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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

Why pay attention to digital twins right now? Because they help your team get more done, work consistently, and think strategically. A digital twin isn’t just another AI tool. It’s your first real AI teammate.

• Digital twins are AI simulators that mirror how you think and work.

• Personal simulators get you value fastest and help you quickly build your AI skills.

• Creating a twin just needs clear inputs: your public content, strategic frameworks, lived experiences, and unique insights.

• There are five simulator types that support GTM teams: personal productivity, exec alignment, peer planning, customer insights, and influencer engagement.

• Teams building simulator ecosystems spend less time on routine tasks and more time on strategic work.

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 18-min podcast here while driving, walking the dog, or doing chores. 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.

Research Backs Up What We’re Seeing: AI Works as a True Teammate

Let’s look at what recent research tells us about how well AI teammates really work.. A recent study with 776 P&G employees shows that individuals working with AI performed just as well as traditional all-human teams.

This research confirms what we’re seeing with AI teammates, including digital twins, in real life. AI also breaks down expertise barriers. It makes work faster. And people actually feel better working with AI partners. You can read more about the research in Ethan Mollick’s article called The Cybernetic Teammate.

As we discuss how to build your first AI teammates, remember this isn’t just theory. The science now backs up what forward-thinking teams already know – AI is more teammate than tool.

Now that we know AI teammates work, let’s talk about how you can start using them in your own team.

The Simulator Ecosystem

In my past newsletters where I discussed how I’ve helped teams grow from using AI as tools to working with AI teammates to managing AI systems, many of you asked: “Where do we start?”

Most people think about AI teammates like a social post writer, campaign planner, customer researcher, or proposal writer. Those are completely valuable roles. But if you’re leading a team and just getting started, I believe everyone creating a digital twin of themselves is a great place to begin.

This makes a fantastic group exercise. Team members can even share their twins with each other to improve communication and collaboration. For GTM executives and leaders, this approach helps both you personally and your team collectively.

Digital twins or simulators (“sims”) mimic specific thinking patterns and knowledge. They work alongside you as true collaborators, not just task helpers.

Let me break down five simulator types that create immediate value for GTM teams:

I built an interactive model showing how each simulator type works in real business scenarios, where you can explore knowledge requirements, and see sample conversations.

I created it using AI (Claude Pro Sonnet 3.7), and it’s become one of my most requested resources. Try it out and let me know what you think!

Wondering where to start? Here’s why creating your personal digital twin is a great first step.

My Sim: The Ideal First AI Teammate

Your personal simulator makes the perfect starting point for three simple reasons.

1. You already have what you need. You know your own content, style, and thinking better than anyone.

2. You can easily check if it’s right. You know right away if your simulator sounds like you and thinks like you.

3. It helps you personally before you expand to your team. This builds your confidence and skills for bigger projects.

How I Built My Digital Twin (and How You Can Too)

Let me share my personal experience building and working with LizaGPT over the past year.

A few years ago, I joked about cloning myself. Now, with my digital twin, I kind of have and it’s changed how I work!

I started with a clear goal: I needed a thinking partner that understood my frameworks, writing style, and strategic approach. This would help me work faster and stay consistent across all my projects.

I gathered three main types of information:

1. Public content I’d created (published articles, newsletters, LinkedIn posts, talks)

2. My writing and communication style guide (tone, voice, what to avoid)

3. My strategic frameworks (templates, models, analysis approaches, AI use cases)

I even shared personal insights like my Myers-Briggs profile (EXFJ, X because I’m smack in the middle of N and S) and my immigrant journey story “A Child Immigrant’s Tale: Raised by America and Keeping it Going” to help it understand what drives me at my core.

Below is a screenshot showing the instructions and knowledge built into LizaGPT. My instructions are straightforward and the knowledge consists of 20 files with the info I discussed above.

