Teams | Collaboration | Customer Service | Project Management

Performance management has been broken in most organizations for a long time. It was designed for offices, where managers could track progress through proximity and ambient visibility. Remote work removed the ambient visibility. AI is now removing the need for most traditional performance proxies.

The first wave of remote work had a low bar. Companies went remote because a pandemic gave them no choice. Being remote at all was the differentiator. The second wave is different. It is voluntary, which means it is competitive. Companies now choose whether to offer remote flexibility. Which means the employees choosing to work for them have genuine alternatives. According to Buffer, 98% of workers want remote work at least some of the time. 46% would consider leaving if forced back to office full-time.

AI is absorbing the parts of your team’s work that used to prove someone was doing their job. If you manage a distributed team, that leaves a real question: what do you actually measure now, and how do you know it’s true? The location debate is already settled. US remote work has held steady at around 27% of the workforce for three years running, according to figures Liam Martin, co-founder of Time Doctor, cited in his opening keynote at Running Remote 2026.

How Rippling and Xero AU payroll integrations eliminate the manual work from every pay cycle.

AI-powered insights into how teams work, recognized by the people who use them every day.

The hidden costs of building your own employee monitoring software.

A practical workforce planning guide for HR leaders covering workforce forecasting, compensation planning, skills gaps, capacity management, and distributed workforce strategy.

The scaling cost of manual performance tracking.

A practical framework for aligning managers, measuring performance fairly, and creating consistency across teams.

Most teams track productivity. Few know what good actually looks like. Measuring productivity is easy. Understanding it is harder. Hours logged, tasks completed, revenue per head — these numbers only tell you so much. Without context, you can not tell if your team is performing well or just staying busy. That is where productivity benchmarks come in. They give you a reference point so performance data actually means something.