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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

Picture a marketing team where humans and AI work side by side – not as replacements, but as partners with clear roles and responsibilities.

That’s exactly what one forward-thinking CMO achieved, transforming a lean marketing team into a 45-member powerhouse where 25 humans guide and work alongside 20 AI teammates.

To help teams envision how this human-AI partnership works in practice, here’s a clear example of a marketing team structure:

This type of structure, explored in our previous Marketing Team 2.0 newsletter, shows how AI teammates can support and amplify human expertise. The team adapted this model with remarkable results.

Here’s what the real marketing team structure looks like, showing how AI tools (dotted boxes) work with human team members (solid boxes):

Each AI tool has a specific job and works with specific team members. This keeps things clear and helps everyone work better together.

In six months, as I helped lead and guide this team along the way, we achieved what many think impossible: 50-75% faster content creation with better quality, 98% accuracy in lead qualification, and AI becoming a trusted thought partner for strategy development.

Here’s the playbook that made it happen. It reflects our key learnings.

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.

Why This Story Matters

While this playbook follows a marketing team’s journey, the approach and learnings apply equally to sales and customer success teams. The principles of human-AI partnership, step-by-step adoption, and focus on people first are valuable for any GTM function.

As we explored in my previous newsletter about The Trailblazer Effect, success starts with team members who spot AI opportunities and take action. In this team, a few people were already using AI tools on their own. These “trailblazers” became natural champions and inspired others to get involved.

There’s more competition. It’s hard to stand out. Customer behaviors are changing fast. The way they find solutions, evaluate vendors, form opinions, and make buying decisions are evolving.

Ensuring good product-market fit and effective go-to-market strategy has never been more important. She needed to improve current operations while building for profitability.

Do more with less!

Her already lean team worked at capacity. People wore multiple hats with no in-house copywriters and minimal agency support. They needed a new approach.

She believed AI could help them adapt. However, adding AI tools alone would fall short. Her goals extended beyond the company’s immediate needs.

She cared deeply about her team’s future and wanted to invest in their growth. Building AI skills would help them succeed in this new era.

The Playbook

Here are the five steps that made this transformation successful. Each step was practical and built on the one before it.

Step 1: Start with Understanding

First, I guided the CMO to understand where everyone stood with AI. Some team members were paralyze because of fear of job loss. Some were already using AI without training or responsible AI guidelines, creating potential risks to the business. We needed to act thoughtfully but quickly.

The CMO set clear expectations early. “This is a learning journey we’ll take together,” she told the team. “While there’s no established playbook for AI adoption, we’ll have guidance from someone who’s helped other teams through this journey. Together, we’ll create our own path forward.”

She addressed concerns head-on. This wasn’t about replacing people. It was about helping them grow. We knew AI skills would be important for their careers, both within the company and beyond. Everyone’s voice needed to be heard for AI to benefit all, not just a few.

This approach paved the way for the team to grow into a 25-human, 20-AI structure, where each has a clear role and purpose.

We created multiple channels for input through open group discussions, 1:1 conversations, regular feedback sessions, and a team survey. Here’s a sample employee survey that you can use and modify as needed.

The survey showed important insights:

This human-first approach resonates with many experienced leaders. As Heidi Melin, a Senior Operating Advisor who guides CMOs of Hellman & Friedman’s portfolio companies go through transformation, notes:

“Working with portfolio company CMOs and collaborating with AI advisors like Liza, I’ve learned that understanding your people must come first.

Once you take time to hear their aspirations and concerns, you can show them a clear vision of a human-AI organization. The breakthrough happens when teams see specific examples of how AI can support each role and function, not replace them. This shifts the entire conversation from ‘what will AI do to us’ to ‘how can we build this together.’

When people feel truly heard and see themselves in this future, they move from hesitation to enthusiasm about the possibilities.“

These results guided our workshop design and overall approach. Being open and clear helped build trust for the next steps.

Step 2: Show What’s Possible

AI has changed how customers search, evaluate, and buy. It amplifies both strengths and weaknesses. Good strategies succeed faster, poor ones fail faster.

Our workshops moved beyond generic AI demos to show how AI could help marketing teams respond to these changes and solve real challenges.

Our initial workshop started with how customer behaviors are changing and ways we need to adapt withn the help of AI. This grounded our AI learning with a purpose–serving our customers the best way we can. It wasn’t simply using AI for the sake of AI.

We inspired what’s possible by covering use cases relevant to specific roles. Doing so jumpstarts people’s learning as they can readily see how AI helps them in their job. I discussed this topic in more detail in my previous newsletter titled Making AI Work for Every Marketing Role with Real Use Cases for Their Jobs.

Here’s just a sampling of AI use cases by function. There are many more.

Here’s our core workshop agenda. Then we conducted function-specific sessions for product marketing, campaign teams, and content creators. This approach helped people see immediate value in their daily work.

We chose our initial AI use cases carefully, focusing on three key criteria that tend to drive the most impact:

1. Tasks that are repetitive, time-consuming, and tactical – especially those that multiple people and functions handle. This immediately lightens the team’s load and frees up time for strategic and creative work.

2. Strategic thinking or processes that benefit from consistency – where AI can help standardize proven approaches and frameworks. It’s democratizing strategic thinking.

3. Use cases aligned with strategic initiatives – strategic initiatives have built-in advantages: clear owners, defined KPIs, allocated resources, and high visibility. With this alignment, we have a better shot at successful adoption. Here’s a template you can use for mapping.

Don’t feel the pressure to do everything at once. Start small and use these guidelines to choose your first AI projects thoughtfully.

Mike Kaput, Chief Content Officer of the Marketing AI Institute captures why this relevance matters:

“Most teams struggle with AI adoption because, a lot of times, people can’t see how it fits into their daily work.

Show a content strategist how AI helps them create better content faster, or a campaign manager how it improves targeting, that’s when the light bulb goes on.

Start with real problems your team faces every day. When they see AI solving those problems, you create the momentum needed for real transformation.”