Building Your Own Digital Twin

If you’re ready to build your own digital twin, here’s how to get started using ChatGPT:

1. Click on Explore GPTs from the main page of ChatGPT, then click on Create, then Configure

2. Name your GPT and briefly describe it

3. Type your instructions and upload knowledge files

4. Click the + sign under the Create/Configure bar to upload a profile photo or have DALL-E create one

5. Test your digital twin in the preview window and tweak as needed

6. When satisfied, click the Create button and choose your sharing settings

Remember that you need to maintain and manage it on an ongoing basis. New OpenAI features and algorithm changes can potentially change how your custom GPT performs. Plus you and your needs change too.

To make updates, simply click on the down arrow next to your GPT’s name and select Edit GPT. Make your changes, test them, and hit Update.

Once your twin is set up, it’s important to find the right balance between your strengths and your AI teammate’s.

Before we get into how your AI teammate complements your strengths, there’s one more piece that most people skip. The instructions makes all the difference.

Write Better Instructions: The Real Key to a Useful Digital Twin

Most people upload a few documents, write a sentence or two of instruction, and hope for the best.

But your instructions are the difference between a digital twin that’s helpful and one that’s transformational.

Over the past year, I’ve refined LizaGPT’s instructions into something that does much more than help me write or summarize. It helps me think better. Work faster. Catch blind spots. And pressure-test ideas before they hit the real world.

Here’s a simple structure you can follow to create high-quality instructions for your own twin:

Your digital twin is more helpful and way more fun when it has a little personality. Let it reflect yours.

Here’s a real line from mine:

“Most of all… have a sense of humor and have fun. Insert a joke here and there. It’s ok to be bold, salty, and spicy just like a bowl of Chex mix.”

Here’s bold, salty, and spicy LizaGPT. 😉

You’ll get the most value and build more confidence in creating AI teammates by writing your own instructions. Enjoy the learning process. When you succeed, you win. When you fail, you learn. Believe me, I’ve had my equal share of AI failures but that’s a huge part of understanding how to best work and guide AI.

Watch the full demo + walkthrough of how I built and use LizaGPT: https://www.youtube.com/watch?v=Io0wqnRh-rU

The Human-AI Balance: Complementary Strengths

After over a year working with my digital twin, I’ve learned that we balance each other well.

My human limitations:

• Some days I’m tired, frustrated, or overwhelmed

• I forget and can only process so much at once

• Life happens – college tours, sick kid, caring for elderly parents

How LizaGPT helps me:

• Processes information quickly when decisions are needed

• Organizes my thinking and jumpstarts my work

• Helps me stay my best professional self during personal challenges

But LizaGPT lacks what makes me human – the fire in my belly, the source of original strategic thinking, my passion for elevating GTM functions’ strategic value, ensuring diverse voices are heard, and using business as a force for good. It doesn’t have my lived experiences, my human judgment, or my ethical compass.

What I’ve found most surprising is that LizaGPT has never been just a productivity tool. Even in the most tactical execution tasks, it’s a true thought partner that makes my ideas better. Starting from a blank slate used to be daunting – now I have a judgment-free sounding board for early ideas.

Of course, LizaGPT still needs:

• Guidance and checking

• Regular maintenance and management

• Accountability (I’m ultimately responsible for results)

The key is finding the right balance where we each contribute our unique strengths.

My Real Life Conversations with LizaGPT

Here are a couple of my chats with LizaGPT. You’ll see how it responded based on my instructions as well as knowledge I’ve given it about my thinking and my work.

1) Content Drafts Based on My Frameworks and Strategy

2) Identifying Jobs to be Done and AI Teammates Aligned to Strategic Initiatives

Digital twins help teams stay connected. A content marketer built a twin before maternity leave to share her expertise with teammates. A leader created one that explains her decision style and communication preferences to new team members. Both twins bridge knowledge gaps and strengthen connections, not replace people.

The impact on my productivity has been dramatic. Tasks that once took 2-3 hours now take 45 minutes. More importantly, my work is more consistent and often higher quality because I can focus on the parts where my vision for what’s possible, human creativity, strategic thinking, and judgment add the most value.

