent! 🫡

The_AI_Patient_Ally

The Blockbuster vs. Netflix Moment for Enterprise Intelligence. 

Blockbuster had more stores. More employees. More capital.
 
None of it mattered.
 
Netflix won because they understood something Blockbuster couldn't see: the value wasn't in physical distribution. It was in knowing what you wanted to watch before you knew it yourself.
 
That same moment is happening right now in enterprise software.
 
But instead of physical vs. streaming, it's scattered knowledge vs. unified context.
 
Foundation Capital just published their thesis on this. They're calling it "AI's trillion-dollar opportunity." 

It validated the context layer of the Revenue Nervous System that I have been sharing.
 
Here's what everyone's missing:
 
Your most important data doesn't live in a database. It lives in Slack threads, deal desk calls, and the tribal knowledge passed between employees.
 
"We always give X companies an extra 10% because their procurement cycles are brutal."
 
That rule isn't in your CRM. When the person who knows it leaves, it walks out the door.
 
Foundation Capital calls this the "decision trace" problem.
 
Rules tell you what should happen. Decision traces capture what actually happened—the exceptions, overrides, and cross-system context that explain 𝘸𝘩𝘺.
 
The reasoning connecting data to action was never treated as data in the first place.
 
Here's what it looks like in practice:
 
An AI agent proposes a 20% renewal discount. Policy caps it at 10%. But the agent pulls three SEV-1 incidents from PagerDuty, an open escalation in Zendesk, and a prior thread where a VP approved a similar exception.
 
The CRM stores one fact: "20% discount."
 
A context graph captures the entire story—the policy, the cross-system data, the precedent, the approval. That's what makes it auditable. That's what makes it compound.
 
Why can't incumbents build this?
 
Salesforce and Workday prioritize current state. They know what a deal looks like now—not the reasoning that justified it.
 
Snowflake and Databricks sit in the read path, not the write path. By the time data lands there, the decision context is already gone.
 
Capturing decision traces requires being in the execution path when decisions are made. Not bolting on governance after the fact.
 
"What could you achieve if the context carried by your RevOps, DevOps, or Security Ops teams became a queryable, permanent asset?"
 
That's the trillion-dollar question.

This article is validation of the Context Layer in the Revenue Nervous System that I have been sharing. 

If you want to learn more, check out the links in the comments.

Anthropic just shipped the most important AI product since ChatGPT.
 
It's called Claude Cowork. Released Sunday. Mac only. Max subscribers only.
 
Here's what early adopters are reporting:
 
→ Taxes filed in 15 minutes (normally 40 hours) 
→ Two months of admin backlog cleared in 2 hours 
→ Gmail inbox cleaned and categorized in 10 minutes 
→ Scattered notes transformed into first-draft quarterly plans
 
This isn't "AI assistant that helps you write emails."
 
This is AI that actually does the work.
 
You give it access to a folder. 

It reads, edits, and creates files. 

It connects to your Drive, Notion, browser. 

It loops you in when it matters. 

Executes independently when it doesn't.
 
The shift is subtle but massive:
 
From AI-assisted → AI-orchestrated.
 
From "help me with this task" → "here's the task, handle it."
 
But here's what most people will miss:
 
The bottleneck isn't the tool. It's your ability to give clear instructions.
 
Most executives are terrible at this. 

We've spent careers delegating to humans who fill in the gaps. 

Who ask clarifying questions. 

Who bring context we forgot.
 
AI doesn't do that. Yet.
 
So the executives who learn to "steer" AI effectively? 

They'll operate at a completely different speed.
 
The ones who dismiss this as "another chatbot upgrade"? 

They'll wonder why competitors keep pulling ahead.
 
We're moving from "there's an app for that" to "there's an agent for me."
 
The busy work is ending. 

The question is: what will you do with the time you get back?

I will be posting more as I dive in.

𝟰𝟬 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝗽𝗲𝗼𝗽𝗹𝗲 𝗮𝘀𝗸 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝗵𝗲𝗮𝗹𝘁𝗵 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗲𝘃𝗲𝗿𝘆 𝗱𝗮𝘆.
 
Not Google. ChatGPT.
 
OpenAI just dropped their "AI as Healthcare Ally" report. The numbers stopped me mid-scroll:
 
→ 5% of all ChatGPT messages globally are healthcare-related 
→ 70% of those conversations happen outside clinic hours 
→ 580,000+ weekly messages come from "hospital deserts"
 
(Source: OpenAI, January 2026)
 
Here's what most healthcare leaders are missing—the generational math.
 
70% of all generative AI users are Gen Z or Millennials (Salesforce). 

Daily AI search usage has more than doubled in six months (HigherVisibility, August 2025).
 
These aren't edge cases. These are your patients.
 
Millennials are 24-43 now. Gen Z is 13-28. 

Combined, they're your fastest-growing patient population.
 
They grew up in the on-demand economy. 

Uber when they want a ride. 

DoorDash when they want food. 

Netflix when they want entertainment.
 
Why would they expect healthcare to be different?
 
They don't.
 
