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5 Battle-Tested Playbooks for AI Transformation
Skip the theory. Michael Domanic shares what actually works when deploying AI at scale.
Hi there,
This week's Just Curious delivers five (5!) battle-tested AI transformation playbooks from Michael Domanic, Head of Generative AI Business Strategy at UserTesting. Michael has successfully led company-wide AI adoption across a 300+ person organization, creating measurable business impact while navigating the cultural and operational challenges that derail most AI initiatives.
Plus in this edition: I put AI skepticism to the test with Just Curious AI (powered by insights from 100+ AI experts), and share my current favorite thing: Tom Blomfield's brilliant take on "vibe coding" from Y Combinator's Startup School. While the term might feel like a misnomer, his insights about how AI coding tools will ultimately amplify experienced developers' creative output (rather than just help beginners) perfectly captures where we're headed.
📣 Our AI Accelerator for Agencies (in 3 weeks!)
I spoke to 200+ AI experts and practitioners over the past 3 months, and a clear divide is emerging between agencies that are capitalizing on the AI opportunity and those that are still figuring it out.
The leaders who are moving fast are:
Using AI to deliver better creative work faster (and charging accordingly)
Streamlining operations with AI tools that actually improve margins
Standing out to clients as the agency that 'gets' AI
With fall coming up, I'm hosting a small, private conference on July 16 for senior agency leaders who want to be in that first group.
The format: Five focused workshops led by practitioners who've actually implemented AI at scale.
Worth a Tuesday afternoon?
🚀 5 Strategic AI Transformation Playbooks from UserTesting's Michael Domanic
Michael Domanic is Head of Generative AI Business Strategy at UserTesting. Michael has successfully led company-wide AI adoption across a 300+ person organization, creating measurable business impact while navigating the cultural and operational challenges that derail most AI initiatives.
The following five playbooks are sourced from our interview with Michael Domanic.
📌 Playbook #1: Appoint a Dedicated AI Transformation Leader
Why It Matters: AI transformation isn't a side project. It requires dedicated leadership with a unique skill set.
The Four Essential Traits:
AI Tool Fluency: Deep understanding of current capabilities and how they connect to business value
Cross-Functional Business Knowledge: "You're not an expert in HR, but you understand what HR does. You're not an expert in marketing, but you know what marketing does."
Proven Execution Track Record: Someone who consistently delivers results when given important initiatives
Deep Creativity: "We've never deployed a technology like generative AI before... You need someone who can think creatively about translating abstract technology into something tangible."
Quick Win: → Evaluate your team against these four criteria within two weeks. This person needs entrepreneurial thinking. They're essentially building something from nothing.
📌 Playbook #2: Start with Information Fragmentation Problems
Why It Matters: Every organization loses significant time hunting through scattered knowledge repositories. This creates an immediate, measurable win.
Action Steps:
Quantify the Pain: Calculate exactly how much time employees spend searching for information across different systems
Create a Custom Knowledge GPT: Pull together dispersed knowledge sources (Confluence, Salesforce, internal docs) into a single AI interface
Measure Impact: "It was really clear to us that we were saving a ton of time... We were also increasing the access to knowledge for folks."
Quick Win: → Run a time audit this week: How many minutes do key employees spend daily searching for information? Build a simple custom GPT around your most-accessed internal documents.
📌 Playbook #3: Deploy the "Early Adopter → Virality" Strategy
Why It Matters: Bottom-up adoption creates sustainable transformation that doesn't feel imposed from above.
Action Steps:
Handpick Strategic Early Adopters: Choose people already showing interest, not just willing participants
Create Controlled FOMO: "We handpicked individuals... It created a little bit of virality. It created a little bit of FOMO for the individuals who didn't have access."
Amplify Success Stories: Use all-hands meetings and lunch-and-learns to showcase early wins
Enable Knowledge Sharing: Create dedicated Slack channels for experimentation and learning
Quick Win: → Identify 5-10 people who are already experimenting with AI tools. Give them enterprise access first and ask them to share what they discover.
📌 Playbook #4: Balance Top-Down Vision with Bottom-Up Innovation
Why It Matters: Successful AI transformation requires both executive clarity and grassroots experimentation.