I’ve had the pleasure to work with Carol-Lyn Jardine, SVP of Marketing at Dice/DHI Group Inc, build a team with human and AI teammates. Here’s the case study and playbook for this real life human-AI org. She explains how digital twins transformed her marketing organization:

“We started building digital twins as an experiment, but they’ve become critical team members. What began as 25 humans and 20 AI teammates has grown to 26 humans working alongside 35 AI teammates, including several sims.

The productivity gains were immediate, but the strategic impact was even more powerful. Our sims help us test messaging across different personas before launch, anticipate executive questions, and maintain consistent strategic thinking even during our busiest periods.

The investment question wasn’t even an issue – about $2,000/month for ChatGPT Team and Claude Pro across our marketing team. We saw ROI from our very first use case that delivered value far beyond this cost. When a technology saves your team hours every day while improving quality, the business case makes itself.

For marketing leaders just starting out, personal sims are the perfect entry point – they create quick wins while building the skills your team needs for broader AI adoption.”

As you start working with your twin, you might hit some bumps. Here’s how to avoid common issues.

Common Pitfalls (and How to Avoid Them)

As you build your first sim, you might run into these issues:

• Inconsistent outputs – Start with focused knowledge inputs for specific use cases rather than trying to build a sim that does everything at once. Iterate based on actual use.

• Getting team buy-in – Start with a personal success story. Show how your sim helped solve a real problem, then offer to help teammates build their own.

• Maintaining the simulation – Schedule regular updates (monthly or quarterly) where you add new content and adjust instructions based on what’s working.

Important: Never use Personally Identifiable Information (PII), sensitive, or confidential information when building sims. Always check your company’s AI policy and your AI model’s guidelines. Privacy and security must come first in any AI project.

Let’s look at specific ways different roles can use digital twins and how it can improve your brand.

Role-Specific Applications and Personal/Company Brand

• For Marketing Leaders – Sims can help test positioning before market launch, optimize content strategies, and align marketing frameworks across distributed teams.

• For Sales Leaders – Sims are good for objection handling practice, proposal refinement, and turning weaknesses into offense in competitive responses.

• For Customer Success Leaders – Sims can improve onboarding processes, test support responses, and help identify expansion opportunities through simulated customer interactions.

Audrey Chia, Founder of Close With Copy and personal branding expert, shares how her digital twin enhances her client work:

“My digital twin has been transformative for both my business and my clients. It helps me maintain consistent quality across projects while I focus on strategy and creative direction.

What surprised me most was how it improved my personal branding work – my AI twin can analyze a client’s existing content to identify their authentic voice patterns, making our branding work more precise and impactful.

For anyone starting out, feed your simulator both your best work and your thinking process behind it. The magic happens when it captures not just what you create, but how you think about creating it.”

Personal branding is an exceptional use case for digital twins. And it’s not just personal, it’s powerful for your company too. Because a company’s people, especially its leaders, are its brand.

As personal brand strategist Victoria Tollossa says:

“Today, we’re deep in the attention economy. It’s not what you know. It’s not even who you know. It’s who knows YOU.”

Trust is the new currency. But trust isn’t built in just one place anymore. AI (and people) form opinions based on signals from everywhere: your content, your reviews, media mentions, employee voices, even what others say about you.

Use your digital twin to help you communicate your unique thinking and experience at scale. Shape your brand actively. Don’t just let it happen. And whatever you do—don’t be invisible.

Your Digital Twin Challenge

Ready to give it a try? Here’s your challenge this week:

1. Create your first personal simulator – Pick one specific area where you need consistent help. If you already have a digital twin, great. Try making it better!

2. Test it out – See how your digital twin performs on a real task. Make any adjustments needed.

3. Share your experience – Consider posting about your experience on LinkedIn using the hashtag #MyAITwin. Your insights on what worked, what surprised you, and the value you discovered could inspire others to start their own AI journey.

The future of human-AI teamwork starts with simple experiments like this. Let’s start small, learn quickly, and build together.