Step 3: Create Space for Learning

The technology isn’t the hardest part—change management is. We created multiple ways for the team to learn, share, and grow together.

We prioritized responsible AI use from the start, collaborating closely with legal and IT teams to set clear guidelines. Teams learned through practical examples what responsible AI use looks like (see examples of responsible uses here) and potential risks to avoid.

This foundation helped us move quickly while protecting the company’s sensitive information. Here are 10 simple strategies to protect your data when using AI.

We made learning AI part of our job, not an afterthought or extra work. We:

• Protected time for AI exploration

• Created safe spaces for questions

• Set up regular help sessions

Three key breakthroughs showed us this approach was working. The team created custom GPTs (AI tools that users train with specific knowledge and guidelines) to handle various tasks:

• Pitch Deck Evolution – Product marketing managers created a custom GPT that reduced a week-long process to days. Teams now update pitch decks consistently and quickly across all chapters.

• Website Content Project – Eight team members across functions used a custom GPT to create website copy based on wireframes, messaging guidelines, and SEO requirements. We completed months of work in weeks, focusing on editing and consistency.

• Strategic Thought Partner – Teams began using AI to evaluate social media strategies, develop campaign plans, build cross-functional operating models, and plan key 2025 initiatives.

As the team worked more with AI, their roles evolved naturally. AI took on routine tasks. This gave people more time for strategic thinking and creative work.

Team members discovered a new dimension to their roles as builders and guides of their AI teammates, making sure their custom GPTs stayed effective and on track.

The team also came up with innovative ways to use AI that went beyond improving tasks. Here are two examples that stood out:

• Supporting Team Transitions – A content marketer preparing for maternity leave built a custom GPT to support her team while she’s away. This AI assistant gives her teammates easy access to her processes, guidelines, and content library. The goal was smooth handoffs and consistent work quality during her absence.

• Enhancing Team Collaboration – A senior leader created a GPT that captures her unique leadership approach. This AI tool helps her team understand her communication style, decision-making process, and how she handles different challenges. It even offers specific suggestions for working effectively with her in various situations. This helps with improving team collaboration as she takes on expanded responsibilities.

If interested, here’s a sample content creation custom GPT in action and a sneak peek of its instructions.

Step 4: Scale Success Through Systems

With early wins showing value, we created two tracking tools to expand these successes across the organization:

Custom GPT Tracking Template

First, we developed a Custom GPT Tracking System to manage our growing collection of AI tools. Clear tracking helped us scale successful approaches and avoid duplicating efforts.

Our tracking covered:

• Clear ownership and accountability

• GPT objectives and capabilities

• How to access the GPT

• Results and benefits

• GPT use limitations and consideration

Below is the Custom GPT Tracking Template. Feel free to adapt this for your team.

Paige O’Neill, CMO of Seismic, shares why this systematic approach matters:

“Anyone can experiment with AI tools. The teams that really transform are the ones that track what works and bring others along on the journey.

When your AI trailblazers share their wins and help teammates learn, you turn individual experiments into company-wide capabilities. That’s how real learning spreads and creates lasting change.”

AI Tech Stack Template

Building on this foundation, we created an AI Tech Stack Template to guide our technology decisions. We learned that building the right AI stack requires careful planning, not rushing to adopt every new tool.

1. Start with Current Martech AI Capabilities – Many existing platforms have powerful AI features. It’s easier to drive adoption with tools your team already knows. Review your platforms’ product roadmap and connect with account teams to maximize current investments.

2. Add Foundational AI Models – We provided paid versions of ChatGPT and Claude to help teams explore core capabilities. These tools offered a secure environment for teams to experiment and learn. The investment was about $1000/month for the entire team.

3. Fill Specific Gaps – Only after maximizing existing tools did we consider new solutions. The AI vendor landscape will consolidate through M&A. Some vendors may not survive. We evaluated additions based on:

• Clear business need

• Integration with current workflow

• Trial/PoC option and ROI potential

• Security and privacy policies

• Vendor stability indicators (Executive team expertise and track record, quality of investors and funding, defensible moats, customer reviews, market position, and growth trajectory)

This AI Tech Stack Template helps map and manage our AI capabilities across functions.

Our approach to building and tracking our AI capabilities delivered measurable results including:

• Content team creating 2x more high-quality assets

• Campaign performance up 35%

• Lead scoring accuracy at 98%

• 15 hours saved weekly on routine tasks

Check out this carousel for more real and quantifiable results from various marketing teams.

Quick Tip: Need to justify AI investment? A different org I worked with got their entire AI program funded after their custom translation GPT (translated customer-facing documents in 4 different languages) saved tens of thousands in localization costs. Start small, show value, then scale.

Step 5: Expand Your Impact

With strong foundations in place, the marketing team is now starting to expand their influence across the company. As the first team to reach 100% AI adoption in just six months, they’re naturally becoming the company’s AI trailblazers.

Early signs of broader impact are emerging:

• Custom GPTs being adapted for other departments

• Marketing-led AI discussions with other teams

• Cross-functional AI initiatives taking shape

This expansion is already breaking down traditional GTM silos. As Sean McCaffrey, Senior Director of Marketing Strategy and Operations at Cin7, noted in my AI Trailblazer Effect newsletter, the real power of AI emerges when it connects workflows across marketing, sales, and customer success, creating more personalized and cohesive customer experiences.

It’s just the beginning, but their story shows how focusing on people creates lasting success with AI.

Looking Ahead

This journey had clear results. In six months, a lean marketing team built a powerful human-AI organization. They strengthened their foundation by understanding team needs, showing practical applications, creating space for learning, and scaling what worked.

More importantly, they proved something valuable. When teams approach AI adoption thoughtfully and systematically, focusing on people first, the results extend beyond metrics. Teams become more strategic. People develop new skills. Work becomes more meaningful.

They continue to push boundaries, now exploring AI tools with autonomous capabilities like Gemini Advanced’s Deep Research and ChatGPT’s Scheduled Tasks. These experiments with basic AI agents (tools that can work on their own, on our behalf) are opening up new possibilities.

