The “AI” line item in your development budget usually gets judged the same lazy way. Stakeholders treat measuring AI value as a headcount question: how many developers can we drop, how many hours come off the sprint. That framing is exactly what produces brittle implementations and a pile of technical debt.
Fourteen years of WordPress and high-scale WooCommerce work has shown me plenty of “automation” hacks, and efficiency was never the whole story. Hours saved is the easiest number to collect, which is why everyone collects it. The bigger wins come when AI raises what your team can do at all, or makes a business model viable that you could never have staffed. Those cases are worth separating: automation, augmentation, innovation.
Three places to look when measuring AI value
The McKinsey State of AI 2025 report draws the same line: high performers are not only optimizing business-as-usual, they are finding capabilities they did not have before. So the first job is knowing which of the two you are actually looking at.
1. Automation and the reliability problem
Automation is the easy one to picture. A task like processing invoices or flagging fraudulent WooCommerce orders goes to a machine instead of a person. What makes measuring AI value messy here is the accuracy tax. The model gets things wrong, and three hours spent debugging one hallucination cancels out ten hours of saved time.
I never run these on the main thread. They go through a background processor like Action Scheduler. The fraud check below runs async and keeps a human escalation path for anything the model is not sure about.
<?php
/**
* Async processing for AI fraud detection.
* Don't block the checkout process; queue it.
*/
function bbioon_enqueue_ai_fraud_check( $order_id ) {
if ( class_exists( 'AS_ActionScheduler' ) ) {
as_enqueue_async_action( 'bbioon_process_order_ai_check', [ 'order_id' => $order_id ] );
}
}
add_action( 'woocommerce_payment_complete', 'bbioon_enqueue_ai_fraud_check' );
add_action( 'bbioon_process_order_ai_check', 'bbioon_handle_ai_logic' );
function bbioon_handle_ai_logic( $order_id ) {
$order = wc_get_order( $order_id );
// Naive approach: Just trust the AI.
// Senior approach: If confidence is < 0.85, flag for human verification.
$ai_response = bbioon_call_fraud_api( $order->get_data() );
if ( $ai_response['confidence'] < 0.85 ) {
$order->update_status( 'on-hold', 'AI flagged: Pending Human Verification.' );
} else {
$order->add_order_note( 'AI Check Passed: High Confidence.' );
}
}2. Augmentation and decision quality
With augmentation the system works as a sparring partner. Take an AI assistant that reads through thousands of customer reviews on your site for UX research. Nobody got replaced. The researcher simply got access to a pile of data that used to sit there unread because it was too big to read. The number to watch is decision quality, not turnaround time.
I have written before about the hard truth about using AI assistants, which is that they only go as far as the domain knowledge of the person driving them. If nobody is tracking whether your team’s calls got better, then nothing about the value is being measured.
3. Innovation and new operating models
Call this one generative design applied to the business. Some things were never off the table technically, only economically, like a personalized landing page for every visitor built from what they are doing on the site right now. No front-end team is big enough to hand-build that. Value here shows up as revenue and market reach, not as a smaller invoice.
If the measuring AI value work is eating your dev hours, hand it to me. I have been in WordPress since the 4.x days.
What to track instead
The stopwatch is not useless, it is just early in the chain. Process improvements turn into capability improvements, and those eventually turn into money. Read the cost line by itself and you will cut the innovation work long before it gets that far. Accuracy is the metric for automation, interaction design for augmentation, and discovery for innovation. Pick which one applies before you build, not after.
