In a recent episode of the podcast "You Should Know," John Phillips, Group Vice President of Employee Experience at ServiceNow, made a bold claim: the current approach to measuring AI adoption is fundamentally flawed. Phillips argues that counting how often employees use AI tools misses the point entirely. What truly matters, he says, is whether jobs are completed faster, with less friction, and with improved outcomes for both employees and the business.
Phillips' remarks come at a time when CHROs are under increasing pressure to demonstrate AI productivity gains across fragmented technology stacks. He describes 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. The result is a disjointed environment where tools do not communicate, leading to inefficiency rather than the promised gains.
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. Many customers arrive with multiple purchased AI tools that lack interoperability, and Phillips emphasizes the need for a cohesive strategy.
The conversation also delved into the two-sided value exchange between employee and employer. Phillips questioned what happens to the 23 hours a tool claims to save, suggesting that the real benefit should be reinvested in meaningful work. He highlighted the importance of discretionary effort over traditional engagement surveys, arguing that hyper-personalization is more effective than one-size-fits-all pulse data.
Phillips also touched on the collapse of work boundaries post-COVID, which has contributed to burnout and an internal dialogue of "am I enough." He stressed that high performance requires both extreme focus and extreme recovery, a principle that applies across environments.
ServiceNow's vision includes an AI control tower that acts as an agentic overlay, stitching together 15 LLMs and 100 systems. This approach aims to create a unified workflow that reduces chaos and enhances productivity. Phillips' perspective is shaped by his experiences in refugee camps, where he learned that "skills and talent is universal and opportunity is not." This philosophy drives his commitment to democratizing access to tools that can enhance work outcomes.
The episode underscores a critical moment for business leaders: the need to move beyond vanity metrics and focus on tangible results. As AI becomes more pervasive, the ability to measure its impact on actual work will be a key differentiator. Phillips' call to action is clear: stop counting clicks and start measuring outcomes.