The team will also have to think about the newly launched ChatGPT Operator. This demo shows how this AI agent ordered pizza, made restaurant reservations, and bought groceries. This again changes the buyer behavior and journey.

The team will need to cater to both humans and the AI agents that work on their behalf. They’ll also need to determine how to use agents responsibly in their work.

As they develop and use more AI teammates, they’re proving what’s possible with the right approach.

Where is your team on this journey? How are you building your human-AI organization?

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.

Or, if audio-visual content is your style, check out recorded sessions on a variety of topics I’ve covered. You’ll also find information about my past and upcoming in-person speaking 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

Picture a marketing team where humans and AI work side by side – not as replacements, but as partners with clear roles and responsibilities.

That’s exactly what one forward-thinking CMO achieved, transforming a lean marketing team into a 45-member powerhouse where 25 humans guide and work alongside 20 AI teammates.

To help teams envision how this human-AI partnership works in practice, here’s a clear example of a marketing team structure:

This type of structure, explored in our previous Marketing Team 2.0 newsletter, shows how AI teammates can support and amplify human expertise. The team adapted this model with remarkable results.

Here’s what the real marketing team structure looks like, showing how AI tools (dotted boxes) work with human team members (solid boxes):

Each AI tool has a specific job and works with specific team members. This keeps things clear and helps everyone work better together.

In six months, as I helped lead and guide this team along the way, we achieved what many think impossible: 50-75% faster content creation with better quality, 98% accuracy in lead qualification, and AI becoming a trusted thought partner for strategy development.

Here’s the playbook that made it happen. It reflects our key learnings.

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.

Why This Story Matters

While this playbook follows a marketing team’s journey, the approach and learnings apply equally to sales and customer success teams. The principles of human-AI partnership, step-by-step adoption, and focus on people first are valuable for any GTM function.

As we explored in my previous newsletter about The Trailblazer Effect, success starts with team members who spot AI opportunities and take action. In this team, a few people were already using AI tools on their own. These “trailblazers” became natural champions and inspired others to get involved.

There’s more competition. It’s hard to stand out. Customer behaviors are changing fast. The way they find solutions, evaluate vendors, form opinions, and make buying decisions are evolving.

Ensuring good product-market fit and effective go-to-market strategy has never been more important. She needed to improve current operations while building for profitability.

Do more with less, while achieving better results!

Her already lean team worked at capacity. People wore multiple hats with no in-house copywriters and minimal agency support. They needed a new approach.

She believed AI could help them adapt. However, adding AI tools alone would fall short. Her goals extended beyond the company’s immediate needs.

She cared deeply about her team’s future and wanted to invest in their growth. Building AI skills would help them succeed in this new era.

The Playbook

Here are the five steps that made this transformation successful. Each step was practical and built on the one before it.

Step 1: Start with Understanding

First, I guided the CMO to understand where everyone stood with AI. Some team members were paralyze because of fear of job loss. Some were already using AI without training or responsible AI guidelines, creating potential risks to the business. We needed to act thoughtfully but quickly.

The CMO set clear expectations early. “This is a learning journey we’ll take together,” she told the team. “While there’s no established playbook for AI adoption, we’ll have guidance from someone who’s helped other teams through this journey. Together, we’ll create our own path forward.”

She addressed concerns head-on. This wasn’t about replacing people. It was about helping them grow. We knew AI skills would be important for their careers, both within the company and beyond. Everyone’s voice needed to be heard for AI to benefit all, not just a few.

This approach paved the way for the team to grow into a 25-human, 20-AI structure, where each has a clear role and purpose.

We created multiple channels for input through open group discussions, 1:1 conversations, regular feedback sessions, and a team survey. Here’s a sample employee survey that you can use and modify as needed.

The survey showed important insights:

This human-first approach resonates with many experienced leaders. As Heidi Melin, a Senior Operating Advisor who guides CMOs of Hellman & Friedman’s portfolio companies go through transformation, notes:

“Working with portfolio company CMOs and collaborating with AI advisors like Liza, I’ve learned that understanding your people must come first.

Once you take time to hear their aspirations and concerns, you can show them a clear vision of a human-AI organization. The breakthrough happens when teams see specific examples of how AI can support each role and function, not replace them. This shifts the entire conversation from ‘what will AI do to us’ to ‘how can we build this together.’

When people feel truly heard and see themselves in this future, they move from hesitation to enthusiasm about the possibilities.“

These results guided our workshop design and overall approach. Being open and clear helped build trust for the next steps.

Step 2: Show What’s Possible

AI has changed how customers search, evaluate, and buy. It amplifies both strengths and weaknesses. Good strategies succeed faster, poor ones fail faster.

Our workshops moved beyond generic AI demos to show how AI could help marketing teams respond to these changes and solve real challenges.

Our initial workshop started with how customer behaviors are changing and ways we need to adapt withn the help of AI. This grounded our AI learning with a purpose–serving our customers the best way we can. It wasn’t simply using AI for the sake of AI.

We inspired what’s possible by covering use cases relevant to specific roles. Doing so jumpstarts people’s learning as they can readily see how AI helps them in their job. I discussed this topic in more detail in my previous newsletter titled Making AI Work for Every Marketing Role with Real Use Cases for Their Jobs.

Here’s just a sampling of AI use cases by function. There are many more.

Here’s our core workshop agenda. Then we conducted function-specific sessions for product marketing, campaign teams, and content creators. This approach helped people see immediate value in their daily work.

We chose our initial AI use cases carefully, focusing on three key criteria that tend to drive the most impact:

1. Tasks that are repetitive, time-consuming, and tactical – especially those that multiple people and functions handle. This immediately lightens the team’s load and frees up time for strategic and creative work.

2. Strategic thinking or processes that benefit from consistency – where AI can help standardize proven approaches and frameworks. It’s democratizing strategic thinking.

3. Use cases aligned with strategic initiatives – strategic initiatives have built-in advantages: clear owners, defined KPIs, allocated resources, and high visibility. With this alignment, we have a better shot at successful adoption. Here’s a template you can use for mapping.

