• Skip to primary navigation
  • Skip to main content
GrowthPath Partners LLC

GrowthPath Partners LLC

Empowering Purpose-Driven Growth

  • Engagements
  • Speaking
  • Resources
  • About
  • Contact
  • Show Search
Hide Search

Liza Adams

AI Will Force Marketing and Sales Alignment: The Revenue Gap You Can’t Hide Anymore

Liza Adams · March 12, 2025 ·

Practical AI in Go-to-Market
Get practical insights in using AI for go-to-market strategy, initiatives, workflows, and roles.

Hello go-to-market leaders, strategists, and innovators! 👋 Thank you for dropping by to learn practical AI applications and gain strategic insights to help you grow your business and elevate your team’s strategic value.

Quick Take

Companies miss revenue targets for many reasons. Market shifts. Economic headwinds. Changing customer needs.

But look between these external factors and you’ll find missed opportunities because of the gap between marketing and sales.

Marketing counts leads. Sales tracks closed deals. Customer success measures satisfaction scores. Everyone focuses on their own numbers instead of shared goals. As a result, the company could be losing money through inefficiency.

Here’s how: Marketing delivers 5,000 leads, hitting their target. Sales closes 500 deals, reaching quota. But what about the 4,500 leads that went nowhere? Some were poor fits, some got slow follow-up, some received inconsistent messaging. If just 10% of those could have closed with better handoffs, that’s 450 more deals and millions in revenue.

To be fair, misalignment isn’t just a sales follow-up problem. If marketing generates leads that aren’t truly qualified, or if sales has insights on ideal customers that marketing isn’t factoring in, both sides miss the mark. Alignment is a two-way street.

Note: All interactive models referenced in this newsletter were created with AI (Claude Artifacts) using natural language prompts.


Prefer to Listen? Try the AI-Generated Podcast

For those who prefer to consume information through audio, I’ve used Google’s NotebookLM to transform this newsletter into a short podcast episode, featuring a natural conversation between two AI hosts. You can listen to the AI podcast here. Once you hit play, give it just a few seconds then it will start.

Disclaimer: This podcast was generated by AI based on this written newsletter and reviewed by me to ensure ethical and responsible AI use. It’s designed to provide an efficient, more inclusive way to consume information.


Why This Story Matters

Customers don’t care about your org chart. They see your company as one entity, not separate departments. They expect seamless experiences regardless of which team they’re talking to.

The irony here is that AI tools can make our organizations more human-centered. As data analytics expose the gaps between teams and calculate their revenue impact, companies naturally rethink how they work together.

When the cost of slow handoffs appears in dollars on a dashboard, no one can ignore it. When the impact of misaligned goals becomes visible, change follows.

These alignment principles work across all business functions. AI makes alignment visible by converting patterns into insights and insights into action.

But AI isn’t a magic fix. It’s an amplifier. It highlights inefficiencies, but true alignment comes from leadership, culture, and execution. The companies that succeed won’t just adopt AI tools, they’ll include alignment into their strategy and incentives.

The Hidden Cost of Misalignment

When marketing and sales measure success differently, problems happen naturally. Marketing aims for more leads. Sales works on closing deals. Both teams can hit their targets while the company loses money.

This interactive calculator shows exactly what misalignment costs your business. There are two views you can explore:

Response Time Impact shows how lead follow-up speed affects revenue:

  • Monthly Leads – Enter your total leads (example: 500)

  • Average Deal Size – Your typical deal value (example: $25,000)

  • Quick Response Win Rate – Conversion rate when leads get fast follow-up (example: 45%)

  • Slow Response Win Rate – Conversion rate when follow-up is delayed (example: 20%)

  • % of Leads with Quick Response – Adjust this slider to see impact (example: 50%)

The calculator shows your current monthly revenue ($4,062,500), potential revenue with 100% quick response ($5,625,000), and the monthly revenue you’re losing due to slow follow-up ($1,562,500). Note that these figures are illustrative examples. Plug in your own numbers to see your specific revenue impact.