If you enjoyed this newsletter, you might find value in my previous pieces that build toward this concept:

• A Leader’s Human-AI Org Transformation Playbook – How a lean team transformed into a human-AI powerhouse

• AI Is Redefining GTM Jobs – The evolution from tool users to teammates to orchestrators

The Practical AI in Go-to-Market newsletter is designed to share practical learnings and insights in using AI responsibly. 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.

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

• AI is changing jobs faster than ever. Some roles will disappear. And while new roles will crop up, the bigger challenge is whether we can adapt quickly enough.

• GTM teams evolve through three phases with AI: using AI as tools, guiding AI as teammates, and orchestrating AI systems. This progression will significantly change how teams work.

• Teams succeed at different phases based on what works for them. The right AI approach helps teams achieve more with less effort.

• Companies are already hiring for new roles that blend GTM expertise with AI skills which create new career paths.

• People who learn to work well with AI today will have better career options tomorrow. Those who build these skills now will compete better for future roles.

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 podcast here while driving, walking the dog, or doing chores. 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.

The Three Phases of AI in GTM Teams

We’re beginning to see this progression in how GTM teams adopt AI:

Phase 1: Using AI as Tools – Teams use AI for individual tasks like writing content, solving problems, or generating ideas. People work with AI one task at a time instead of in connected workflows.

Best fit for teams just starting with AI, regulated industries, or when you need humans to have the final say on all outputs.

Phase 2: Guiding AI as Teammates – Teams develop structured workflows where humans and AI collaborate. AI handles defined processes while people provide strategy and oversight.

Works best when your customers expect personalized service, when complex decisions require human judgment, or when you need both automation and human insight.

Phase 3: Orchestrating AI Systems – Leaders coordinate multiple specialized AI systems working together toward strategic goals. Humans provide oversight and make the ethical judgment calls that AI cannot.

Right choice for organizations with lots of data, standardized processes, and when speed and efficiency directly impact your bottom line.

Most teams today operate in Phase 1 or early Phase 2. Different organizations will find their ideal balance at different phases, based on their specific needs and goals.

While AI evolves quickly, most orgs need time to adapt. People learn at different speeds, workflows need updating, and systems require integration. It may take months to progress between phases just like any significant workplace change.

Choose what supports your goals and what your customers expect, not just what sounds most advanced. Remember, most orgs are still figuring this out. This is a learning journey for everyone.

The 100-Year View: Jobs Change, Humans Adapt

Jobs have always changed over time.

When computers came along, file clerks moved into system administration. When the internet took off, retail workers shifted to e-commerce. Some jobs disappeared, but new careers took their place.

(See the timeline chart below, created by Claude Sonnet 3.7, based on research from ChatGPT 4.5 about U.S. jobs over the last 100 years. If interested, here’s the full research report, the infographic and my prompts.)

The big difference today is speed. Earlier changes took decades. AI is happening in months or weeks.

Ethan Mollick, Associate Professor at The Wharton School, puts it best:

“It is time to stop pretending that the world isn’t changing, and time to start taking control to get the future we want. We can’t predict which future we get, but we can try to steer towards a better one.”

Paul Roetzer, CEO of Marketing AI Institute and SmarterX, as well as the creator of JobsGPT, offers practical insight:

“AI isn’t just changing jobs; it is changing how we think about work itself. The real challenge isn’t whether AI will replace jobs, but how fast professionals and organizations can adapt.

With JobsGPT, we’re helping people understand how their roles are evolving, assess AI’s impact on specific tasks, and identify the skills needed to stay ahead. Those who thrive won’t just use AI. They will rethink workflows, develop new skills, and build AI-forward careers.”

Curious about how AI might impact your job?

Try JobsGPT. It shows you which tasks AI can support and the new skills you’ll need.