Don’t feel the pressure to do everything at once. Start small and use these guidelines to choose your first AI projects thoughtfully.

Mike Kaput, Chief Content Officer of the Marketing AI Institute captures why this relevance matters:

“Most teams struggle with AI adoption because, a lot of times, people can’t see how it fits into their daily work.

Show a content strategist how AI helps them create better content faster, or a campaign manager how it improves targeting, that’s when the light bulb goes on.

Start with real problems your team faces every day. When they see AI solving those problems, you create the momentum needed for real transformation.”

Step 3: Create Space for Learning

The technology isn’t the hardest part—change management is. We created multiple ways for the team to learn, share, and grow together.

We prioritized responsible AI use from the start, collaborating closely with legal and IT teams to set clear guidelines. Teams learned through practical examples what responsible AI use looks like (see examples of responsible uses here) and potential risks to avoid.

This foundation helped us move quickly while protecting the company’s sensitive information. Here are 10 simple strategies to protect your data when using AI.

We made learning AI part of our job, not an afterthought or extra work. We:

• Protected time for AI exploration

• Created safe spaces for questions

• Set up regular help sessions

Three key breakthroughs showed us this approach was working. The team created custom GPTs (AI tools that users train with specific knowledge and guidelines) to handle various tasks:

• Pitch Deck Evolution – Product marketing managers created a custom GPT that reduced a week-long process to days. Teams now update pitch decks consistently and quickly across all chapters.

• Website Content Project – Eight team members across functions used a custom GPT to create website copy based on wireframes, messaging guidelines, and SEO requirements. We completed months of work in weeks, focusing on editing and consistency.

• Strategic Thought Partner – Teams began using AI to evaluate social media strategies, develop campaign plans, build cross-functional operating models, and plan key 2025 initiatives.

As the team worked more with AI, their roles evolved naturally. AI took on routine tasks. This gave people more time for strategic thinking and creative work.

Team members discovered a new dimension to their roles as builders and guides of their AI teammates, making sure their custom GPTs stayed effective and on track.

The team also came up with innovative ways to use AI that went beyond improving tasks. Here are two examples that stood out:

• Supporting Team Transitions – A content marketer preparing for maternity leave built a custom GPT to support her team while she’s away. This AI assistant gives her teammates easy access to her processes, guidelines, and content library. The goal was smooth handoffs and consistent work quality during her absence.

• Enhancing Team Collaboration – A senior leader created a GPT that captures her unique leadership approach. This AI tool helps her team understand her communication style, decision-making process, and how she handles different challenges. It even offers specific suggestions for working effectively with her in various situations. This helps with improving team collaboration as she takes on expanded responsibilities.

If interested, here’s a sample content creation custom GPT in action and a sneak peek of its instructions.

Step 4: Scale Success Through Systems

With early wins showing value, we created two tracking tools to expand these successes across the organization:

Custom GPT Tracking Template

First, we developed a Custom GPT Tracking System to manage our growing collection of AI tools. Clear tracking helped us scale successful approaches and avoid duplicating efforts.

Our tracking covered:

• Clear ownership and accountability

• GPT objectives and capabilities

• How to access the GPT

• Results and benefits

• GPT use limitations and consideration

Below is the Custom GPT Tracking Template. Feel free to adapt this for your team.

Paige O’Neill, CMO of Seismic, shares why this systematic approach matters:

“Anyone can experiment with AI tools. The teams that really transform are the ones that track what works and bring others along on the journey.

When your AI trailblazers share their wins and help teammates learn, you turn individual experiments into company-wide capabilities. That’s how real learning spreads and creates lasting change.”

AI Tech Stack Template

Building on this foundation, we created an AI Tech Stack Template to guide our technology decisions. We learned that building the right AI stack requires careful planning, not rushing to adopt every new tool.

1. Start with Current Martech AI Capabilities – Many existing platforms have powerful AI features. It’s easier to drive adoption with tools your team already knows. Review your platforms’ product roadmap and connect with account teams to maximize current investments.

2. Add Foundational AI Models – We provided paid versions of ChatGPT and Claude to help teams explore core capabilities. These tools offered a secure environment for teams to experiment and learn. The investment was about $1000/month for the entire team.

3. Fill Specific Gaps – Only after maximizing existing tools did we consider new solutions. The AI vendor landscape will consolidate through M&A. Some vendors may not survive. We evaluated additions based on:

• Clear business need

• Integration with current workflow

• Trial/PoC option and ROI potential

• Security and privacy policies

• Vendor stability indicators (Executive team expertise and track record, quality of investors and funding, defensible moats, customer reviews, market position, and growth trajectory)

This AI Tech Stack Template helps map and manage our AI capabilities across functions.

Our approach to building and tracking our AI capabilities delivered measurable results including:

• Content team creating 2x more high-quality assets

• Campaign performance up 35%

• Lead scoring accuracy at 98%

• 15 hours saved weekly on routine tasks

Check out this carousel for more real and quantifiable results from various marketing teams.

Quick Tip: Need to justify AI investment? A different org I worked with got their entire AI program funded after their custom translation GPT (translated customer-facing documents in 4 different languages) saved tens of thousands in localization costs. Start small, show value, then scale.

Step 5: Expand Your Impact

With strong foundations in place, the marketing team is now starting to expand their influence across the company. As the first team to reach 100% AI adoption in just six months, they’re naturally becoming the company’s AI trailblazers.

Early signs of broader impact are emerging:

• Custom GPTs being adapted for other departments

• Marketing-led AI discussions with other teams

• Cross-functional AI initiatives taking shape

This expansion is already breaking down traditional GTM silos. As Sean McCaffrey, Senior Director of Marketing Strategy and Operations at Cin7, noted in my AI Trailblazer Effect newsletter, the real power of AI emerges when it connects workflows across marketing, sales, and customer success, creating more personalized and cohesive customer experiences.

It’s just the beginning, but their story shows how focusing on people creates lasting success with AI.

