Liza Adams

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.