How AI Is Changing GTM Roles and Creating New Jobs

Forward-thinking companies are already hiring for new roles that blend GTM expertise with AI skills, as you can see below:

Even AI leaders like OpenAI are creating new roles that bridge technology and go-to-market functions. They’re currently hiring a “Head of GTM Innovation” in their Technical Success department, not in marketing or sales.

Smart companies like OpenAI aren’t simply adding “AI” to old job titles. They’re creating whole new roles built for a world where humans and AI work as partners.

See How GTM Roles Change Through the Three Stages

Here’s how this evolution might look specifically for Product Marketing, as an example.

Check out this evolution yourself using the interactive models below for various roles in marketing, sales, and customer success:

• Interactive Marketing Role Evolution Model – Models Brand Marketing, Content Marketing, Digital Marketing,Product Marketing, Field Marketing, Marketing Operations, Demand Generation, Growth Marketing, and Partner Marketing

• Interactive Sales Role Evolution Model – Models Account Management, Sales Development, Solutions Sales, Sales Enablement, Sales Operations, Channel Sales, Inside Sales, Enterprise Sales, and Sales Engineering

• Interactive Customer Success Role Evolution Model – Models Customer Success Management, Customer Onboarding, Technical Customer Success, CS Operations, Customer Enablement, Customer Support, Digital Customer Success, Voice of Customer, and Renewal Management

Real-World AI Integration Early Success: Human-AI Marketing Ecosystem

Megan Ratcliff, Director of Growth Marketing and Integrated Campaigns at Dice, has built an AI ecosystem that transforms how she works.

“We all know that feeling – back-to-back meetings all day, then racing to deliver on commitments in those precious 30-minute gaps. So here’s what I built for myself: a personal AI ecosystem that helps me think, create, and deliver better work even when time is tight.

These aren’t replacements for collaboration with my amazing colleagues – they’re tools that help me show up more prepared when we do connect.

What makes this work is the collaboration flow between specialized AIs – each designed for specific tasks but working together in an integrated system.”

She explained the role of each AI and how there work together here.

It’s early days with this system built with custom GPTs (ChatGPT), AI Projects (Claude), and simple automations. But there’s a bigger vision to connect more of the tech stack, support work across more teams, and orchestrate AI agents (AIs that do tasks on our behalf autonomously).

In fact, in the future, the ecosystem may include AI agents that manage other agents. Megan will continue to be the architect, strategist, and the responsible AI guide.

This real system is already delivering results:

• Aligning campaigns with company goals without overwhelming customers

• Quickly adapting to market shifts

• Testing ideas with AI-driven customer personas before launch

• Creating better data visuals and deeper insights

• Leading cross-functional strategic initiatives

Her manager notes that Megan is one of the most efficient employee she’s ever seen, as if she works double the hours.

Megan has begun to reimagine what a marketing leader can be, becoming a Marketing Strategy Architect. She has redefined her role!

The good news is that her approach is something that many can do. She made this happen with no coding skills but with a lot of curiosity, systematic thinking, and a growth mindset.

Megan is a trailblazer in the human-AI org transformation case study and step-by-step playbook that I highlighted in my previous newsletter.

This team that I helped lead to become a 45-member powerhouse (25 humans, 20 AI teammates) achieved impressive results in 6 months:

• 50-75% faster content creation

• 98% accuracy in lead qualification

• 35% better campaign performance

How Human-AI Workflows Change Across Phases

As teams go through the three phases, workflows change:

Phase 1 – Humans use AI for individual tasks like writing, research, or problem-solving, but without connected workflows.

Phase 2 – Humans and AI have specific roles with clear handoffs. The sample workflow below shows how this looks in practice:

Phase 3: Multiple specialized AIs work together while humans focus on strategy, monitoring results, and high-level decisions.

Note that creating these workflows doesn’t require coding skills, just clear thinking about processes and handoffs.

Try the interactive workflow simulators for each GTM team:

• Interactive Sales Workflows Simulator– Models lead qualification, sales discovery & call prep, objection handling, proposal generation, and deal velocity analysis.

• Interactive Marketing Workflows Simulator – Models product launch campaign, content creation, event planning, competitive analysis, and campaign performance.