Looking Ahead

This journey had clear results. In six months, a lean marketing team built a powerful human-AI organization. They strengthened their foundation by understanding team needs, showing practical applications, creating space for learning, and scaling what worked.

More importantly, they proved something valuable. When teams approach AI adoption thoughtfully and systematically, focusing on people first, the results extend beyond metrics. Teams become more strategic. People develop new skills. Work becomes more meaningful.

They continue to push boundaries, now exploring AI tools with autonomous capabilities like Gemini Advanced’s Deep Research and ChatGPT’s Scheduled Tasks. These experiments with basic AI agents (tools that can work on their own, on our behalf) are opening up new possibilities.

The team will also have to think about the newly launched ChatGPT Operator. This demo shows how this AI agent ordered pizza, made restaurant reservations, and bought groceries. This again changes the buyer behavior and journey.

The team will need to cater to both humans and the AI agents that work on their behalf. They’ll also need to determine how to use agents responsibly in their work.

As they develop and use more AI teammates, they’re proving what’s possible with the right approach.

Where is your team on this journey? How are you building your human-AI organization?

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.

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

Every brand wants trust. Now we can measure what it’s worth: 5× lower acquisition costs, 50% higher retention, 20% premium pricing. But a big change is that AI evaluates your brand before humans do.

Let me share a recent experience that shows why this matters. When I received an invitation to be listed in a business directory, I didn’t schedule calls or review materials. I simply asked AI about the organization. Within seconds, the AI response showed concerning patterns in their business practices. Decision made, before they could even make their pitch.

This is B2B buying in 2024. The value of a strong brand is no longer just measurable, it’s immediate.

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.

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 Real Impact of Brand Trust

“We need more brand awareness.”

“Our brand needs a refresh.”

“Brand building is important, but we can’t measure the ROI.”

Sound familiar? For years, marketing leaders have struggled to quantify the business value of brand investments. Board meetings and budget discussions often end with brand initiatives being viewed as a cost center rather than a value driver.

But what if we could measure it and show, in real numbers, how brand strength drives business value?

Amy Heidersbach, CMO of DHI Group Inc., has spent years proving that we can. Working with data from Harvard Business Review, McKinsey, Bain & Company, and other leading firms, she’s developed a framework that quantifies brand impact.

Our research, combining AI analysis of thousands of industry data points and market studies, validates these metrics across the B2B landscape. We’ve partnered to make this framework accessible through an interactive calculator.

“For too long, brand value has been treated as intangible – important, but impossible to measure. That’s a narrative we need to change.

The data is clear: strong brands drive measurable business outcomes. And in the AI era, these impacts are becoming even more pronounced and measurable.

What used to take months or years to demonstrate can now be seen more quickly through AI’s lens.”

Here’s what the numbers tell us for a sample SaaS company targeting the mid-market segment. See the demo below:

1. Customer Acquisition Becomes Dramatically More Efficient

Strong brands can experience up to 5× lower CAC (Customer Acquisition Cost). If you’re currently spending $1,000 per new customer, that’s an $800 savings each time. With your current user base of 100,000 monthly active users, applying this to just 10% of new acquisitions could mean $800,000 in lower acquisition costs annually.

2. Retention and Loyalty Create Compounding Value

Strong brands see 50% higher retention. With your current 85% retention rate and 10,000 premium users paying $100/month, improving retention could generate over $5.1 million in additional retained revenue over the course of the year. Plus, loyal customers are 4× more likely to refer others, with potential referral revenue from premium users who convert at your 10% rate.

3. Pricing Power Gives You More Options

Strong brands can often charge up to 20% more for their services. With your 10,000 premium users paying $100 per month, that extra 20% can translate to $2.4 million in additional annual revenue through premium pricing power alone.

The revenue impact is just the start. Strong brands also:

• Drive 2x higher conversion rates (with top B2B companies achieving up to 11.7% conversion rates)

• Contribute 20-30% of company market valuation (as seen across S&P 500 companies)

• Reduce talent acquisition costs by 43% while improving employee retention by 28%

The SaaS Multiplier Effect kicks in when customers trust you. They spend 25-40% more on additional features, creating a virtuous cycle where user growth leads to exponential value creation.

Want to calculate these numbers for your business? Try our calculator.

I created this calculator with AI (Claude Pro Sonnet 3.5), using simple instructions and no code (Yes, this engineer, many decades ago, turned GTM leader can’t code 😉).

In using the calculator, note that the results represent potential improvements if each brand impact is realized fully. In practice, results may overlap, and brand gains tend to build over time rather than immediately. Use these results as a guideline for possible outcomes, not a guaranteed one-year forecast.

To Amy’s point, the time to lean in on brand is now. The numbers above show the baseline value of a strong brand. But here’s what’s exciting: AI amplifies and accelerates all these KPIs. Let me show you how.

How AI Changes Everything

Yesterday, companies controlled their story through marketing and sales. They built their brand one meeting at a time. Today, AI evaluates your company before any interaction starts. 

Sure, people should verify what AI tells them. But let’s be honest: how many actually do? It’s like Google search results – we know there’s more beyond page one, but we rarely look. When AI gives an answer about your company, that often becomes the only answer most people see.

Here’s what we’re seeing:

• Speed of Impact. I asked AI about a business directory invitation. Within seconds, it showed poor BBB ratings and concerning business practices. Decision made. No calls needed. This happens thousands of times daily across B2B buyers. See my entire conversation with AI.

• Trust at Scale. While checking board game reviews at Target, I watched AI instantly verify trust signals. If buyers expect this level of verification for $30 games, imagine their expectations for six-figure B2B software contracts. Here’s the AI exchange.

• Earlier Influence. Universities now get evaluated through AI before the first campus visit. The same happens in B2B. Your brand opens or closes doors before your sales team knows about the opportunity. See my full collaboration with AI.

AI is an amplifier. It takes your brand’s existing signals, good or bad, and multiplies their impact. Strong brands see their advantages compound faster. Weak brands find their challenges exposed more quickly.

