Podcast Summary: "How A 2-Week AI Agent Launch Enabled 67% Productivity Gains"

Podcast: Experts of Experience
Host: Lacey Peace (Mission.org), produced by Rose Shocker
Guest: Molly Bodensteiner, SVP Operations, Enjin
Air Date: September 24, 2025

Episode Overview

This episode of Experts of Experience delves into how Enjin, a fast-growing business travel platform, achieved remarkable gains in customer service and sales productivity by launching an AI agent in just 14 days. The conversation, driven by host Lacey Peace with producer Rose Shocker and guest Molly Bodensteiner, explores practical strategies for implementing AI, the critical importance of "ruthless prioritization," change management, the value of human-plus-AI models, and the myth that AI is just for reducing headcount. The episode is rich with actionable insights, real results, and a vibrant discussion on how to bridge the gap between planning and execution in AI transformations.

Key Discussion Points & Insights

1. The Real Value of AI: Not Just Cost Savings

• Stop thinking of AI as just an OPEX reducer. Primary value is in making existing teams more effective, not simply reducing headcount.

  • Quote:

    “We're all obsessed with OPEX and headcount reduction and cost savings. But that's not the point of what we're trying to do here with AI. Right. The real value is how do you make your existing people more effective?”
    — Molly, [00:00]

• AI as a growth enabler, not a cost-cutting exercise.

  • Quote:

    “AI is a growth enabler, not a cost cutting exercise. So we've got to change that perspective.”
    — Molly, [00:39]; [64:28]

2. The Two-Week AI Agent Launch: Ruthless Prioritization

• Enjin's first AI agent, EVA, was launched in 14 days, focused exclusively on automating hotel cancellations—300 requests per day.

  • Stats after implementation:

    • 15% reduction in average handle time
    • On track for $2M annual savings
    • 67% increase in sales rep efficiency
    • CSAT above 90%

  • Quote:

    “It might not have been our sexiest problem, or even the most technically interesting, but when we look at the volume, right, 300 cases daily, like it's costing our team a ton in productivity as well as just customer experience.”
    — Molly, [14:51]

• Lesson: Choose the highest-leverage, least-complicated use case and execute ruthlessly.

  • Quote:

    “Ruthless prioritization. So picking one thing and sticking with it ruthlessly.”
    — Lacey, summarizing Molly, [02:30]

• Avoid “Frankenstacking,” or piling up too many disconnected tools and platforms.

  • Quote:

    “That Frankenstack word is this idea that you've got 20 different tools trying to band aid solutions together.”
    — Lacey, [06:10]

3. Beyond the Hype: From Brainstorming to Action

• Many teams get stuck in brainstorming mode due to the endless potential of AI, but this paralyzes progress. Execution wins over ideation.
  • Quote:

    “We've got this huge list of ideas that almost paralyzes us... Which is why I loved our conversation with Molly Bodensteiner today... ruthless prioritization.”
    — Lacey, [02:09]

4. Customer Experience & Design for Trust

• Transparent Communication: Letting customers know they're interacting with AI built trust.

  • Quote:

    “We're upfront with customers. You're interacting with AI, Right. I mean, let's be honest, as consumers, we already kind of know that anyway in most situations. But being transparent and building that trust, I think was things that we learned through those feedback loops.”
    — Molly, [19:21]

• Seamless Escalation & Contextual Handoffs: EVA knows when to escalate to a human, ensuring customers never repeat themselves.

  • Quote:

    “We don't let her struggle through complex scenarios. We make sure she knows the right handoff, but then within that handoff, we have all of that context shifting.”
    — Molly, [20:00]

5. Results & Impact

• Quantifiable Impact:

  • Nearly $2M annual savings

  • 15% reduction in case handle time

  • 10% improvement in service rep productivity

  • 67% increase in sales rep efficiency

  • CSAT >90% (industry norm ~83%)

  • Improved job satisfaction and reduced attrition

  • Quote:

    “We've improved productivity of our customer service reps by 10%. And we are really like CSAT scores are above 90% right now, which is extremely high for this industry.”
    — Molly, [25:43]

  • Quote:

    “Our internal ... enps has continued to improve. Attrition is lower.”
    — Molly, [27:28]

6. Parallel Use Cases: Sales Augmentation, Not Replacement

• Tools Built for Sales:

  • AI-augmented prospecting to surface and prioritize accounts

  • Rep coaching, onboarding, and call simulation with actionable feedback

  • Quote:

    “What we're doing is not replacing human judgment. We're augmenting it with better data and faster insights so that reps can be more productive.”
    — Molly, [29:24]

• Simulated roleplay for sales and service reps: Agents can safely learn from varied, unpredictable AI-generated scenarios, benefiting onboarding and skill growth.

