The conversation around artificial intelligence in the workplace has reached a critical juncture, with many organizations struggling to quantify the true impact of their AI investments. In a recent episode of the podcast You Should Know, hosted by Ryan Leary and William Tincup, John Phillips, Group Vice President of Employee Experience at ServiceNow, offered a blunt assessment: the industry is measuring AI adoption the wrong way, and the current landscape is a "train wreck of productivity."
Phillips argues that counting how often employees use AI tools is a misguided metric. "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 is critical as CHROs face mounting pressure to demonstrate productivity gains from AI across increasingly fragmented technology stacks. According to Phillips, the proliferation of AI agents within individual systems of record has created chaos, with each system shipping its own agent, leading to a disjointed and inefficient user experience.
The episode delved into the two-sided value exchange between employees and employers. Phillips posed a thought-provoking question: what happens to the 23 hours a tool claims to save you? He suggests that the real value lies in reducing friction and enabling employees to focus on higher-order tasks. This ties into a broader discussion about discretionary effort versus engagement surveys. Tincup, a long-time critic of engagement surveys, pushed Phillips on whether discretionary effort is a truer metric. Phillips agreed, noting that hyper-personalization in feedback mechanisms is more effective than one-size-fits-all pulse surveys.
The conversation also touched on the post-COVID collapse of work boundaries, which has led to increased burnout and an internal dialogue of "am I enough?" Phillips emphasized that high performance requires both extreme focus and extreme recovery, a principle that applies across environments. "The highest performers in the world have those things," he said.
ServiceNow's approach, as described by Phillips, involves layering 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. This fragmentation is a significant barrier to realizing AI's potential. ServiceNow's AI control tower vision aims to stitch together multiple large language models and hundreds of systems, providing a unified interface that can orchestrate workflows seamlessly.
Phillips' perspective is shaped by his time spent in refugee camps, where he learned that "skills and talent is universal and opportunity is not." This philosophy underscores his commitment to creating technology that democratizes access to opportunity. The episode also featured a personal anecdote from Leary, who shared his frustrating experience of applying to Home Depot and never receiving an acknowledgment email, highlighting the importance of a positive candidate experience.
As AI continues to permeate every aspect of work, Phillips' insights serve as a timely reminder that the ultimate measure of success is not adoption rates but tangible outcomes. Organizations must shift their focus from counting clicks to evaluating whether jobs are completed faster, with less friction, and with better results for both employees and the business. The call to action for HR and business leaders is clear: rethink how AI's value is assessed and invest in solutions that unify the fragmented AI landscape.