Godard Abel, CEO of G2, sees how this shift transforms business growth.

“Companies can no longer rely on traditional marketing messages and sales conversations to build brand and trust.

Your prospects now use AI LLMs to synthesize all information about your company in real time: website content, educational resources, customer reviews, social media discussions, employee feedback, and community engagement.

Market leaders aren’t just telling a great story. They’re focusing on creating amazing customer experiences that those customers share with the world across digital channels. That authentic customer feedback loop is what drives growth in today’s market.”

In the end, AI creates a faster path to either success or failure.

The AI Multiplier Effect

Here are three ways AI changes the speed and scale of brand impact:

• Customer Acquisition flips completely. AI recommendations put you on shortlists before competitors know about the opportunity. The typical 5x savings in acquisition costs is just the start. Your prospects now come pre-qualified, asking about solutions instead of credentials.

• Sales Velocity jumps forward. No more long cycles explaining who you are. Buyers arrive having seen your customer success stories and industry validation. The conversation starts at “how can we work together?” instead of “why should we trust you?”

• Revenue Impact compounds naturally. Strong brands command 20% higher prices because buyers see proof before discussing cost. Your customer success stories and validated outcomes show up in every AI search. Customers buy more features because they start with trust, not skepticism.

Where Do You Stand?

This new reality means you need to know exactly where your brand stands. Here’s a simple way to think about it:

The matrix shows four possible positions. Each one means something different in the AI era:

• Market Leaders combine high trust with strong product-market fit. AI shows their credibility and customer success stories automatically. They don’t just stay ahead. They pull further ahead.

• Hidden Gems have great products but low trust signals. Even with strong offerings, they might not show up in AI recommendations. Their focus should be building trust markers that both AI and humans can verify.

• Missed Opportunities have strong brand trust but haven’t aligned their product value. Their good reputation buys them time to improve, but they need to move fast. AI increasingly exposes the gap between brand perception and product reality.

• Danger Zone companies face tough choices. Low trust combined with poor product-market fit creates a compound problem as AI amplifies both weaknesses. They need to rebuild fundamentals before scaling.

Alexandra Gobbi, CMO of Veracode, understands how technology companies move between these positions.

“Getting product-market fit or building trust alone isn’t enough anymore. The most interesting shift I see is how quickly companies can move between these quadrants.

A startup with a great product but low trust can rapidly become a market leader by consistently proving their value. Meanwhile, established brands can’t coast on reputation – AI makes it clear when your product isn’t keeping up with market needs.

Success comes from treating trust and product excellence as one connected goal.”

Want to know where you really stand? Ask AI what the market thinks about your company. You’ll get an unfiltered view of your product-market fit and trust signals. The answers might surprise you, but they’ll show you exactly where you are on this matrix and what to fix first.

Making This Practical

1. First, know your numbers. Use our calculator to set your baseline metrics for price premiums, customer acquisition costs, and retention rates. You can’t improve what you don’t measure.

2. Next, see what AI says. Ask ChatGPT, Claude, Gemini, Perplexity, and other AI assistants about your company. What key insights are shared? What strengths get highlighted? What concerns come up? This is what your prospects see when they research you.

3. Finally, build trust signals that AI can find and verify. Start with customer proof. Share success stories with real metrics, customer reviews that show specific value, and case studies with clear outcomes. These give AI concrete evidence of your impact.

Add expert validation to strengthen your position. This includes recognition from industry analysts, mentions in research reports, and recommendations from respected voices in your field. AI picks up these third-party endorsements and uses them to validate your claims.

Keep your digital presence strong and consistent. Create helpful content, engage with your community, and maintain a clear message across all platforms. This helps AI build a complete picture of your value.

Want to dive deeper into the data behind these insights? I’ve used AI (Gemini Advanced Deep Research) to analyze hundreds of industry reports, academic studies, and market data. Here’s the research report for your reference.

Also check out these practical guides on optimizing your AI search strategy (an important part of your overall brand trust equation):

• Beyond AI-Generated Content: A Guide to Standing Out When 50% of Web Traffic Disappears

• Make Your Brand Sourced and a Top Result in AI Search: Practical Strategies for Marketers

Note that in the AI era, your brand value isn’t just what you say it is. It’s what AI tells everyone else it is.

Looking Ahead

AI isn’t changing what makes a great brand. It’s changing how fast the world notices. Great products, happy customers, and genuine value still matter most. AI just makes sure everyone knows about it sooner.

Think of AI as your brand’s megaphone to the market. Build something worth talking about, and AI will spread the word. Create real value, and AI will help you prove it.

Your brand has always been valuable. AI just makes it worth more.

Instead of just asking how to show up in AI, maybe we should ask: Who do we want to be when AI tells our story?

What did you discover when you asked AI about your brand? What surprised you most? Let me know in the comments.

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

Content creation is changing fast. AI makes it easier than ever to create good content at scale. At the same time, AI search tools are changing how people find information, often giving them answers without clicking through to websites.

Gartner predicts that we could see 50% less web traffic as a result by 2028.

So how do we create content that stands out when:

• Everyone has access to powerful AI writing tools

• More content is competing for attention

• The ways people find and consume content are shifting

I’m seeing successful teams rise above the noise by focusing on three key strategies:

1. Creating content AI search can’t ignore

2. Finding stories others miss

3. Telling authentic stories

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 it here.

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.

Create Content AI Search Can’t Ignore

We’re in a new era of content discovery. When people use AI search, they often get answers without visiting websites. The opportunity is when AI tools cite their sources.

When your content is truly valuable, AI systems will reference it and send interested readers your way. You might get less traffic but visitors are more qualified.

You’ll win at AI search by being truly helpful, not by trying to game the algorithms. Share clear steps that work. Back up your ideas with real examples. Show what you’ve learned from doing the work.

When you deeply understand your target audience, you can create content that answers their questions directly.

