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No-Bull Q&As 🚫💩

Candid interviews with BPO & CX industry insiders and experts...without the bull!

Garry Gormley: How to Future-Proof Your Contact Center & Prep for AI

Peter Ryan No-Bull Q&A

Change is coming for contact centers, so how can they set up for success and control their fate? 🏆 


In this interview, UK-based contact center expert and consultant Garry Gormley lays out some cold, hard truths and a viable course of action for contact center survival. 


🚷 Flawed practices harming continuous improvement

🤖 Preparation tips for wholesale AI adoption

💻 Risk/reward of ditching/adopting CCaaS vendors

💡 And loads more.


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Q: What’s one controversial thing you believe about the contact center world? Where can they stand to improve?

A: Most contact centers are too focused on AI and self-service technology, neglecting the human skills that are essential for a better customer experience.


It’s true that technology can and will handle some interactions that humans cover today, but customers will undoubtedly avoid companies that replace the human touch entirely. Emotional intelligence, conflict resolution, and active listening are evergreen skills that technology simply cannot replicate, especially in complex or sensitive situations with vulnerable customers.


Contact centers need to focus on helping agents master these soft skills and empower them to handle tough interactions with deep empathy and understanding. Without these fundamentals, no amount of technology will stop the accelerating decline in customer satisfaction.


Q: What contact center practice do you think is fundamentally flawed, and how would you solve it?

A: Obsession over inaccurate metrics and failure to act on survey results really grinds my gears. NPS surveys, in particular, are given too much air time, often selectively presented to customers who’ve had positive experiences, and they’re typically completed by those with strong opinions—positive or negative—which can skew results, leading to unreliable data.


There’s a gold mine of valuable insights in the volume of passive scores these surveys produce, but without clearly defined closed-loop practices, teams can’t help customers effectively. Agents need more autonomy and decision-making authority to do what’s right for the customer.


If we want genuinely customer-centric contact centers, we have to move beyond NPS obsessions and embrace metrics that actually reflect the quality of service—namely, first contact resolution (FCR) and customer effort score (CES), which prioritize problem-solving and ease of interaction over speed or recommendations.


By applying speech analytics to capture unresolved data and sentiment and by training agents to resolve issues in the first interaction, customer satisfaction will continuously improve. Still, we have to shift our focus away from average handling time (AHT)—a change we all acknowledge but rarely implement.


Q: You once told me that contact centers aren’t ready for wholesale adoption of AI yet. How can they start to prepare to reach that point?

A: First things first, they need to be crystal clear on the purpose and the use case for AI adoption. There are major operational advantages and customer satisfaction improvements to be gained with AI, such as powering agent assistance tools that can alleviate the strain and cognitive overload that contact center employees deal with.


Still, AI thrives on clean, structured data, so be consistent about organizing and tracking data so that AI can effectively do its job—otherwise, you’ll put garbage in and get garbage out. On top of that, most contact centers are juggling multiple legacy platforms—CRMs, call routing systems, knowledge bases—which don’t communicate well with each other. This needs to be resolved before wholesale AI adoption is possible.


I recommend focusing on a well-thought-out customer journey, unshakable integrations with other systems, and a clean, well-structured CRM and knowledge base, along with being 100% clear on the problems you want to solve.


Q: Since many contact centers rely heavily on CRM/CCaaS providers for AI tools, what are the risks and advantages of building their own? What new value props could they bring to clients, for instance?

A: Building CRMs and CCaaS tools internally, even using tools like AWS, is risky business if you don’t have the capabilities to maintain and evolve them. Internal builds often lack the ability to integrate with rapidly evolving third-party platforms, which improve so fast that building your own solutions may mean expensive software development bills.


With all that said, bespoke solutions mean you aren’t reliant on out-of-the-box limitations or a product roadmap that may not play out as planned. Plus, you can be more agile and flexible with resourcing and deployment windows if you have adequate internal capacity and developer bandwidth.


The advantage of using a CCaaS or CRM provider lies in their scale, experience, and need to stay competitive by following market trends. The industry exists to help you get things right and retain your business, which can differentiate your contact center.

While I don’t see these vendors disappearing soon, I do foresee market consolidation, which could eventually disadvantage customers. As the larger players gain more control, we might see less innovation and higher pricing, especially as AI reduces the need for licenses in contact centers.



Connect with Garry on LinkedIn here to continue the discussion.


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