Human problem · Workplace operations

AI workplace: front end to back end

Following the employee journey into the operations behind it, and bringing AI into both.

Role: Design leadership · AI experience strategy

Vision · not shipped
An employee day supported by contextual workplace AI. Fictitious data.

The human problem

A large campus runs on thousands of small tasks: a broken door, a missed shuttle, a lunch order, a facilities ticket. Employees lose time finding the right tool. Operations teams lose time routing requests by hand across systems that don’t share data.

Both sides needed help that arrives in context, at the moment it’s useful.

Chapter 01

From the front end to the back end

We started where most workplace teams start: the employee experience of commuting, dining, parking and finding a place to work. When we mapped the full journey, a pattern appeared. Almost every front-end moment depended on a back-end operation. A missed shuttle depended on transportation dispatch, a lunch order on café operations, a broken door on a facilities ticket.

Front end — the campus experience across the employee day.
Back end — the workplace capabilities supporting those moments.

A great employee experience couldn’t be designed on its own. So we dug deeper, into the work of the people who keep the campus running.

Chapter 02

The same mindset, applied to operations

We brought the same human-centered approach to the people who run the campus. For facilities, transportation and dining teams, we began redesigning operational and ticketing workflows around natural language and role-aware access. People describe a problem in their own words, and the system routes it and shows each role only what it needs. We projected it would unlock more than 16,400 hours of operational capacity a year.

We worked alongside Microsoft’s Global Workplace Services team and CBRE, and mapped a capability blueprint for smart building operations. This work is still in progress as internal tooling, so it is described here without screens.

AI Digital Workplaces vision across employee experience and operations.
The workplace team at Realcomm.

I presented our approach publicly at Realcomm, the industry conference for smart buildings and workplace technology. Microsoft Campus – Redmond won the 2026 Realcomm | IBcon Digie Award for Most Intelligent Building Projects: Corporate HQ.

Chapter 03

Bringing AI into both sides

Vision · not shipped

With both sides mapped, the question became how AI could connect them. To align leadership on where this could go, we told one employee’s day as a story with two sides. The employee gets a morning brief, a commute rerouted around a highway closure, a ride home after a missed shuttle, and lunch suggestions based on history, location and cravings.

Vision · not shipped
Three principles for workplace AI: contextual, personalized, and actionable. Fictitious data.
Vision · not shipped
Missed-shuttle support in the employee journey. Fictitious data.

The operator sees the same café as revenue, waste and energy, and a broken door is reported just by pointing a phone camera at it. Three principles guided every moment: contextual, personalized and actionable.

Vision · not shipped
Café operator dashboard connecting demand, waste, revenue, and energy. Fictitious data.
Vision · not shipped
End-of-day workplace recap. Fictitious data.

This was a vision and did not ship. Additional material is available on request.

Outcomes

  • Projected more than 16,400 hours of annual operational capacity from AI-first workflow redesign.
  • Built a capability blueprint with Global Workplace Services and CBRE for smart building operations.
  • Established an AI-first discovery loop that tested high-fidelity generative AI prototypes early.
  • Represented Microsoft’s workplace platform strategy at Realcomm.
View the 2026 Realcomm | IBcon Digie Award winners

What I learned

Change always creates tension. Lean in, try, be curious. Start with the moment, the context, not the tech.