7. Change Management: The Core Challenge

• Adoption Is Not Automatic:
  Service teams were eager; sales teams were skeptical and required transparency (“show, not tell”), under-the-hood demos, and influential peer advocates.

  • Quote:

    “I had it all wrong on how adoption would go... On the sales side... it was almost like, oh, that's nice, I'm gonna keep doing what I'm doing.”
    — Molly, [38:37]

• 70% Change Management, 30% Tech:

  • Quote:

    “Successful AI implementation is like 70% change management, 30% the tech. So even with the best AI and tech in the world, if people don't trust it, you're not going to get the adoption.”
    — Molly, [65:32]

• Tips for Adoption:

  • Show exact outputs and prompt structures
  • Let influential mid-tier users lead the way, not the top performers

8. Quality Control & Risk

• Iterative Validation:

  • 100% manual review for initial AI interactions, then 10% sampling + ongoing monitoring

  • AI checks AI for additional redundancy

  • Quote:

    “Quality control has to start in design, right? It can't be at the point of inspection.”
    — Molly, [49:29]

  • Emphasize “good enough” and safe escalation over unreachable perfection

9. Building a Future-Proof Tech Stack

• Avoid platform lock-in and Frankenstacking:

  • Go deep with fewer platforms (Salesforce ecosystem + abstraction layers), build modular, swappable backend integrations

  • Quote:

    “Assume everything's going to change and go in probably with that assumption, right? ... We don't hard code specific AI models into our workflows. We have more of interfaces that sit underneath.”
    — Molly, [53:10]

10. Choosing AI Partners: It’s About People

• Tech is table stakes.
  Culture fit and partnership matter most now that almost all vendors offer 95% similar products.
  • Quote:

    “It’s not so much tech that's going to differentiate you as a company. It's actually the people in your company.”
    — Lacey, [06:10]

Notable Quotes & Memorable Moments (With Timestamps)

• On ruthless prioritization:

  “If we wouldn't have done that, we'd probably still be building eva, right? ... Focused on the good enough that we can learn and iterate ... With agents, there's no such thing as perfect.”
  — Molly, [18:32]

• On sales adoption resistance:

  “I am not an influencer ... most salespeople are influential because they're sellers ... But the top sellers are going to be your worst adopters because ... they're not going to rock their boat.”
  — Molly, [41:08]

• On what’s underhyped:

  “Process intelligence is super under hyped right now. ... Getting AI to actually understand our processes and start to suggest optimizations ... that's going to help change the revenue engine.”
  — Molly, [61:13]

• On cultural change:

  “In just eight months ... how much we've changed the culture around AI ... we've democratized it and ... built an AI literate organization.”
  — Molly, [64:39]

• On the myth that AI replaces people:

  “We're all obsessed with OPEX and headcount reduction and cost savings, but, like, that's missing the point entirely. ... The real value is: how do you make your existing people more effective?”
  — Molly, [64:28]

Timestamps for Important Segments

• [00:00–01:00]: The philosophy with AI and value in augmenting people
• [02:09–03:29]: The paralysis of endless AI brainstorming vs. ruthless prioritization
• [14:51–18:32]: 14-day launch story of EVA, focus on hotel cancellations
• [19:21–20:58]: Customer experience results, importance of trust and seamless handoff
• [25:43–27:54]: Quantitative impact, CSAT, employee satisfaction
• [29:24–32:47]: Augmenting sales with AI; no replacement for human connection
• [38:37–44:43]: Change management, building trust, influence, and adoption strategies
• [49:29–53:10]: Quality control and managing risk with AI agents
• [61:13]: Underhyped area: AI-driven process intelligence

Tone & Style

The conversation is practical, candid, and rich with lived experience—not theoretical. Molly provides playbook-style, hard-won lessons, and both hosts keep the tone energetic, sometimes self-deprecating, and always relatable.

Conclusion

Enjin’s rapid AI journey is a living case study in the power of focus, action over perfection, transparent trust-building, and human-plus-AI synergy. Their story counters the narrative that AI is about automation-for-layoffs, instead showing it can prepare companies to grow, improve customer and employee experience, and drive meaningful culture change. Their core advice:
“Stop planning, start doing, and prioritize change management as much as technology.”

Additional Resource

• Molly on LinkedIn: [Find Molly Bodensteiner][68:09]
• Enjin: enjin.com

Shout out: American Eagle for delivering a standout, personalized support experience via chat—setting the bar for customer expectations in the AI era.