The AI CX Payoff:
Measuring Returns and Managing Spend at Scale

WHERE WE LEFT OFF 
Edition I Recap: Implications of Generative AI for Customer Experience Leaders in the Philippines 
Three things came out of that room: 

• CX had decisively shifted from a cost center to a growth lever — and GenAI was the accelerant. 

• The greater risk was not moving too fast, but analysis paralysis while competitors shipped. 

• The gap between an AI strategy and an AI deployment was wider than most had budgeted for. 

The closing question was “metrics that matter” — which value levers to measure, and how. 
Edition I established what the value is, and that it’s measurable. 
Edition II asks why, a year on, so few have banked it in production. 

THE PILOT IS THE EASY PART  
54% of Philippine CX decision-makers already use generative AI in production or are piloting it. Another 30% plan to adopt within the year.  

But adoption and maturity are not the same thing. Some contact centers in this market are running pilots; others are still deciding where to start. Comparatively few run AI in production at scale — with the numbers to prove it. 

In a market where the CXM services industry is projected to grow from $12.5B (2023) to $15.6B by 2029, agent productivity isn’t just an operational metric. It’s a national competitive position. 

Closing the gap is the conversation. 

THE THREE OBSTACLES  
Join us for an exclusive executive luncheon with 15 other CX leaders in the Philippines — an intimate, closed-door discussion to exchange insights, explore emerging trends, and connect with CX thought leaders in the country. 

Three obstacles between a pilot and a payoff 

01 — Proving the return 
Edition I established that AI outcomes are measurable. A year on, measurable in principle isn’t the same as measured in practice — most business cases still rest on benchmarks rather than your own numbers. We discuss how to build the case before you commit, and which measures stand up to scrutiny. 

02 — Surviving the economics 
Per-seat contracts and the burden on scalability. We discuss how leaders are modeling the true cost of AI in customer operations — and how to keep the bill from scaling faster than the benefit. 

03 — Making the leap to AI-ready 
Whether you’re moving from a traditional contact center or trying to get a pilot into production, the failure point is rarely the model. We’ll discuss what the organizations that made the leap did differently. 

Voice AI where volumes are still growing. Governance in regulated industries. Bringing a workforce along for the ride. These are the questions running through all three obstacles — and the ones this room is built to work through together. Reserve your seat today