• Interactive Customer Success Workflows Simulator – Models customer onboarding, issue resolution, product adoption, expansion planning, and renewal processes.

Alina Vandenberghe 🌶️ he Co-Founder and Co-CEO of Chili Piper, puts it this way:

“AI is the ultimate unfair advantage for GTM teams if you use it right. The strongest teams don’t simply automate tasks. They train AI to think like their best reps and eliminate tasks that slow them down.

If your team still qualifies leads manually, spends hours on research, or does repetitive tasks, you’re behind. Map your slowest processes first. Then let AI clear those bottlenecks—whether it’s data entry, customer insights, or sales follow-ups.

The future won’t wait. Teams that work with AI as a teammate will drive the best results.”

Next Steps Based on Your Phase

Pick your starting point based on where you are today:

If you’re in Phase 1 (Using AI Tools) – List out what tasks take too much time or require deep thinking. Pick one workflow where people and AI could team up, and start there.

If you’re in Phase 2 (Guiding AI Teammates) – Write down what’s already working well. Find your AI trailblazers. These team members will help others get comfortable with new ways of working.

If you’re approaching Phase 3 (Orchestrating AI Systems) – Focus less on the details and more on the big picture. Track how your efforts improve the full customer experience.

For a Hybrid Approach, figure out which teams need which approach. Some might need basic tools while others are ready for more advanced systems.

Across all phases, people who actively build AI skills today will have more opportunities tomorrow. The job market already values these abilities, and this trend will only grow. The window to get ahead won’t stay open forever.

Start small, learn as you go, and adjust based on what works.

I’d love to hear about your experiences. What phase is your team in today? What new AI skills are you learning?

Let’s continue learning together as we build the future of GTM functions.

The Practical AI in Go-to-Market newsletter is designed to share practical learnings and insights in using AI responsibly. 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.

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

• AI is changing jobs faster than ever. Some roles will disappear, and while new roles will emerge, the bigger challenge is whether we can adapt quickly enough.

• GTM teams will move from using AI as just a tool to closely working with AI teammates. This significantly changes daily tasks.

• Teams that move through all three phases will have an advantage over their competitors, doing more complex work faster and with fewer people.

• Companies are already hiring for new roles that blend GTM expertise with daily AI collaboration.

• AI will make many roles more efficient, meaning fewer people may eventually be needed. Professionals who learn how to collaborate closely with AI will be better positioned to compete for these valuable roles.

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 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.

The 100-Year View: Jobs Change, Humans Adapt

Jobs have always changed over time.

When electricity arrived, blacksmiths became auto mechanics. When computers came along, file clerks moved into system administration. When the internet took off, retail workers shifted to e-commerce. Some jobs disappeared, but new careers took their place.

(See the timeline chart below, created by AI/Claude Sonnet 3.7, based on research from AI/ChatGPT 4.5. If interested, here’s the full research report, the infographic and my prompts.)

The big difference today is speed. Earlier changes took decades. AI is happening in months or weeks.

Ethan Mollick, Associate Professor at The Wharton School, puts it best:

“It is time to stop pretending that the world isn’t changing, and time to start taking control to get the future we want. We can’t predict which future we get, but we can try to steer towards a better one.”

AI is already changing how we work. We can either actively guide the change or let it happen to us.

Paul Roetzer, CEO of Marketing AI Institute and SmarterX, as well as the creator of JobsGPT, offers practical insight:

“AI isn’t just changing jobs; it is changing how we think about work itself. The real challenge isn’t whether AI will replace jobs, but how fast professionals and organizations can adapt.

With JobsGPT, we’re helping people understand how their roles are evolving, assess AI’s impact on specific tasks, and identify the skills needed to stay ahead. Those who thrive won’t just use AI. They will rethink workflows, develop new skills, and build AI-forward careers.”

Curious about how AI might impact your job?

Try JobsGPT. It shows you which tasks AI can support and the new skills you’ll need.

