GrowthPath Partners LLC

Empowering Purpose-Driven Growth

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AI Video Explainers: Making Complex Ideas Click

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AI video explainer quality just got noticeably better.

I’ve been using NotebookLM to create podcast versions (with AI hosts) of my newsletters for months. I’ve also been testing their video feature, a slideshow walkthrough with narration.

With the enhancements, I’m now including an 8-min AI explainer video below alongside the 12-min AI podcast for my latest newsletter on how AI is reorganizing GTM teams around customers, not departments.

Here’s what stood out:

  • It tied McKinsey’s research to real case studies and made the Journey Teams model feel practical, not theoretical.

  • The graphics explained the frameworks clearly and were visually appealing.

  • It focused on the most important point: you don’t have to evolve your organization overnight. Start with one painful workflow, fix that handoff, build from there.

Most leaders need to hear that third one. Org transformation sounds overwhelming. The video made it feel doable by showing the crawl-walk-run approach. Start small, prove it works, build momentum.

I still reviewed every second for accuracy. AI is good at pulling information together but can’t replace knowing what GTM leaders actually need to hear.

Now I have another format to reach different learning styles and time constraints. Links in comments for the video (8 min), podcast (12 min), or full written newsletter with frameworks and case studies.

Pick the format that fits how you actually learn.

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Beyond ‘Ask Anything’: Train Your Team to Fly with AI

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You handed out ChatGPT with a text box that says “Ask anything,” ran a basic AI training session, and expected your team to build cross-functional AI workflows that they orchestrate.

That’s the Grand Canyon, not a strategy.

Many people still look at ChatGPT and see a fancy search engine. Or an intern that hallucinates. Or a Q&A machine that makes things faster but not better.

Basic training doesn’t change that. Teaching your team how to prompt without showing them what’s actually possible just means they’ll write better queries to the search engine.

ChatGPT speaks natural language. You can draft strategy, analyze patterns, build frameworks, test ideas, challenge assumptions. It’s a thought partner you guide, not just a faster way to Google.

Nobody’s showing them how to build AI teammates (e.g., custom GPTs) for specific tasks and connect them together to create an end-fo-end workflow.

So they’re stuck on one side of the Grand Canyon, thinking they need to walk across on foot. When really, they could fly.

Show your team what’s possible. Share real examples. Walk through use cases that matter for their role. Put hands on keyboard to build confidence. Teach them to use it responsibly and strategically. Give them the space to learn. Let them reimagine new work that wasn’t possible before, not just make old work faster.

Once they see and experience it, they’ll soar.

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AI-Driven Workflows: The Shift to Customer Outcomes

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

Published on 2025-06-12 13:04

The gap between the job to be done and where expertise resides is shrinking. AI doesn’t care about silos. Neither do customers. They care about outcomes.

Companies are just beginning to build cross-functional workflows that align to customer outcomes rather than departmental goals. The enablement and governance to support this are emerging now. These early moves are showing new possibilities for how teams organize and how roles evolve.

McKinsey found that workflow redesign has the biggest effect on bottom-line results from gen AI. Yet only 21% of organizations have fundamentally redesigned how work flows across teams.

Based on what I’m seeing with GTM teams, four stages are emerging:

  • Stage 1: Traditional Org + AI Tools →

  • Stage 2: Traditional Org + AI Teammates →

  • Stage 3: Connected Workflows →

  • Stage 4: Work Chart Organization

Most companies operate at Stage 1 or early Stage 2. A small number are building toward Stage 4, organizing around customer journeys instead of departments.

Key insights:

  • ➡︎ Journey Teams own complete customer outcomes (Net New Revenue + time-to-value, Net Retention Rate + customer satisfaction). Everyone shares the same metrics instead of optimizing for departmental goals.

  • ➡︎ A Shared Expertise Pool provides unified data, AI systems, and brand narrative that both Journey Teams build from. No more handoffs between disconnected functions.

  • ➡︎ You don’t need to reorganize everything at once. Start by connecting one painful workflow across teams. Prove the model works. Build momentum.

  • ➡︎ There are compelling results: 75% faster content creation, 98% lead qualification accuracy, 2-3X campaign engagement from teams building connected workflows.

  • ➡︎ Roles are evolving. Marketing ops professionals are becoming infrastructure enablers. Integrated campaign managers are becoming GTM journey orchestrators. People are building capabilities that didn’t exist before.

Thank you to Heidi Melin (6X CMO, Senior Operating Advisor at Hellman & Friedman) and Sarah Gavin (Chief Communications Officer and Acting CMO at Zendesk) for sharing their insights on what this shift means for GTM leaders.

See the full framework, real case studies with results, and a 5-step implementation guide in the newsletter below.

I created 8-min AI video explainer and 12-min AI podcast versions (links in comments) of the newsletter using NotebookLM to cater to different learning styles. I reviewed these AI outputs personally for accuracy and to ensure responsible use. Check them out. This tech is advancing dramatically to help with learning.

Would love to hear your thoughts. If you found this helpful, please subscribe and share.

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AI: Why Customer Journey Teams Are the New KPI

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

Published on 2025-06-12 13:04

AI makes departmental KPIs obsolete. Marketing optimizes for MQLs. Sales optimizes for deals closed. CS optimizes for retention. The customer experiences the gaps between them. Those gaps are now visible to buyers in real-time.

Teams organizing around customer outcomes are rewriting how success gets measured.

Instead of separate departmental targets, the entire team owns the customer outcome end-to-end.

  • New Customer Journey Team owns Net New Revenue AND time-to-value (e.g., getting customers to see value within 90 days)

  • Growth Customer Journey Team owns Net Revenue Retention AND customer satisfaction (e.g., maintaining 90%+ CSAT while expanding revenue)

When everyone shares the same metric, the handoffs that break customer experience disappear.

One global cybersecurity company built cross-functional workflows this way. Marketing ops evolved into the infrastructure team providing unified data, AI systems, and governance.

Teams stopped optimizing for their function and started optimizing for the customer. Campaign engagement improved 2-3X.

Tomorrow’s (Thu, Nov 13) newsletter shows the full AI Work Chart Maturity Model, how Journey Teams structure actually works, the three capabilities that determine who can make this transition, and practical steps to start without reorganizing everything at once.

Subscribe to Practical AI in GTM (see link in comments) to get it directly in your inbox.

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Redesign Workflows for AI: Ditch Silos, Delight Customers

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Only 21% of companies have redesigned their workflows for AI. The other 79% are still organizing around departments while their customers demand seamless experiences across teams.

McKinsey analyzed 25 organizational attributes and found workflow redesign (not tools or models) has the biggest effect on EBIT impact from gen AI.

Microsoft’s 2025 Work Trend Index confirms it. “Teams form around goals, not functions, with AI helping employees do more and work faster.”

Harvard studied cross-functional teams at P&G using AI and found: “You stop caring as much about the normal boundaries of your job.” When AI helps people think beyond specialized training, traditional silos break down naturally.

Based on these three independent studies, the gap between the job to be done and where expertise resides is shrinking. AI doesn’t care about silos. Neither do customers.

Companies are just beginning to build cross-functional workflows aligned to customer outcomes. The enablement and governance frameworks to support this are emerging now.

My upcoming newsletter on Thu, Nov 13 breaks down the AI Work Chart Maturity Model showing the four stages of this transformation, what Journey Teams look like in practice, real results from companies making this shift, and where to start without reorganizing everything at once.

Subscribe to my newsletter (Practical AI in Go-to-Market) to get it directly in your inbox. See link in the comments. I’ve also included links to the 3 research studies.

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