What Is APIx? Avaya’s AI Performance Index for CX

In enterprise CX, the market has no shortage of demos, copilots, bots, and promises about efficiency. While the promise of AI in customer experience is immense, many organizations find it difficult to unlock its full value. 

This isn't a failure of AI technology itself, but a challenge in measuring its true impact. A recent Gartner study quantifies this gap, finding that only 28% of AI projects in infrastructure and operations meet their ROI expectations. The study revealed a crucial insight: success isn't determined by the most sophisticated models, but by the ability to connect AI to real workflows and business goals. 

Customer experience leaders are feeling that pressure directly. That is where the AI Performance Index (APIx) comes in. In Avaya Infinity, APIx is designed to measure AI performance across outcomes, cost, and automation, with the goal of making AI more accountable, more explainable, and easier to optimize over time.

Here’s why legacy CX metrics no longer tell the full story, what buyers are really being asked to prove, and how Avaya is trying to make that measurement problem easier to solve.

Why AI ROI Gets Harder to Defend in Customer Experience

For years, contact center leaders have used familiar performance measures like average handle time (AHT), containment, and deflection. Those metrics still matter, but they were built for a world where most of the work was done by humans.

That’s no longer the world most enterprises are operating in.

Today, AI may be handling intake, surfacing context, guiding agents, executing workflows, or resolving parts of the interaction directly. But, we all know a faster interaction may not always be a better one. A contained interaction is not always a resolved one. And a lower-cost interaction is not necessarily a smarter one — especially if it comes at the expense of quality, risk, or most importantly, customer trust. AI ROI gets harder to defend when all you can show is activity. 

Demos are the easy part. The harder part is proving value once AI is live in production.

What CX Leaders Need to Prove About AI ROI

Most enterprise buyers are trying to prove that AI is helping the business in ways senior leaders actually care about. In practice, that usually means proving some combination of four things: 

• Is AI helping resolve customer issues more effectively?
• Is AI lowering cost or reducing wasted effort?
• Is AI improving quality, consistency, or confidence in the interaction?
• Is AI doing that consistently in live operations?

For CX leaders, deployment is only the start. They still have to show what changed, where value showed up, and how to improve performance. That’s the problem Avaya is addressing with APIx—augmenting or adding value metrics to the current activity metrics.

What Is the AI Performance Index (APIx)?

The AI Performance Index (APIx) is Avaya Infinity’s framework for measuring AI across outcomes, cost, and automation. The goal is to help enterprises see why performance changed and where to improve it. In practice, that means looking at measures such as:

• Autonomous resolution — how independently the AI completed a task end-to-end, without human intervention
• Goal completion — whether the interaction solved the customer’s problem or merely sped up the handoff.
• Intelligent economics — the cost per goal achieved, including variable AI costs such as token use, inference, and data retrieval.
• Decision accuracy and hallucination rates — whether the AI’s reasoning was reliable and how often it generated incorrect information. 
• Sentiment-driven scores — whether the customer left the interaction in a better state, not merely a shorter one.
• Outcome ownership and AI risk — who or what is accountable for the decision, and what operational or reputational risk came with it. 

With Avaya Infinity, AI now has a scorecard tied to business outcomes in production—not just activity metrics in a dashboard. 

Which CX Outcomes Matter Most for AI ROI

Modern AI in CX is tied to operational and financial outcomes that a buyer can actually take into a budget meeting. With Avaya Infinity, those outcomes show up in very practical ways: 

• AI-assisted workflows and preserved context can reduce handle time by cutting repeated discovery work. 
• More informed routing and automation can help lower cost to serve and improve staff efficiency. 
• Back-office automation can deliver significant ROI, depending on the workflow and operating model. 

This data matters because it maps directly to the kinds of business outcomes enterprise leaders care about—operating cost, labor efficiency, customer effort, resolution quality, and the ability to scale without losing control. The challenge, of course, is attribution. If a leader sees cost improve or AHT drop, what actually caused it? Was it better context? Smarter routing? A more effective handoff between AI and a human? A stronger agent-assist layer? A cleaner workflow? 

If a CX team can only say that handle time went down, they still have work to do.

A stronger ROI story is showing that AI reduced recap work, improved context quality, and lowered cost per successful resolution without increasing risk or repeat effort.

See how Avaya Infinity helps enterprises measure AI performance more clearly across outcomes, cost, and automation.