Response Time Impact

Goal Alignment Impact shows how marketing-sales alignment affects revenue:

  • Marketing Metrics – Monthly leads (1000), lead quality score (60%), cost per lead ($200)

  • Sales Metrics – Lead follow-up rate (40%), conversion rate (25%), average deal size ($25,000)

This view shows your current revenue ($2,500,000), potential aligned revenue ($3,750,000), and monthly revenue lost from misalignment ($1,250,000).

Of course, these numbers aren’t one-size-fits-all. Conversion rates and revenue impact depend on factors like industry, sales cycle, and competitive positioning. Use this as a directional guide, not a predictor.

The key insight is that time matters, but so does cross-team alignment. When marketing generates leads that sales doesn’t follow up on, or when sales ignores certain lead types, the company leaves serious money on the table.

Goal Alignment Impact

👉 Try the interactive calculator using your own data and scenarios. (Better experience on desktop vs mobile)

Latané Conant (she/her), Chief Revenue Officer at 6sense and author of “No Forms. No Spam. No Cold Calls,” notes:

Latane Conant, Chief Revenue Officer of 6Sense

“B2B buying isn’t a straight line — it’s an average 11-month maze with 640 interactions, and 81% of buyers have already picked a winner before they ever talk to sales. That means revenue teams need show up early, often, and in sync.

AI ensures alignment by making every touchpoint count, turning fragmented signals into a connected, high-impact buying experience. When teams have a shared understanding of the buying journey, they can engage the full buying team with the right actions at the right time, without stepping on each other’s toes along the way.”

The Power of Strategic Focus: Aligning Teams on the Right Targets

When marketing and sales align, they start saying “no” together.

While the interactive calculator shows the revenue cost of misalignment, there’s another hidden expense around wasted effort going after prospects that aren’t right for your business. The most resilient companies today have shifted from “growth at all costs” to “sustained profitability.”

This simple but powerful targeting framework can transform how teams collaborate:

  • Green (center) – Your ideal customers. Focus most resources here where ROI is highest

  • Yellow (middle) – Opportunistic prospects requiring careful qualification

  • Red (outer) – Poor-fit prospects to avoid unless there’s a compelling strategic reason

See how the targeting framework works below:

B2B Target Framework

👉 Play around with the interactive B2B target framework. (Better experience on desktop vs mobile)

When marketing and sales share this classification framework, they naturally start working as one unit. Marketing stops generating leads that sales won’t pursue. Sales stops complaining about lead quality. Both teams become accountable for pursuing the right opportunities, not just more opportunities.

What makes this approach powerful is how it creates natural alignment. The framework shows exactly which segments deserve focus and which should be deprioritized. This clarity eliminates the blame game and builds mutual accountability around customer fit.

The most aligned teams don’t just measure handoffs – they agree on who they’re targeting in the first place.

The Alignment Framework That Changes Everything

Response time is just one piece. The bigger challenge is aligning teams on shared outcomes.

GTM Alignment Matrix

This interactive framework helps teams align on what matters. Each market segment (Top Accounts, Key Verticals, Volume Business) has specific goals. Every function contributes to these shared outcomes.

For example, in the “Key Verticals” segment, marketing might own “achieving 30% market awareness in healthcare.” Sales commits to “closing 20 healthcare deals this quarter.” Product builds “healthcare-specific features by June.” When one area falls behind, everyone sees it and can help.

The matrix shows:

  • Who owns which goals for each segment

  • What teams need from each other

  • Where handoffs work well or break down

  • Which functions need support

The color coding serves as a signal, not a judgment. Green areas need maintenance. Red areas need attention. This visual approach helps teams support each other toward common goals.

👉 See the interactive framework in action. (Better experience on desktop vs mobile)

Kimberly O’Neil, who served as COO of Encompass Technologies and developed multiple cross-functional alignment frameworks, shares:

Kimberly O’Neil, former COO of Encompass Technologies

“The best teams I’ve led focus on shared goals, not just their own tasks. Using frameworks like this cut down friction between departments.

What makes it powerful is how it forces teams to map their workflows together. It helps with understanding exactly what they need to get from each other and what they must give or deliver to others. When teams make clear commitments about their inputs and outputs, work gets done, deals close faster and sales grow.

