We’re continuing our Moments-Based Marketing series—and Step 4 tackles one of the most important questions teams are facing right now: How to actually use AI day to day without losing clarity, confidence, or creativity.
Quick rewind:
- Step 1 helped us get our data in order.
- Step 2 pushed us to rethink how we design journeys.
- Step 3 tackled content at scale.
In Step 4: Put AI to Work with Human-Led Expertise, the conversation shifted from AI potential to AI practice.
We were joined by Shweta Puri, Sr. Product Manager, Marketing Technology at Nextdoor, Erin Kelsh, VP of Messaging Solutions & Innovation at Merkle, and Julia Erlandson Thiesen, Director of Product Management at Iterable
- Shweta shared how Nextdoor uses AI as an assistive layer to help teams move faster, surface insights, and improve relevance—while keeping humans firmly in control.
- Erin brought the agency perspective, emphasizing that AI only creates value when it’s operationalized, embedded into workflows, and paired with clear ownership.
- Julia shared how Iterable fits into the broader AI ecosystem teams are already using.
One thing came through loud and clear: AI works best when humans stay in the driver’s seat. AI should accelerate good decision-making, not replace it—helping teams move faster without losing control or intent.
Key Takeaways
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AI works best as an assistive layer, not an autopilot
Shweta shared how Nextdoor uses AI to support teams, helping surface insights, speed up experimentation, and improve relevance—while keeping humans firmly in control of decisions and guardrails.The goal isn’t more automation. It’s better judgment, faster.
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Embedded AI beats bolt-on AI every time
In the webinar poll, a lot of you called out system integration as a major challenge:“System Integration - AI tools feel bolt-on rather than embedded in our daily workflows.”
Erin echoed this from the agency side. When AI feels separate, it adds friction. When it’s embedded into existing workflows, teams actually trust and use it.
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Data readiness still sets the ceiling for AI
Both the speakers and the poll results pointed to the same blockers:-
Data living in too many disconnected systems
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Data quality that’s hard to maintain
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Limited access without engineering help
AI doesn’t fix these issues—it exposes them. Clean, connected, accessible data is still foundational.
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- Teams want clarity, not just more AI
From Erin’s perspective working across many clients, the biggest gap isn’t tools—it’s roadmap clarity. In the webinar polls, a lot of you echoed this. Teams want to know where to start, what to prioritize, and how to apply AI in a way that scales responsibly instead of creating more complexity.
- Iterable’s role in the AI ecosystem is about connection, not replacement
Julia shared how Iterable’s Model Context Protocol (MCP) Server—fits into the broader AI ecosystem teams are already using. Rather than asking marketers to rip and replace their tools, MCP helps connect specialized AI signals, systems, and decisioning so AI can work with existing workflows.
Replay & Resources
- 🎥 Watch the full replay to see how teams are pairing AI capabilities with human-led strategy to make smarter decisions at scale.
- Step 5 (the final step!)is coming up next, where we’ll focus on turning all of this into revenue-critical action.