Want to learn exactly how to make your brand and content relevant in AI search? My previous newsletter titled “Make Your Brand Sourced and a Top Result in AI Search: Practical Strategies for Marketers” shows you how to:

• Identify your audience’s key questions

• Track how AI systems find and share content

• Build content that naturally rises to the top

Below is a sample of how six AI assistants responded to an inquiry. It gives insights into what content bubbles up and the sources cited. Doing this type of research using AI is just one of the steps I cover in the newsletter referenced above.

Chris Andrew, CEO of Scrunch AI, discusses the importance of understanding buyer intent and not focusing on trying to game the AI search system.

“Don’t chase algorithms or stuff content with keywords.

Focus on clear and concise answers.  AI crawlers are designed to prioritize content that is structured, relevant and clear.

When your content is truly valuable, both AI systems and humans will naturally want to reference it.”

Find the Stories Others Miss

Most teams focus on creating more content. Smart teams create different content. Here’s how to do it with AI.

I built a special version of ChatGPT (called a custom GPT or custom Generative Pre-trained Transformer) that’s trained to find new angles on common topics. Think of it as your personal content brainstorming partner that knows your industry and audience. I named it Persona- & Buyer Stage-Specific Content Creator.

Here’s how it works.

Train it with your knowledge about:

• Customer personas and journeys

• Positioning and messaging

• Industry trends and beliefs

• Brand guidelines

Then ask it to find unique stories that:

• Challenge common beliefs not backed by data

• Reveal overlooked but important areas

• Connect unexpected dots across industries

• Offer fresh perspectives on trending topics

• Offer counter-narratives that receive less coverage

Collaborating with AI in this way not only gives us new ideas, it also jumpstarts our thinking quickly.

The short video below shows the custom GPT in action and a behind-the-scenes peek at its instructions.

A master of content and digital marketing, Andy Crestodina, is trailblazing in how to stand out in a sea of average AI-assisted content.

“The two future-proof, highly differentiated formats for content are original research and strong opinion. They’re special partly because AI can’t produce them… but AI can definitely help you find those opportunities.

Ask your favorite LLM which common assertions are unsupported with data (your next research project) or what counter narratives you’re audience would find provocative (your next thought leadership post).

Now more than ever, original research and thought leadership are winners in content marketing.”

Tell Stories That Connect

Let me share a real example of storytelling.

A few years ago, I wrote about an incredible African adventure with 15 dear friends from across the country. We tracked mountain gorillas in Rwanda’s Virunga Mountains and saw the Big Five in South Africa’s largest private game reserve.

But the most powerful stories came from the people we met along the way.

One moment stands out. Our guide Francis said something that changed my perspective: “The gorillas welcomed you into their home. Now, it’s on you to amplify their voice.”

It’s amazing how our travel experiences turn us into storytellers. Check out the full story of our African adventure with business storytelling tips here.

This journey taught me three key principles about creating content that connects:

1. Go Beyond What We Make to What We Make Possible – Don’t just talk about products and features. Show how technology helps teams find cures for diseases, create new ways of learning, improve how we work and live, and more. Make it real by showing how to get there and our role in it.

2. Make the Customer the Hero and Us, the Guide – People don’t buy what they want. They buy what they want to be – an innovator, game changer, generous leader, inspiring mentor. Be like Yoda to Luke Skywalker. Encourage, enable, and empower your customers to achieve their potential.

3. Educate, Entertain, Amaze, and Inspire Action – It’s not enough to educate and entertain. You need to amaze your audience by showing the journey: the starting point, challenges overcome, and final impact. Then inspire action by helping people see themselves in stories about topics they care about.

Karrie Sanderson, a former CMO and exceptional brand marketer, believes in the power of storytelling.

“Marketing isn’t just about selling—it’s about creating meaningful stories that speak to both the mind and the heart.

Every story should bridge practical solutions with genuine human experiences. Marketers should recognize that behind every interaction, there’s a real person seeking not just a product, but a solution that understands their deeper needs and aspirations.

Great brands don’t just deliver functional benefits; they create emotional connections with their customers.”

Your Next Steps

You don’t have to tackle everything at once. Start with one small step in each area:

• Look at your top three customer questions. Create content that answers them completely, with real examples from your experience.

• Choose one common belief in your industry. Dig deeper to find a different angle that others haven’t covered.

• Pick one customer story that shows your bigger purpose. Share not just what happened, but why it mattered.

Remember this golden rule of marketing, especially in the AI era:

Which of these three approaches resonates most with your content strategy? I’d love to hear about your learnings and results.

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

Every team achieving early success with AI has something in common: Trailblazers. These are the people who spot problems AI can solve and take action. They show up in any department. They start small and get real results.

A global marketing team cut translation time from weeks to days. A product marketing team saved a full week’s worth of work updating pitch deck sections. These wins inspire others to follow. By using tools like custom GPTs and AI-powered martech tools, trailblazers don’t just solve problems, they show the whole team what’s possible.

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 it here.

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.

How AI Trailblazers Drive Change

People drive AI success. In every marketing team I work with, certain people step up naturally as change agents. We call them trailblazers. (More on AI adoption categories of people here.)

These pioneers spot AI opportunities fast. But here’s their real superpower: they show others what’s possible through quick wins. They prove that AI, when used responsibly, can make work both better and more meaningful.

You’ll find trailblazers in surprising places. I’ve seen content strategists lead the charge in one company. In another, it was the marketing ops team. Their job title doesn’t matter. What counts is their drive to solve real problems, curiosity, and growth mindset..

Proof in Numbers: From AI Workshops to Wins

In our applied AI workshops, we start with the big picture: how AI is reshaping customer behavior and market dynamics. We inspire how to adapt to those changes with real-life AI use cases relevant to each marketing function.

Then we get even more practical and ramp the impact. Workshops are just the beginning. We guide teams as they apply AI to their own challenges, advising them on approaches to solve the problem with AI, considering the right tools, and using it responsibly.

The goal isn’t just to show what’s possible, it’s to help teams become good at using AI tools themselves and guiding AI with their unique knowledge and expertise.