The Dual Strategy:
Top-Down Requirements:
CEO regularly communicates why AI adoption is strategically crucial
Clear governance policies for data usage and security
Cross-functional AI working group with legal, security, and business leaders
Bottom-Up Enablement:
"We have fully democratized the building of custom GPTs throughout the organization"
Safe spaces for experimentation within governance guardrails
Regular sharing of lessons learned and interesting discoveries
Quick Win: → This week: CEO sends company-wide message about AI importance. Next week: Form cross-functional governance group. Month two: Begin controlled rollout to early adopters.
📌 Playbook #5: Focus on High-ROI Use Cases First
Why It Matters: Not all AI applications are created equal. Start where you can demonstrate clear business value.
Priority Areas for Most Organizations:
Sales & Go-to-Market: Enhanced prospecting, proposal writing, customer communication
Software Development: Code efficiency, documentation, testing processes
Repetitive Workflows: "GPTs are really great at any kind of repetitive workflow that you might be doing"
Strategic Work: Using AI as a thought partner for high-level decision making
Michael's Examples:
Usage analytics GPT that processes vendor data dumps and creates executive reports
OKR creation GPT: "You shouldn't have to be good at writing OKRs. That's a distraction from the thing that you're hired for"
Quick Win: → List your team's 10 most time-consuming repetitive tasks. Pick the one with clearest ROI potential and prototype a solution this month.
🎯 The Bottom Line:
Michael's approach proves that successful AI transformation requires three things: dedicated leadership with the right skill set, strategic focus on measurable pain points, and a balanced top-down/bottom-up approach that creates organic adoption.
The "Do More with More" Philosophy: "We're far more interested in doing more with more, right? Everybody saves 12 hours of their week. Now we can focus on other areas of the business, other challenges."
🛠️ Start Today:
Choose one playbook above and take the first action step. Michael's experience shows that AI transformation succeeds through consistent, measured progress, not perfect planning.
🤿 Dive Deeper:
Full Interview → How UserTesting Drove AI Adoption
Key Insight: How to Measure and Maximize AI ROI: Insights from UserTesting's Michael Domanic
Quick Read: The Four Traits of Effective AI Leaders
🙋Ask Just Curious AI: Can AI Actually Create Real Business Value? 🤔
SMB leaders often share their doubts, so I put this skepticism to our Just Curious AI, which is powered by the perspectives of almost 100 Just Curious AI experts.
Q: I'm skeptical about whether AI can help me create value. Convince me I'm wrong.
Here's what Just Curious AI had to say:
I get the skepticism. AI’s been hyped to the moon. But when thoughtfully applied, AI can absolutely create value for SMBs. Let me break it down with real-world examples:
1️⃣ Start with tangible problems:
AI-driven scheduling solutions optimize appointments, reduce no-shows, and save your team hours each week.
2️⃣ Understand your customers better:
Use AI to analyze feedback, social media interactions, and sales data to discover valuable insights.
(As recommended by Justin Massa from Midwest Quality Consulting.)
3️⃣ Compete smarter, not harder:
Leverage AI to amplify your unique SMB strengths, solving customers’ pain points better and faster.
(Insight by Robert Hatta from Ten-X Talent.)
4️⃣ Measurable revenue impacts:
Implement AI for personalized marketing and inventory management, directly boosting conversions and reducing waste.
Bottom line: You don’t have to overhaul everything at once. Pick one pain point, test a small AI solution, measure, and scale from there.
🌐 My Favorite Thing: How To Get The Most Out Of Vibe Coding | Startup School
I’m not sure this is for me to say but vibe coding feels a bit like a misnomer.
While it initially benefits two groups—non-technical users who can quickly create simple products, and experienced developers who gain productivity—the deeper impact will likely emerge from what it unlocks for seasoned engineers.
By automating repetitive and routine tasks, experienced developers are empowered to focus more on strategic architecture, innovative designs, and higher-value activities. Over time, this shift could significantly amplify their creative output, shaping the future of software development far beyond the initial ease-of-use benefits for casual users.
Enjoy it.
🚀 See You Next Week
Curious about AI?
Check out Just Curious. Ask questions of our AI. Or just reply here and I’ll use our network to help you out.
See you next week,
- Stu
Ps. Please forward this to anyone curious about AI!