The AI Paradox: What AI Reveals About Us w/ Ty Givens | S2E10

Guest: Ty Givens — You've outgrown duct tape. You're not ready to hire a full time VP of Support. That gap is where I work. I'm Ty Givens, founder of CX Collective. For more than 25 years I've built and run customer support operations, first inside companies like See's Candies, Thrive Causemetics, The Honey Pot Co., ShoeDazzle, and Herbalife, then as the person growing teams call when they've outgrown improvisation. Here's the pattern I see over and over: one support leader doing five jobs at once. AI. Reporting. Workforce management. Quality assurance. Zendesk. Hiring. Coaching. Executive reporting. Often all in the same week, with no one else on the team who's done any of it before. CX Collective exists to close that gap. Not by handing you a slide deck. Not by renting you agents. By building the systems with you, then training your team to run them without me. What that looks like in practice: Help desk implementation and optimization (Zendesk and beyond) - AI and Automation strategy - Quality Assurance and Coaching Programs - Workforce Management and staffing practices - Self-Service and Knowledge Management - Reporting, Metrics, and Operational Frameworks - Support Organization Design and Scale Planning One recent example: a rebuilt help center that cut ticket volume 30% and brought response time under two hours. No added headcount. I stay until it works. Clients I built systems for years ago are still running them today, without me, because that was always the point. If you're leading a growing support team and trying to scale without losing the experience that got you here, let's connect.

AI is not the solution. It is the mirror. In this episode of The Human Protocol, Mykel Salomon sits down with Ty Givens to unpack a hard truth about AI in customer support, CX, and leadership. As more companies rush to adopt AI automation, chatbots, and AI agents, many are finding that AI does not fix broken systems. It exposes them. From messy workflows and weak documentation to unclear escalation paths and poor ownership, this conversation shows what leaders need to face before they can scale AI the right way. Ty Givens shares real-world lessons from years of experience in support operations, CX leadership, AI deployment, and scaling teams. She explains why AI in customer service still needs human judgment, why leaders must become more technical, how poor documentation creates weak AI outcomes, and why the future of support will depend on curiosity, execution, and accountability. This episode is for anyone leading customer experience, customer support, operations, AI transformation, or service strategy. Key Topics: - Why AI exposes broken processes instead of fixing them - The truth about AI in customer support and CX - Why leaders need to become more technical in the AI era - How bad documentation leads to bad AI answers - What companies get wrong when deploying AI agents and chatbots - Why ownership and accountability matter more than ever - Where human support still matters most - How to build the right foundation before scaling AI automation -- TIMESTAMPS 00:57 Ty Givens introduction & career journey 03:59 Founding CX Collective – helping leaders build better 04:37 AI pressure in CX & support teams today 05:31 What really breaks when you deploy AI? 07:58 Real client story – sales vs support AI bots 13:00 Why leaders must understand frontline work in AI era 18:00 Programming systems is now part of leadership 22:40 Curiosity VS pretending to be strategic 28:00 How AI exposes burnout & unclear escalation paths 33:20 Don't automate broken processes – fix them first 38:50 Humans should handle complex, meaningful problems 43:10 CSAT often drops after AI rollout – here's why 48:20 Customers don't care if it's AI or human – they want fast, correct answers 52:40 Transparent AI vs pretending it's a person 57:37 Final advice to younger Ty: stay curious

Conversation Summary

In this episode of The Human Protocol Podcast, host Mykel Salomon and guest Ty Givens dive into the complexities of deploying AI in customer support and CX leadership. As companies rush to leverage AI, many find that rather than solving all problems, AI exposes existing flaws in workflows and escalation paths. Ty shares her experiences and the lessons she's learned about the need for strong foundations before AI implementation, emphasizing the importance of human judgment and technical understanding in leadership roles. This conversation sheds light on the necessity for leaders to be strategic, technically savvy, and resourceful to harness AI effectively.

AI Exposes, Not Fixes, Broken Processes

AI adoption highlights rather than resolves broken systems. Leaders must understand that AI will make messy workflows, unclear escalation paths, and burnout more visible. A successful AI implementation requires leaders to first fix these foundational issues.

Human Judgment is Still Crucial in Customer Support

AI can handle many tasks in customer support, but it should not replace human workers where complex problems and empathy are needed. Customers value quick, accurate responses, whether from humans or AI, but complex inquiries often require human intervention.

Leaders Need Technical Proficiency

As AI technologies become more prevalent, leaders must develop technical skills to manage and improve AI systems effectively. The ability to understand and manipulate these systems is rapidly becoming as important as people management skills.

Documentation Quality Directly Impacts AI Performance

Poor documentation can lead to incorrect AI responses and degrade user experience. Organizations must ensure that all help articles and knowledge base documents are clear, accurate, and comprehensive to enable AI to deliver correct answers.

AI Implementation is a Continuous Process

Deploying AI is not a set-and-forget task. It requires constant monitoring, evaluation, and updates to adapt to changing business needs and maintain performance. Organizations must create roles and processes to support ongoing AI development and maintenance.

Final Thoughts

This episode underscores the reality that AI is not a panacea for organizational issues—it's a tool that reflects existing systems. Leaders must be prepared to take responsibility for both technical and human elements to leverage AI successfully. By fostering curiosity, being resourceful, and applying strategic thinking, they can navigate the challenges of AI deployment and use it to unlock new efficiencies.

Key Takeaways

Frequently Asked Questions

What are the common mistakes companies make when deploying AI in support?

Companies often assume AI will automatically fix problems without addressing underlying issues like broken processes, weak documentation, or unclear escalation paths. AI exposes these flaws rather than fixing them.

Why must leaders be more technical in the AI era?

To effectively manage AI systems, leaders need technical skills that allow them to understand, implement, and improve these technologies. The role of leaders is evolving, and technical proficiency is becoming as vital as management skills.

How does poor documentation affect AI outcomes in customer support?

Poor documentation can lead to incorrect AI responses, as AI systems rely on clear and correct information to function properly. This can result in customer dissatisfaction and undermine the AI implementation.

Why is continuous monitoring important after implementing AI?

AI systems require ongoing oversight to address new challenges, update knowledge bases, and ensure they continue meeting business needs. Continuous monitoring allows organizations to refine AI processes and adapt to shifts in customer expectations.

Do customers prefer human or AI support?

Customers generally prioritize receiving accurate, timely answers over the mode of delivery. While some complex issues require human empathy and intervention, for straightforward queries, AI can provide a satisfactory user experience when implemented correctly.