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. He argued that counting how often employees use AI tools misses the point entirely. Instead, he says, the focus should be on whether jobs get done faster, with less friction, and with better outcomes for both employees and the business.
Phillips' comments come at a time when CHROs face mounting pressure to demonstrate AI's productivity gains across increasingly fragmented technology stacks. He painted a stark picture of the current landscape: "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. "We're watching this like train wreck of productivity."
The core problem, Phillips explained, is that each software vendor has shipped its own AI agent, and these agents do not communicate with each other. He described customers arriving with eight purchased AI tools plus one they built themselves, none of which talk to each other. This fragmentation undermines the very efficiency AI is supposed to deliver.
Phillips predicts a swift change in how success is measured. "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," he said. This shift would align metrics with actual business value, rather than vanity metrics like login counts or feature clicks.
The conversation also explored the two-sided value exchange between employee and employer. Phillips raised a provocative question: what happens to the 23 hours a tool claims to save you? If those hours are simply absorbed by more work, the employee sees no benefit. True success, he implied, requires that saved time translate into reduced burnout and improved well-being.
On the topic of human performance, Phillips offered a memorable insight: "High performance has both extreme focus and extreme recovery. It's in any environment, the highest performers in the world have those things." This principle, he suggested, applies to how organizations should design work in an AI-augmented world.
The episode also touched on the collapse of work boundaries post-COVID, burnout, and the internal dialogue of "am I enough." Phillips' perspective is shaped by time spent in refugee camps, where he learned that "skills and talent is universal and opportunity is not." That philosophy drives ServiceNow's approach of layering an agentic companion across existing systems rather than ripping and replacing them.
Tincup revisited his long-standing critique of engagement surveys, pushing Phillips on whether discretionary effort is a truer metric. Leary shared a personal saga of applying to Home Depot and never receiving an acknowledgment email, illustrating the disconnect between corporate tools and candidate experience.
ServiceNow's vision, Phillips explained, is an AI control tower that acts as an agentic overlay, stitching together 15 LLMs and 100 systems. This approach aims to unify disparate AI efforts into a coherent workflow, reducing chaos and improving outcomes.
The episode is available now on the WRKdefined Podcast Network, which reaches over 3.9 million verified monthly listeners. The conversation underscores a critical message for leaders: stop counting tool usage and start measuring what matters—work outcomes.