Let’s look at how one team turned inspiration into real impact below:

The results came fast. After just a few two-hour workshops, the team was using AI in 15 different ways. Team members started finding their own uses for AI in both strategy and daily tasks.

Growth Marketing and Product Marketing saw the biggest wins. They saved time, cut costs, and produced better work. Best of all? Teams had more time for creative, strategic thinking.

For more examples of quantifiable benefits across marketing functions, check out our recent analysis here.

Jill Axline, Senior Director of Global Marketing at Morningstar, believes in success breeding success, starting with these AI champions. She is a trailblazer herself.

“The key to successful AI adoption is creating an environment where early adopters can thrive while helping others see the possibilities.

Champions become the best teachers because they focus on solving real problems that their team faces in their individual roles. They are given the support, resources, and time to explore, do their best work, and bring others along.”

Scaling Success: Trailblazers Share Their Wins

Let me share how teams use custom GPTs – specialized AI tools you can build for specific tasks – to transform their work. These tools combine OpenAI’s technology with your team’s expertise and guidelines. Here’s what two teams achieved:

Translation and Localization Success

A global marketing team had a common challenge: translating and localizing content into eight languages. The process was slow and expensive, taking weeks to complete.

Two team members spotted an opportunity. They built custom GPTs for English to German and French translations, using their brand guidelines and local market expertise. Within a week, they had a working solution.

Native speakers with subject matter expertise review all AI translations and regularly update the GPTs with their feedback. This human oversight keeps quality high while still delivering speed.

Translation time dropped from weeks to days, saving thousands in agency fees.

Their success spread quickly. Other marketing teams saw the potential and requested their own AI tools. The ROI easily justified more AI licenses.

Product Pitch Deck Creation

Another win came from Product Marketing. A trailblazer tackled pitch deck creation using custom GPTs. The goal was to build targeted decks quickly, with the right message for each persona.

They fed the GPT everything it needed while protecting sensitive information: product details, messaging, persona information, customer quotes, and brand voice. Soon, multiple PMMs were using it for their sections. One PMM saved a full week’s work updating their product sections!

This success sparked new ideas. The team is now planning to build GPTs for FAQs, battle cards, one-pagers, and sales training. This frees up PMMs to focus on deeper work like understanding customer needs, tracking competitors, and crafting GTM strategy.

A big customer advocate, Melissa Carey, Director of Product Marketing at DHI Group, Inc., believes in the responsible use of AI as a teammate to not only make PMMs more efficient but also more effective.

“Product Marketing’s deep understanding of customers, messaging, and the buying journey provides a strong foundation for AI tools. We can use this knowledge to create custom GPTs that maintain consistency across all customer touchpoints.

Our work naturally guides the development of AI tools to help create pitch decks, FAQs, and sales materials, ensuring that every piece of content speaks directly to customer needs.”

Building Custom GPTs: Scaling Trailblazer Impact

Many trailblazers multiply their impact by creating custom GPTs for their teams. These AI tools carry your team’s knowledge and best practices.

Here’s how teams build effective custom GPTs:

1. Start with a clear purpose

2. Add conversation starters to guide users

3. Feed it your key documents – brand guidelines, messaging, templates

4. Give it specific instructions for creating and delivering work

5. Test, refine, and update regularly based on human oversight and feedback

Note that GPTs need ongoing maintenance and human oversight. Teams regularly review outputs, catch mistakes, and update the tools with their expertise. This keeps the GPTs accurate and aligned with your standards.

Below is a demo of both how a sample custom GPT works and how it’s built. Our Content Topic Creator GPT helps teams develop content ideas for specific buyer personas.

The demo shows how the GPT guides users through tasks and includes a behind-the-scenes look at its instructions and knowledge documents.

Remember: GPTs can do much more than create content. Teams use them to analyze data, derive insights, automate tasks, develop and assess strategy, and personalize experiences. The key is matching the tool to your team’s needs.

Marketing Team 2.0: Where Trailblazers Are Leading Us

What does the future marketing team look like? Our trailblazers are showing us that it’s a blend of human talent and AI support.

The org chart below shows how teams are evolving. AI tools, both custom GPTs and AI-powered martech, support specific marketing functions. But these tools also work across teams, connecting workflows.

Humans lead with strategy and creativity. AI handles the tasks that slow teams down.

Sean McCaffrey, Director of Marketing Operations at Cin7, believes in the even greater potential of AI when used to connect workflows across teams.

“I started by using AI to identify our most engaged accounts from marketing data. That worked well, but I saw bigger possibilities.

Now we’re connecting those insights to help sales personalize their outreach. We’re also sharing what we learn from sales conversations with customer success for better onboarding. What began as one focused solution has become a connected workflow.

The key is to solve immediate needs while staying open to broader opportunities.”

What Sean described is just the beginning of AI enabling connected and personalized experiences for buyers. AI will push companies to break down Marketing, Sales, and CS silos. Read my newsletter on AI is Raising Customer Expectations: How to Unify Go-to-Market Workflows for practical insights on this topic.

These teams track and manage their AI tools systematically. Here’s what good tracking looks like:

1. Every AI tool has a clear owner

2. Teams document what works (and what doesn’t)

3. Learning gets shared across departments

4. Results are measured in business impact

Below is a template we use to track custom GPTs. The first entry shows you what a completed entry looks like. Feel free to adapt this for your team.

Want to learn more about this Marketing Team 2.0 vision? Check out my newsletter on this topic.

The Path Forward: Your Trailblazers Are Ready

AI success starts with trailblazers. They see what’s possible and help others get there. Your trailblazers are ready, they just need the right environment to thrive.

Here’s how to accelerate AI adoption in your marketing team:

1. Start with inspiration – show teams how AI helps them adapt to changing customer behaviors

2. Identify your natural trailblazers

3. Give them room to experiment and prove value

4. Let them build tools like custom GPTs to share their expertise

5. Support them as they bring others along

6. Build toward that Marketing Team 2.0 vision

Your trailblazers can lead the way to something powerful: a marketing team that’s both more capable and more human. Give them the support to make it happen.

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.