The conversation around AI in the workplace has been dominated by adoption metrics—how many employees are using a tool, how often, and for what tasks. But John Phillips, Group Vice President of Employee Experience at ServiceNow, says this approach is fundamentally flawed. In a recent episode of the podcast 'You Should Know,' Phillips argued that counting tool usage misses the point entirely. What truly matters, he said, is whether jobs get done faster, with less friction, and with better outcomes for both the employee and the business.
The discussion arrives as chief human resources officers face mounting pressure to demonstrate AI's productivity gains across increasingly fragmented technology stacks. Phillips described the current landscape as a 'train wreck of productivity,' caused by every system of record shipping its own AI agent. '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.
Phillips predicts a rapid shift in how AI success is evaluated. '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 perspective aligns with ServiceNow's approach of layering an agentic companion across existing systems rather than replacing them. Phillips noted that customers often arrive with eight purchased AI tools plus one they built themselves, none of which communicate with each other. ServiceNow's AI control tower vision acts as an agentic overlay, stitching together 15 large language models and 100 systems to create a unified workflow.
The conversation also delved into the two-sided value exchange between employee and employer, questioning what happens to the 23 hours a tool claims to save. Phillips emphasized the importance of discretionary effort over engagement surveys, arguing that hyper-personalization beats one-size-fits-all pulse data. He also touched on the pre-COVID versus post-COVID collapse of work boundaries, which has led to burnout and an internal dialogue of 'am I enough.'
On human performance, Phillips offered a resonant 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 philosophy is shaped, in part, by time spent in refugee camps, where he learned that 'skills and talent is universal and opportunity is not.'
Leary shared a personal anecdote about applying to Home Depot and never receiving an acknowledgment email, highlighting the disconnect between technology and human experience in hiring. Tincup revisited his long-standing critique of engagement surveys, pushing Phillips on whether discretionary effort is the truer metric. The episode provides a candid look at the challenges and opportunities in measuring AI's impact on work, urging leaders to shift their focus from adoption to outcomes.