39% of Gen Z say they'd delay seeing a doctor if AI tells them their symptoms are low-risk—that's actually more than the 36% who'd book an appointment. (Mesothelioma Center/SurveyMonkey, October 2025)
 
And Gen Beta? Born 2025 onward? They won't remember a world without conversational AI.
 
We're watching patient behavior shift in real-time. 

The practices that figure this out—meeting patients where they already are—will own the next decade.
 
The ones waiting for patients to "come back" to traditional channels?
 
They'll keep wondering why acquisition costs keep climbing.
 
We are building Care Agent at Experity and working with partners to interconnect the patient journey and make it intelligent from end to end to solve the fragmented and lack of transparency that happens across the healthcare journey

Care Agent will "always be available" for the patient... meeting them where they are today and staying with them for every part of their health journey.

Anthropic released 55 pages of data on how people actually use Claude.
 
The finding that should kill the "AI is coming for your job" narrative:
 
𝟱𝟮% 𝗮𝘂𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝘃𝘀 𝟰𝟱% 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻.
 
More than half of AI usage is humans working 𝘸𝘪𝘵𝘩 AI. Not AI working 𝘪𝘯𝘴𝘵𝘦𝘢𝘥 𝘰𝘧 humans.
 
But here's what makes it interesting:
 
This ratio 𝘀𝗵𝗶𝗳𝘁𝗲𝗱 𝗯𝗮𝗰𝗸 𝘁𝗼𝘄𝗮𝗿𝗱 𝗮𝘂𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 from August.
 
As AI capabilities improved — file creation, memory, Skills — users moved toward collaborative use. Not replacement use.
 
The more sophisticated AI gets, the more we're using it as a partner.
 
This inverts the automation anxiety narrative completely.
 
Other findings that matter for business:
 
→ Headline productivity gains (1.8pp) drop to ~1.0pp when adjusted for actual success rates. Cut in half.
 
→ Complex tasks = higher speedup (12x for college-level work) BUT lower success rates (66% vs 70% for basic tasks)
 
→ AI is a force multiplier for expertise. Not a replacement. The people extracting value already know the work.
 
→ When AI handles tasks, remaining job requirements either upskill or deskill by role. Property managers upskill (AI handles admin, humans need more judgment). Travel agents deskill (AI handles complexity, humans handle routine).
 
→ Geographic adoption converging 10x faster than 20th century tech. 

Your "we'll adopt before competitors" window is closing every day.
 
Three things for GTM leaders:
 
1. Success rates cut ROI projections in half. API success is 49%. Consumer AI is 67% — with human iteration.
2. Multi-turn extends what's possible. Single prompts hit a wall at ~3.5 hours of equivalent human work. Iteration pushes it dramatically further.
3. Design for augmentation when humans are in the loop. Save automation for back-office workflows.
 
The companies that win won't chase "AI replaces everything."
 
They'll build human-AI systems:
 
• Where does AI amplify our best people?
• Where do humans catch AI's mistakes?
• Which tasks stay human because they're our moat?
 
The replacement narrative is wrong.
 
The collaboration data is in.

Your company is probably extracting 20% of the value from your AI investments.
 
Not because you picked the wrong model. Because you picked the wrong architecture.
 
Here's what I mean:
 
Microsoft's Excel agent uses Claude 4.5. Anthropic's Claude in Excel uses Claude 4.5. 

Same model. Same underlying intelligence. 

Completely different business outcomes.
 
AIG compressed business review timelines by 5x. Data accuracy jumped from 75% to over 90%. 

Norway's $1.6 trillion sovereign wealth fund saved 213,000 hours.
 
Meanwhile, most enterprises are getting... marginally better formulas.
 
The difference isn't the AI. It's how the AI was integrated.
 
Microsoft built Claude as a formula writer. Ask a question, get a VLOOKUP. 

The AI is capped at what Excel could already do—just faster.
 
Anthropic built Claude as the analyst. 

The AI actually thinks through the problem, performs the analysis, and uses Excel to display results.
 
One approach automates your existing process. 

The other replaces it with something fundamentally better.
 
This is the question every executive should be asking about their AI vendors:
 
𝗜𝘀 𝘁𝗵𝗶𝘀 𝘁𝗼𝗼𝗹 𝘂𝘀𝗶𝗻𝗴 𝗔𝗜 𝘁𝗼 𝗱𝗼 𝘁𝗵𝗲 𝘄𝗼𝗿𝗸? 

𝗢𝗿 𝘂𝘀𝗶𝗻𝗴 𝗔𝗜 𝘁𝗼 𝘄𝗿𝗶𝘁𝗲 𝗶𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗹𝗲𝗴𝗮𝗰𝘆 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝘁𝗼 𝗱𝗼 𝘁𝗵𝗲 𝘄𝗼𝗿𝗸?
 
Because that architectural choice determines whether you get 5x productivity gains or 1.2x.
 
Companies that bolt new technology onto old processes get incremental improvements. 

Companies that rebuild processes around new capabilities get exponential ones.
 
Most enterprise AI deployments right now are bolt-ons.
 
