What reward leaders are saying in 2026

Most organisations still cannot answer the question their employees are already asking: what do I actually earn?

That is not a fringe concern. It came up in every single session of the Total Rewards Lab, across every type of organisation, framed differently each time. And it is just one of the things that surprised us.

Earlier this year, uFlexReward and Unequity partnered to run four Total Rewards Lab sessions. The format was simple and deliberate. Small groups. Senior reward practitioners from global organisations. A confidential space with no presentations, no panels, and no pitching. Just people who work in reward every day, talking honestly about what is actually happening in their world.

What we were looking for was not consensus or best practice. We wanted to hear what reward leaders are genuinely wrestling with in 2026, the things that do not always make it onto a conference agenda or into a published report, because the room does not feel safe enough to say them out loud.

It turns out that when the room does feel safe, people say a lot.

Five things that came up, across all four sessions.

Data is not the problem. Most organisations have more reward data than they know what to do with. The problem is that it sits in the wrong places, in the wrong formats, and is not accessible to the people who need to make decisions with it.

More flexibility does not mean more empowerment. Organisations that have invested heavily in flexible reward frameworks have learned the hard way: without clear structure underneath, employees feel overwhelmed, not empowered. More choice does not automatically mean more value.

Managers are still the biggest bottleneck. Every organisation in the room had invested in manager training. It is rarely enough. Not because the training is bad, but because managers do not need more information. They need the right information, at the right moment, in a form they can actually use.

AI amplifies what is already there. Where reward data is solid and well-structured, AI is genuinely useful. Where it is fragmented or inconsistent, AI makes the problem faster and more visible. It does not fix a data problem. It accelerates one.

Employees do not understand what they earn. Not the full picture. Across every session, across every type of organisation, the honest answer to this question was no.

What the format made possible.

One of the things that struck us most was not any single insight from the sessions. It was what the format itself produced.

Reward is a discipline where people often feel they have to have the answers. In these sessions, people felt they could share the questions instead. The uncertainties. The things they had tried that had not worked. The tensions they were navigating without a clear resolution.

That kind of conversation is rare. And it is exactly the kind of conversation the industry needs more of.

We hope to continue that, with new voices at the table, and a genuine belief that the people in this industry have the ability to drive the change that is actually needed. If that sounds like you, stay tuned.

The full individual lab session blogs are coming soon.