In a recent episode of the podcast You Should Know, John Phillips, Group Vice President of Employee Experience at ServiceNow, made a bold case for rethinking how organizations measure the success of artificial intelligence. Phillips contends that the current focus on adoption metrics—how many employees click a button or use a feature—is fundamentally misguided. Instead, he argues, the true measure of AI's value lies in whether work gets done faster, with less friction, and with better outcomes for both the employee and the business. The conversation arrives at a critical time, as chief human resources officers face mounting pressure to demonstrate productivity gains from AI investments across increasingly fragmented technology stacks.
Phillips did not mince words when describing the current AI landscape. He called it a "train wreck of productivity," pointing out that every system of record now ships its own AI agent, creating chaos for practitioners. "Every system of record is now got their little AI agent and it's creating chaos for these practitioners," he told hosts Ryan Leary and William Tincup. This fragmentation, he explained, leads to disconnected tools that fail to work together, undermining the very efficiency they promise. Phillips predicts a swift shift in focus: "We're going to quickly stop talking about AI adoption as tool usage, and we're going to start looking at the outcomes and jobs to be done."
The episode delved into the two-sided value exchange between employee and employer. Phillips raised a provocative question about the 23 hours a tool claims to save you—what happens to that time? He suggests that without careful design, those savings can evaporate into increased workload or burnout. He also touched on the difference between discretionary effort and engagement surveys, arguing that hyper-personalization beats one-size-fits-all pulse data. This aligns with Tincup's long-standing critique of engagement surveys, and Phillips pushed the conversation forward by suggesting that discretionary effort is a truer metric of employee commitment.
A significant portion of the discussion focused on the collapse of work boundaries since COVID-19. Phillips noted that the pre- versus post-pandemic shift has led to widespread burnout and an internal dialogue of "am I enough." He emphasized the need for extreme focus and extreme recovery in high performance, a principle that applies universally. "High performance has both extreme focus and extreme recovery. It's in any environment, the highest performers in the world have those things," he said.
ServiceNow's approach, as Phillips described, is to layer an agentic companion across existing systems rather than ripping and replacing them. He noted that customers often arrive with eight purchased AI tools plus one they built themselves, none of which communicate with each other. ServiceNow's vision is an AI control tower that acts as an agentic overlay, stitching together 15 large language models and 100 systems. This approach aims to unify disparate tools and deliver coherent, outcome-oriented results.
Phillips' perspective is shaped by diverse experiences, including time spent in refugee camps, which informed his belief that "skills and talent is universal and opportunity is not." This philosophy underpins his advocacy for democratizing access to AI benefits across the workforce. The episode also featured Leary sharing a personal story about applying to Home Depot and never receiving an acknowledgment email, illustrating the broader failures in employee experience that AI could address.
The conversation on You Should Know, part of the WRKdefined Podcast Network based in Arlington, Texas, is available now wherever podcasts are heard. With more than 3.9 million verified monthly listeners, the show delivers unfiltered conversations for people invested in the evolving world of work. For those interested in the intersection of AI, HR, and productivity, this episode offers a compelling argument for shifting the focus from adoption metrics to meaningful outcomes.