The vendors selling you "AI-powered" everything are often just routing requests to an LLM, then constraining the output to what their legacy software can handle.
 
You're paying for the model's full intelligence. You're getting a fraction of it.
 
Three questions to ask your AI vendors:
 
→ Does the AI perform the analysis, or does it write code for your existing tools to execute?
→ What's the ceiling—the AI's capability or your legacy system's capability?
→ Can you show me results from customers who rebuilt workflows vs. customers who automated existing ones?
 
The companies figuring this out now are about to create gaps their competitors can't close.

Urgent Care is evolving and with AI we have the ability to reimagine the patient journey to become connected, intelligent and always on… that’s exactly the experience patients demand. 

Come check out what we are up to and how we are tackling all of the challenges in navigating and providing healthcare today!

MORE UCC HEADLINERS ✨ 

During this main stage session, Jonathan Moss and Ian Lyman will share the latest Forrester + Experity Clinical Intelligence data and define what it takes to become an intelligent urgent care organization.

Immediately following, Aaron Weber, a stand-up comedian, Grand Ole Opry performer, and co-host of The Nateland Podcast, will bring the day of learning and networking to a fun and memorable close.

Join us in Nashville. Tickets here >> https://lnkd.in/e2qX44PQ

Your top seller just closed another massive deal.
 
Again.
 
Slack lights up. Everyone claps. But behind the smiles? Quiet frustration.
 
The rest of the team is still stuck chasing dead-end prospects. Wondering why the magic never transfers.
 
Here's the hard truth: you're not scaling performance.
 
You're scaling luck.
 
I spent years throwing training, comp plans, and pep talks at this problem. It never worked.
 
Because the gap between your top 20% and everyone else isn't talent.
 
It's intelligence.
 
Your best reps know which accounts to prioritize. Which products to position. Who actually makes the decision. And exactly when to deliver the message.
 
That intelligence lives in their heads—not in your systems.
 
ICONIQ's 2025 research shows the gap clearly:
 
→ High AI adopters: 61% of AEs hit quota 
→ Everyone else: 56%
 
That 5-point gap represents millions in revenue.
 
But here's what keeps me up at night:
 
→ High adopters close in 20 weeks. Others take 25. 
→ High adopters convert 41% of free trials. Others convert 36%. 
→ High adopters see 38% productivity gains. Others see 28%.
 
Every metric compounds. Every advantage multiplies.
 
While your systems stay static, theirs get smarter every single day.
 
The companies winning right now aren't working harder.
 
They've built what I call an Intelligence Layer—the pattern recognition engine that makes everyone as effective as their top performers.
 
Instead of 9-month ramp times, new hires are productive in week one.
 
Instead of guessing on deals, reps get guided to the right accounts with the right message in real-time.
 
Instead of pipeline being a mystery, it becomes predictable.
 
Your stars aren't superhuman.
 
They're just working with better intelligence.
 
The future of sales isn't about more reps. It's about smarter systems.
 
And the companies that figure out how to scale that intelligence across every rep?
 
They win.
 
What would change if every rep on your team could see the patterns your best performers see?

Google ads target what you typed.
 
ChatGPT ads will target what you 𝘮𝘦𝘢𝘯.
 
OpenAI announced ads coming to ChatGPT. 

800 million users, testing in the US "in coming weeks."
 
Most coverage focused on revenue models. 

"OpenAI needs money." "Subscriptions aren't enough."
 
They're missing the story.
 
When someone Googles "best CRM for small business," that's a keyword match. The algorithm knows what you typed. That's it.
 
When someone asks ChatGPT the same question? 

The AI knows context. 

Your team size from three messages ago. 

Your budget sensitivity from how you phrased things. 

Your integration needs from last week's conversation.
 
This isn't search advertising. It's intent advertising.
 
And it gets weirder.
 
OpenAI's announcement showed users can "start a direct chat" with the advertiser's AI. 

The funnel becomes: ChatGPT conversation → ad → brand AI conversation → purchase.
 
Your brand doesn't just need an ad. It needs an AI that can hold a real conversation.
 
Here's what changes for GTM operators:
 
→ Conversational brand presence becomes a strategic asset 
→ New metrics: conversation depth, AI-assisted conversion, conversational share of voice 
→ Attribution gets messy (good luck tracking that funnel) 
→ Two-tier AI is official: paid = clean, free = ads
 
OpenAI made the standard promises. 

"Ads won't influence answers." 

"Your conversations are private." 

"You control your data."
 
Every platform has said this. Watch how it evolves.
 
The last major ad platform—social media—created trillion-dollar companies.
 
This one will be bigger. And it's happening now.

Check out the link in the comments for more.

You don’t wanna miss Dannielle Sakher sharing the goods!!

View newsletter: GTM AI Podcast & Newsletter

Open article: 1/28/26: 5 AI Workflows MindStudio’s GTM Leader Runs Daily to 3x Pipeline  by Jonathan M Kvarfordt, MBA • 7 min read

1/28/26: 5 AI Workflows MindStudio’s GTM Leader Runs Daily to 3x Pipeline

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