AI could track these connections daily instead of waiting months to see results. Companies that work this way will beat those where each team only cares about their own numbers.”

I saw first-hand how Kim put these frameworks to work and aligned our executive team at Encompass. We failed, learned, solved problems, and succeeded together!

From Framework to Reality

A GTM team recently implemented this approach with a simple principle that success belongs to everyone.

Each function mapped their goals to segment targets. Marketing didn’t just set lead goals. Sales didn’t just forecast deals. They focused on shared success:

  • What each segment needs to win

  • How teams support each other

  • Clear deliverables between functions

  • Regular progress checks

Consider this example: For enterprise accounts, marketing committed to delivering 50 qualified meetings per quarter. Sales promised detailed feedback on every meeting within 48 hours. Product agreed to join key calls to answer technical questions. This clarity eliminated the blame game (“these leads are bad” or “sales isn’t following up”) and built mutual accountability.

AI can make this even more effective by:

  • Alerting when high-value leads haven’t been contacted within an hour

  • Flagging when content for a specific industry isn’t being used by sales

  • Highlighting which types of leads convert best across segments

  • Predicting which deals need executive support to close

Early signs show promise. Teams catch handoff issues faster. They jump in to help before deals stall. Most importantly, they’re having better conversations about what customers really need.

But for these frameworks to stick, teams need more than dashboards. They need clear ownership and incentives. Alignment thrives when leaders tie success metrics to shared outcomes, not just individual KPIs. Change happens faster when compensation, feedback loops, and enablement reinforce cross-team collaboration.

Jonathan Moss, EVP of Growth, GTM Strategy, and Operations at Experity, shares:

Jonathan Moss, EVP of Growth, GTM Strategy, & Operations at Experity

“Most business ideas stay trapped in static slides and spreadsheets. The companies pulling ahead are those turning thinking into doing with AI-built models anyone can use. We’ve seen teams create interactive calculators in minutes that would have taken weeks to code.

The real power comes from giving people tools to test scenarios with their own numbers and see results instantly. These models solve the last-mile problem in GTM strategy: turning insights into actions that drive revenue. Interactive tools lead to faster, smarter decisions across the organization.”

Build Your Own Interactive Models

Creating models like these is one of AI’s most useful yet overlooked powers. Most teams share static slides that no one uses. AI helps turn ideas into tools people actually use.

Building models like the Revenue Calculator or GTM Alignment Matrix is easier than you think. No coding needed. Just describe in plain language:

  • Your key inputs (leads, close rates, deal size)

  • The math you want done

  • How to show the results

  • What people should be able to change

For example, I recently asked AI: “Create an interactive model that shows revenue impact of lead response time. Let users input monthly leads, average deal size, and conversion rates for fast and slow response. Calculate the difference in revenue.” Within minutes, I had a working calculator without writing a single line of code.

The video below show how I prompted AI in plain English to create an interactive model.

How to Create an Interactive Model Using AI (Claude)

AI does the technical work. Your ideas become tools people use. Teams work with numbers instead of just reading them.

This changes how insights spread. Teams see money impact with their own numbers. They spot gaps where they happen. Data drives action.

Looking Ahead

AI gives us new ways to see how team alignment affects money. Companies that build shared goals will win. Those with strict silos risk missing growth.

As we explored in my previous newsletter on AI Raising Customer Expectations: How to Unify Go-to-Market Workflows, customers don’t see your org silos, they expect seamless experiences. When marketing and sales align on targeting the right prospects from the beginning and sharing insights throughout the journey, they naturally deliver these connected experiences.

When teams see the numbers, something clicks. Data makes the invisible visible. Sales understands marketing’s challenges. Marketing sees what sales needs. People start working together because they can see how their work connects. They focus on the same goals instead of competing priorities.

The result is better experiences for customers and stronger work places where success belongs to everyone.


The Practical AI in Go-to-Market newsletter is designed to share practical learnings and insights in using AI responsibly for go-to-market strategy, product, brand, demand, content, and digital, and growth marketing. Subscribe today and let’s learn together on this AI journey!

