GTM-focused SaaS Advisor and Board Member

I am a go-to-market-focused technology executive and board member with over 20 years experience leading SaaS companies.  

I have led product, marketing, sales, and customer success, and twice I have run companies as CEO.  Along the way I have served formally on 4 boards of directors (including one public company), 7 advisory boards and 3 non-profit boards.

As part of these roles, I have helped to:

* Sell 5 companies (to Oracle, Amazon, Aurea, Maritz, and NonProfitEZ)
* Secure over $100M in equity financing (series Seed, A, B, C)
* Acquire and integrate 5 companies
* Manage small and large quotas (up to $300M)
* Launch dozens of products
* Get two products to profitability on a pure PLG / self-serve basis
* Grow multiple companies at 50%+ growth rates
* Restructure / downsize multiple companies
* Hire hundreds of people
* Create over $1B of shareholder value

I am now 100% focused on teaching, writing, investing and advising.  

As the Executive Chairman of Winning by Design, I work with leadership teams to optimize go-to-market strategies, product development, and customer success.  As an active board member and advisor, I focus on product development and corporate strategy.  As a professor at BYU's Marriott School of Business I teach Product-led Growth, B2B Sales & Marketing, and Career Strategy.

I recently published my first book with Stanford University Press:  FREEMIUM, available from all book retailers.

I am proud to serve as a formal advisor to Mercato Partners, Pledge, Terrett, and ProAI, and an informal advisor to other entrepreneurs and business leaders changing the world.

My mission is to empower the next generation of software leaders and entrepreneurs to create value for their customers and for society.

Dave Boyce

No one has it figured out. 

Since AI changed everything about how customers discover, buy, and use your product, you have to go back to being the "chief figure it out" officer.

"Working harder" on yesterday's playbooks won't cut it.

But to figure it out, you need an experimental framework.  This is what I laid out in my book FREEMIUM, and I recently discussed it at length with Craig Taylor on his podcast, Truth, Lies & B2B Growth.

You can find the full episode on my SubStack:  ProductLedGTM.

XOXO,

-db

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

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.

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

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.

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?

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

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.

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.

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.

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 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?

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”?

“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

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The Battle

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