How ServiceNow is building an AI-native workforce, in their own words

1. On stage at Knowledge 26

The AI-native workforce, live: Josh Newman (ServiceNow) & Mikael Wornoo (TechWolf)

In this session at Knowledge 26 (ServiceNow's yearly customer conference), ServiceNow's Josh Newman and TechWolf co-founder Mikael Wornoo walk through what an AI-native workforce looks like in practice: treating skills as live signals rather than static surveys, and building a readiness stack that connects business strategy, the actual work people do, and talent. Mik demonstrates the EmployeeWorks agent turning a question like "scale my FDE pipeline" into a conversational answer in minutes. Josh reflects on what it takes to move, in his words, from intuition to intelligence.

Watch the full keynote here

About the speakers

Josh Newman is VP of Workforce Skills and Talent Readiness at ServiceNow, where he leads the program to staff the company's new AI-native roles.

Mikael Wornoo is Co-founder and President of TechWolf, which builds the skills and work intelligence foundation behind the readiness stack.

2 The webinar

Skills as signals, not snapshots: Nur Duygun (ServiceNow)

Nur Duygun, Director of Skills Intelligence at ServiceNow, makes the case for a different way of thinking about skills: as living signals about capability, not a snapshot that is stale the moment it is captured. She covers confidence-weighting the data, keeping humans in the loop on every decision, and her advice for anyone starting out.

Don't boil the ocean. Pick a few critical roles, pick a few horizontal use cases, and go deep. Connecting even a few disconnected pieces builds momentum and belief."
— Nur Duygun, Director of Skills Intelligence, ServiceNow

Watch the full webinar here

About the speaker

Nur Duygun is Director of Skills Intelligence at ServiceNow, focused on turning workforce data into decisions leaders can trust.

3 The podcast

From skeptic to believer: Josh Newman on The TechWolf Podcat

Julius Schelstraete, customer community lead at TechWolf, sits down with Josh Newman for a longer conversation. Josh is candid that he entered the program as a self-described skills skeptic, and talks through what changed his mind.

Listen to the episode here

The key takeaway

‍What changed Josh's mind wasn't a better skills survey. It was focusing on the layers underneath the skills label: the work people actually do, the tasks, and how AI is reshaping the role. As he puts it, "Every business has some of these elements. You don't need perfection across all of them to start making more intelligent decisions."

4. The throughline

Across a keynote, a webinar and a podcast, the same picture emerges. ServiceNow is redesigning roles around AI, and it needs a live, trustworthy read on what its people can actually do. The throughline isn't a single tool. It's a shift from static skills snapshots to continuously updated signals, kept honest by human review, and applied to a few high-stakes roles first rather than everywhere at once.

Key takeaways across all three

• Skills are signals, not snapshots. A survey is stale the moment it's captured; signals from real work stay current.
• Start narrow, go deep. Prove value on a few critical roles and use cases before scaling anywhere near everywhere.
• Keep humans in the loop. The data narrows and informs the shortlist; people still own the decision.
• You don't need perfect data to start. Connecting even a few disconnected sources beats waiting for completeness.
• Skepticism is a feature. The program earned trust by working the layers under "skills", the work, tasks and AI impact, not by re-arguing the case for skills.