For those who prefer more interactive learning, explore our applied AI workshops, designed to inspire teams with real-life use cases tailored to specific go-to-market functions.

Also check out this team transformation case study and step-by playbook of how we helped transform a lean GTM team into a human-AI powerhouse with human and AI teammates.

Or, if audio-visual content is your style, here are virtual and in-person speaking events where I’ve covered a variety of AI topics. I’ve also keynoted at many organization and corporate-wide events. Whether through the newsletter, multimedia content, or in-person events, I hope to connect with you soon.

Marketing’s AI Evolution: From Tools to Teams

Liza Adams · March 12, 2025 ·

Published on 2025-03-12 13:15

When everyone else is obsessing over which AI tools to use, the truly forward-thinking marketers are asking a different question: “How do I build and lead AI teammates?”

Following my recent post (https://lnkd.in/gSNPwyRR) about how 60% of today’s jobs didn’t exist in 1940, I’ve been exploring what this means for marketing professionals specifically.

Working with AI, I created this visualization showing how marketing roles might evolve as AI becomes both our teammate and our customers’ research assistant.

The infographic uses Product Marketing as an example, but this same evolution applies across marketing functions:

  • ► Today’s Product Marketing Manager creates messaging and analyzes competitors manually

  • ► Tomorrow’s Market Insight Leader directs AI research teams and teaches AI about customer needs

  • ► The future Market Opportunity Architect builds AI prediction systems and identifies markets

The real value shift is when we go beyond learning to use AI tools better, to learning to build and lead AI teams.

As I covered in my Human-AI Org Transformation newsletter (https://lnkd.in/gKVHapFX), teams that set clear roles between humans and AI create tremendous value. The organizations investing in these leadership skills rather than just buying AI tools will gain a big advantage.

Where are you on this evolution? Still focused on using AI tools, or already building AI workflows and leading AI teams?

#AI #Marketing #FutureOfWork #ProductMarketing #ChangeManagement

Evolve Your Marketing: From AI Tools to AI Teams

Liza Adams · March 12, 2025 ·

When everyone else is obsessing over which AI tools to use, the truly forward-thinking marketers are asking a different question: “How do I build and lead AI teammates?”

Following my recent post (https://lnkd.in/gSNPwyRR) about how 60% of today’s jobs didn’t exist in 1940, I’ve been exploring what this means for marketing professionals specifically.

Working with AI, I created this visualization showing how marketing roles might evolve as AI becomes both our teammate and our customers’ research assistant.

The infographic uses Product Marketing as an example, but this same evolution applies across marketing functions:

  • ► Today’s Product Marketing Manager creates messaging and analyzes competitors manually

  • ► Tomorrow’s Market Insight Leader directs AI research teams and teaches AI about customer needs

  • ► The future Market Opportunity Architect builds AI prediction systems and identifies markets

The real value shift is when we go beyond learning to use AI tools better, to learning to build and lead AI teams.

As I covered in my Human-AI Org Transformation newsletter (https://lnkd.in/gKVHapFX), teams that set clear roles between humans and AI create tremendous value. The organizations investing in these leadership skills rather than just buying AI tools will gain a big advantage.

Where are you on this evolution? Still focused on using AI tools, or already building AI workflows and leading AI teams?

#AI #Marketing #FutureOfWork #ProductMarketing #ChangeManagement

Visualization of marketing roles evolving with AI

See original post here

AI & Jobs: History’s Lessons for Future Work

Liza Adams · March 11, 2025 ·

Published on 2025-03-11 13:15

60% of today’s jobs didn’t exist in 1940. This fact shows how dramatically work changes across generations.

As someone who inspires GTM teams with what’s possible with AI using real-life use cases, I’ve wondered how many current jobs were brand new in the last century. Could our past workforce shifts guide our approach to AI?

I wanted to test new AI models, so I used the newly released ChatGPT-4.5 to research U.S. job evolution over the last 100 years.

Guiding teams through change isn’t just about technology. It’s about meeting people where they are and creating clear paths for upskilling. When humans and AI work together as teammates, the results are powerful.