Can we reskill fast enough? Can companies create new roles quickly enough?

History shows humans adapt. With every new technology, we’ve always found new ways to contribute and add value. We’re built to adapt as long as we prepare now.

How AI Is Changing GTM Roles and Creating New Jobs

Go-to-market roles are already shifting significantly as AI adoption grows. This evolution follows a clear progression:

• Today – Doing tasks and coordinating projects

• Tomorrow – Guiding AI strategy and daily use

• Future – Designing and overseeing entire AI systems

This shift is affecting marketing, sales, and customer success teams equally. Forward-thinking companies are already hiring for new roles that blend GTM expertise with AI skills:

These new roles require daily collaboration with AI and often command six-figure salaries. Job titles like AI Agent Engineer, Gen AI Marketing Lead, and Experience Transformation AI Sales Specialist show how quickly the job market is changing.

Real-World Example of a New Job: Head of GTM Innovation

Even AI leaders like OpenAI are creating new roles that bridge technology and go-to-market functions. They’re currently hiring a “Head of GTM Innovation.” This is a perfect example of how orgs are rethinking traditional boundaries.

This person will:

• Lead engineers who improve how customers experience OpenAI

• Work with Sales, Technical Success, and Revenue teams

• Build AI tools that make GTM teams more effective

• Speak up for what users really need

What makes this interesting isn’t just the job title, it’s where it sits in the organization. This role lives in the Technical Success department, not in marketing or sales. OpenAI is building bridges between their AI experts and customer teams.

This is exactly the kind of silo-breaking we’ve been talking about. Remember what Jacob Warwick said: “The best executives are rebuilding how work gets done.”

Smart companies like OpenAI aren’t simply adding “AI” to old job titles. They’re creating whole new roles built for a world where humans and AI work as partners.

Here’s how this evolution might look specifically for Product Marketing as an example.

Check out this evolution yourself using the interactive models below:

• Interactive Marketing Role Evolution Model – Models Brand Marketing, Content Marketing, Digital Marketing,Product Marketing, Field Marketing, Marketing Operations, Demand Generation, Growth Marketing, and Partner Marketing

• Interactive Sales Role Evolution Model – Models Account Management, Sales Development, Solutions Sales, Sales Enablement, Sales Operations, Channel Sales, Inside Sales, Enterprise Sales, and Sales Engineering

• Interactive Customer Success Role Evolution Model – Models Customer Success Management, Customer Onboarding, Technical Customer Success, CS Operations, Customer Enablement, Customer Support, Digital Customer Success, Voice of Customer, and Renewal Management

Jason Warwick, CEO of ThinkWarwick Global, who coaches top executives on career growth and compensation, puts it simply:

“AI is changing how we lead, what we earn, and where our careers go—and it’s happening faster than any tech we’ve seen before. The best leaders aren’t just using AI tools. They’re completely rethinking how work happens. They tear down walls between teams, clear roadblocks, and build environments where people and AI succeed together.

The strongest leaders today are building their superpowers at the intersection of AI, leadership, and psychology. They understand technology, but also what makes people tick and how to bring out their best. As AI handles more routine tasks, your ability to influence, inspire, and connect on a human level becomes your competitive edge. Being authentic, showing integrity, and understanding what motivates people creates more value as AI clears away busywork and opens space for meaningful impact.

Leaders who can get their teams excited about AI instead of fearing it will build an unfair advantage. Those who wait or resist will be left behind. Your paycheck will reflect your ability to combine AI with strong teams. If you want to stay relevant, don’t passively wait for AI to define your job. Decide how AI fits into your vision, lean into your human leadership strengths, and take action now.”

Jacob has more great insights at www.execsandthecity.com.

Real-World Success: Human-AI Marketing Team in Action

This isn’t just theory. In my previous newsletter titled “A Leader’s Playbook: How a Lean Team Transformed Into a Human-AI powerhouse”, one forward-thinking CMO transformed a lean marketing team into a 45-member powerhouse where 25 humans built and guide 20 AI teammates responsibly.

