Gina Clarkin

Gina Clarkin is a product marketing manager at ASAPP. She works to bring advanced technologies to market that help companies better solve real-world problems. Prior to joining ASAPP, she honed her product marketing craft at tech companies with firmware, wireless, and contact center solutions.

Who should meet the customer first?

Gina Clarkin

What "agentic AI" actually requires to ship in a regulated enterprise

3 things customer experience leaders stopped believing (and what that tells us)

Why scaling AI in customer service starts with redesigning work

The contact center operating model is reversing

Getting from escalation to collaboration: A better approach to human-in-the-loop

How to Equip Your Contact Center for Human / AI Collaboration

Get critical visibility into GenerativeAgent behavior with Conversation Explorer

Will the real human-in-the-loop please stand up?

Recently Published

Browse Blog

Deploying more AI agents won't improve outcomes. See why orchestration, not agent count, decides which enterprises actually win with agentic AI.

Customers repeat themselves because routing comes before understanding. See what changes when orchestration sits at the front of every interaction.

Trust or trash the biggest AI customer service claims. Chris Arnold breaks down agentic AI, human-in-the-loop, AI governance, and CX myths.

15 best practices to build a human-in-the-loop operating model for agentic CX, covering workforce transformation, AI governance, AI Ops, and automation.

Can generative AI for customer service resolve issues or just deflect them? Use this framework to assess resolution, governance, and ROI. URL: generative-ai-for-customer-service

See how leading CX teams are setting new standards for personalization, security, and trust, featuring ASAPP's Chris Arnold at CCW Vegas

Most bots deflect demand. Learn how an AI customer service agent resolves issues through integrations, human oversight, and measurable KPIs.

Learn the three tenets of human-AI collaboration for customer service, including HILA, autonomous resolution, and AI optimization at scale.

Every vendor claims to be agentic. Here's what agentic AI actually requires to ship in regulated customer experience: architecture, governance, integration.

Beyond deflection, what are the benefits of AI in customer service? Use a buyer's framework to assess cost, CSAT, FCR, scale, and governanc

Automation is easy; resolution is hard. Evaluate agentic ai for customer service using FCR, repeat contacts, escalation cost, and satisfaction.

Deflection isn’t the goal. Evaluate AI customer service use cases by resolution impact, operational fit, governance requirements, and rollout priority.

Browse Blog