AI is transforming the front door of customer experience, but the companies getting it right aren't simply automating faster. They're using technology to build greater trust.

In this episode of Getting to Aha!, Darshan Mehta sits down with Declan Ivory, VP of Customer Support at Fin, to explore how AI agents are reshaping customer support and why empathy, ownership, and human judgment remain essential. Declan explains why support should be viewed as an investment and a source of customer insight rather than a cost center, and how the “acknowledgement, ownership, resolution” framework builds trust at every touchpoint. They also discuss measuring customer experience beyond traditional satisfaction scores, testing support journeys from the customer's perspective, and removing friction early to accelerate time to value, reduce churn, and drive expansion.

Declan Ivory is a customer experience and support technology leader with 30 years of experience transforming how organizations engage with customers through AI and human-centered solutions. With a background in electrical and electronic engineering, he has held leadership roles at innovative technology companies, including Intercom, where he developed customer experience frameworks and AI-driven support tools. Today, as VP of Customer Support at Fin, Declan focuses on building AI-ready teams, future-proofing service models, and creating smarter, faster, and more human customer experiences.

Key Takeaways

👉 Judge AI on Experience, Not Just Efficiency – Declan argues that AI agents should be evaluated primarily on whether they improve the customer experience, rather than simply reducing costs or resolving tickets faster. Organizations that adopt AI purely for efficiency risk damaging trust by prioritizing speed over quality. He points to Kalshi’s use of Fin as an example of “rehumanizing support,” with AI handling routine interactions so humans can focus on complex, nuanced customer needs.
👉 Turn Support Conversations Into Product Insight – Declan explains that customer support is often a company’s most frequent customer touchpoint, making it a rich source of product and customer insight. Yet many organizations still treat support as a cost center and allow valuable feedback to disappear into ticket logs. By using AI to analyze conversations at scale, teams can identify recurring pain points, inform product roadmaps, reduce churn, and uncover opportunities for growth.
👉 Build Trust Through Acknowledgement, Ownership, and Resolution – Declan shares a simple framework for creating trust in every customer interaction: acknowledgement, ownership, and resolution. Customers often reach out when they're already frustrated or anxious, making that first response critical. Rather than passing customers between departments, the person who receives the issue should take responsibility for seeing it through. Fin's approach preserves context during handoffs, ensuring customers don't have to repeatedly explain their problem.
👉 Measure Every Interaction With a Customer Experience Score – Declan describes developing a Customer Experience Score that evaluates every AI-powered conversation rather than relying solely on CSAT surveys, which capture only a small percentage of interactions. By assessing conversations against defined quality parameters, businesses can identify trends and potential problems across customers, products, and stages of maturity. This provides a far more complete picture of whether AI is genuinely improving customer experience or quietly degrading it.
👉 Organize Around Skills, Not Rigid Job Titles – Declan believes AI will push organizations to rethink traditional role-based structures as routine work becomes increasingly automated. Instead of organizing teams around titles such as onboarding specialist or success manager, companies can identify people according to their specific expertise and relationship skills. Customers don't care about internal organizational charts; they want the right person solving their problem. Skill-based structures allow businesses to deploy human talent more flexibly and effectively.
👉 Walk in Your Customers' Shoes to Find Hidden Friction – Declan argues that leaders need to experience their own customer journeys rather than relying exclusively on dashboards and performance metrics. Acting as a customer or following an interaction from beginning to end can reveal friction that resolution rates and CSAT scores may hide. When Declan tested Fin's experience himself, he discovered customers were treating it like an old-fashioned chatbot. A simple prompt change encouraged more natural conversations and lifted CSAT by 5% overnight.

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Episode Resources:
Darshan Mehta on LinkedIn -  https://www.linkedin.com/in/darshan--mehta/
iResearch Website - https://iresearch.com
Declan Ivory on LinkedIn - https://www.linkedin.com/in/decivory/
Fin - Website