The research confirmed workers have continuously adapted to new technologies:

  • Farm workers learned to use tractors

  • Factory workers adopted computer systems

  • Office workers used digital tools

Society also created entirely new careers like wellness coaches and social media managers that previous generations couldn’t have imagined.

Now AI brings another major transition. The World Economic Forum predicts AI will create around 170 million new jobs worldwide by 2030, far more than it replaces.

Curious, I asked ChatGPT to tell me what some of these new jobs might be. Here are five that stood out:

  • AI Transparency Advocate – Making sure AI decisions remain trustworthy

  • Virtual Reality Workplace Designer – Creating spaces for remote collaboration

  • Digital Detox Specialist – Supporting healthy technology boundaries (I can definitely see the need for this one.)

  • AI-Powered Ecosystem Restoration Manager – Using AI to repair natural environments

  • Personal Data Broker – Helping people manage their data ethically

ChatGPT-4.5 provided the research that Claude Sonnet 3.7 (also new) turned into the graphic below.

Graphic illustrating job evolution and new AI jobs

See the link to a doc with the full research report and my prompts in the comments, https://lnkd.in/gZcWTcQC.

I do think that this AI transition will be much tougher. In previous innovations, it took time for them to happen… electricity/put up power lines, lay fiber in the ground, etc. AI is now able to leverage all that infrastructure in place. So the changes are much faster. The question is: how fast can we adapt?

Will AI follow historical patterns where technology creates more jobs than it eliminates? Are you preparing your teams to work alongside AI effectively? I’d love to hear your approach.

#FutureOfWork #JobCreation #AI #ChangeManagement #AILiteracy

How AI Creates New Jobs: Lessons from History

Liza Adams · March 11, 2025 ·

60% of today’s jobs didn’t exist in 1940. This fact shows how dramatically work changes across generations.

As someone who inspires GTM teams with what’s possible with AI using real-life use cases, I’ve wondered how many current jobs were brand new in the last century. Could our past workforce shifts guide our approach to AI?

I wanted to test new AI models, so I used the newly released ChatGPT-4.5 to research U.S. job evolution over the last 100 years.

Guiding teams through change isn’t just about technology. It’s about meeting people where they are and creating clear paths for upskilling. When humans and AI work together as teammates, the results are powerful.

The research confirmed workers have continuously adapted to new technologies:

  • Farm workers learned to use tractors

  • Factory workers adopted computer systems

  • Office workers used digital tools

Society also created entirely new careers like wellness coaches and social media managers that previous generations couldn’t have imagined.

Now AI brings another major transition. The World Economic Forum predicts AI will create around 170 million new jobs worldwide by 2030, far more than it replaces.

Curious, I asked ChatGPT to tell me what some of these new jobs might be. Here are five that stood out:

  • AI Transparency Advocate – Making sure AI decisions remain trustworthy

  • Virtual Reality Workplace Designer – Creating spaces for remote collaboration

  • Digital Detox Specialist – Supporting healthy technology boundaries (I can definitely see the need for this one.)

  • AI-Powered Ecosystem Restoration Manager – Using AI to repair natural environments

  • Personal Data Broker – Helping people manage their data ethically

ChatGPT-4.5 provided the research that Claude Sonnet 3.7 (also new) turned into the graphic below.

AI Generated Graphic

See the link to a doc with the full research report and my prompts in the comments, https://lnkd.in/gZcWTcQC.

I do think that this AI transition will be much tougher. In previous innovations, it took time for them to happen… electricity/put up power lines, lay fiber in the ground, etc. AI is now able to leverage all that infrastructure in place. So the changes are much faster. The question is: how fast can we adapt?

Will AI follow historical patterns where technology creates more jobs than it eliminates? Are you preparing your teams to work alongside AI effectively? I’d love to hear your approach.

#FutureOfWork #JobCreation #AI #ChangeManagement #AILiteracy

See original post here

  • « Go to Previous Page
  • Page 1
  • Interim pages omitted …
  • Page 77
  • Page 78
  • Page 79
  • Page 80
  • Page 81
  • Interim pages omitted …
  • Page 122
  • Go to Next Page »

Copyright © 2026 · GrowthPath Partners LLC · Log in

  • LinkedIn