In just six months, they saw clear results:

• 50-75% faster content creation

• 98% accuracy in lead qualification

• 35% better campaign performance

The team created human-AI workflows. Each person has specific AI teammates trained to support them.

See the full case study and step-by-step playbook.

Inside Human-AI Workflows: How the Collaboration Actually Works

In successful workflows, humans provide strategic direction, creativity, and final decision-making. AI rapidly analyzes data, surfaces insights, and handles routine tasks.

This goes beyond casually using tools like ChatGPT. It’s an intentional, structured partnership between GTM experts and AI trained for their specific roles.

Below is a detailed example of a Sales workflow:

Try the interactive workflow simulators for each GTM team:

• Interactive Sales Workflows Simulator– Models lead qualification, sales discovery & call prep, objection handling, proposal generation, and deal velocity analysis.

• Interactive Marketing Workflows Simulator – Models product launch campaign, content creation, event planning, competitive analysis, and campaign performance.

• Interactive Customer Success Workflows Simulator – Models customer onboarding, issue resolution, product adoption, expansion planning, and renewal processes.

While each workflow shows collaboration within a single team, the strongest results happen when workflows connect across GTM teams. This breaks down silos, creating smoother experiences for your customers.

Alina Vandenberghe 🌶️ he Co-Founder and Co-CEO of Chili Piper, puts it this way:

“AI is the ultimate unfair advantage for GTM teams if you use it right. The strongest teams don’t simply automate tasks. They train AI to think like their best reps and eliminate tasks that slow them down.

If your team still qualifies leads manually, spends hours on research, or does repetitive tasks, you’re behind. Map your slowest processes first. Then let AI clear those bottlenecks—whether it’s data entry, customer insights, or sales follow-ups.

The future won’t wait. Teams that work with AI as a teammate will drive the best results.”

Three Ways to Pick Your First Human-AI Workflow

To choose your first AI teammate, here are three approaches to consider:

• Focus on key strategic projects. These efforts usually get quicker buy-in and support. Here’s a template you can use to map key AI use cases to strategic initiatives.

• Start with your biggest pain points. Quick results build confidence in AI.

• Empower your trailblazer. Begin with team members already excited about AI. Learn more about the important role and impact of trailblazers in scaling AI adoption here.

Once you pick your first use case, clearly map each step of the workflow. Decide exactly which tasks need human judgment and which ones AI can handle. Define clear points where humans and AI pass tasks to each other.

Looking Ahead: The Next Evolution in Human-AI Teams

As teams become comfortable with AI, systems will handle more complex work and require less oversight.

This means human roles will become even more important. People who guide AI will focus on strategic tasks. Teams will be able to do more without adding people.

But there’s also another side. AI will make many roles more efficient. Over time, fewer people may be needed to do the same work. People who know how to collaborate closely with AI will become more valuable and better positioned to compete for these roles.

Preparing now by reskilling and upskilling is the smartest way to remain competitive as these changes happen.

Skills you’ll need will also evolve over time, following the same progression from using AI tools to managing AI teammates to overseeing autonomous systems.

Where Are You in This Evolution?

Where does your team stand? Are you focused on AI tool usage, or building AI teammates?

Here are three ways to take the next step:

1. Share this newsletter with colleagues and discuss which workflows you could enhance with AI teammates.

2. Map one critical process in your GTM function using the human-AI workflow framework.

3. Create a simple AI teammate for one specific task and track the results.

I’d love to hear about your experiences. What workflows are you enhancing with AI teammates? What challenges are you facing? What benefits have you discovered?

Let’s continue learning together as we build the future of GTM functions in the AI era.

The Practical AI in Go-to-Market newsletter is designed to share practical learnings and insights in using AI responsibly. 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.

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.

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.

👉 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:

“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:

👉 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.

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:

“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:

“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.

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.

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.

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.

👉 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:

“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:

👉 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.

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:

“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:

“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.

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.