Ruth Fornell, Chief Executive Officer, Poppulo.
Organizations are communicating more than ever, but executing less effectively. That contradiction should concern every leadership team.
According to Gallup, just 31% of U.S. employees and 20% of global employees are actively engaged. At the same time, enterprises are producing unprecedented communication volume across email, chat, intranets, town halls and AI-generated content.
Recently, I’ve argued that speed is not the same as leadership, and that more communication does not resolve uncertainty—it often amplifies it. Both point to the same underlying issue: Many organizations still measure internal comms as a publishing function instead of an execution function.
That distinction matters more now than ever, because AI is about to scale whatever system leaders choose to optimize.
What 2.2 Billion Communications Reveal
Over the past two years, my organization has analyzed anonymized, amalgamated datasets from some of the world’s largest enterprises and published the findings. Our 2025 benchmark report analyzed the 2.2 billion communications sent through the Poppulo platform in 2024, and our 2026 report compared that against 2025 data.
Open rates increased across the dataset, demonstrating that organizations continue to reach employees effectively. Yet the relationship between opens, clicks and business outcomes remains far less clear.
As employee communication habits evolve, traditional engagement metrics provide only a partial view of impact. They can tell leaders a message was delivered and seen. They reveal far less about whether it was understood, trusted or acted upon. What happens next depends on what the employee already knew and how the message was reinforced elsewhere, whether by a manager or team conversation.
Opens and clicks signal engagement, but cannot tell you on their own whether behavior changed. An employee can open a message, read it and do nothing. Or, they can act without clicking anything at all. Bridging that gap requires additional data, such as surveys, operational metrics and feedback on whether behavior actually changed on the ground.
With agentic AI, the stakes become higher. If AI is trained against the metrics most organizations currently prioritize, it will become exceptionally effective at maximizing engagement metrics without necessarily improving understanding, alignment or action.
A Deeper Look At The Data
From those 2.2 billion messages, we also identified trends in communications. In 2025, AI-related content nearly doubled in send volume year-over-year. Leadership and health-and-safety communications maintained or increased engagement. Wellbeing and IT lost ground. Sustainability, after declining the prior year, regained traction.
This demonstrates to me a clear signal: Communication tied to immediate relevance still earns attention. Abstract or irrelevant messaging gets filtered out. Employees are becoming increasingly disciplined about what earns their attention.
One additional data point stood out: Event invitations increased 3%. As digital volume expands, the appetite for human connection expands with it. When communication feels participatory rather than performative, behavior changes.
What Leaders Should Measure Instead
If open rates are only part of the story, what should organizations measure? I think about this in two categories: leading indicators that reveal whether communication is landing, and lagging indicators that prove it changed something.
On the leading side, context matters first. Benchmarks vary significantly by industry. An engagement metric that looks healthy in financial services can be misleading in manufacturing, where data often reflects a reachable subset rather than the full workforce.
Know your baselines. Then move beyond them to behavioral and confidence-based measurement. Instead of asking, “Did employees receive the message?” the better question is, “Do employees know what to do next?”
One metric I track consistently at Poppulo is Employee Net Promoter Score (eNPS). Adapted from customer NPS, it asks employees how likely they are to recommend the organization as a place to work. This provides a direct read on sentiment, rather than a proxy like open rates.
Gallup research shows a positive correlation between employee advocacy and customer advocacy. When employees believe in the organization, customers experience the difference.
On the lagging side, a simple before-and-after question such as “I understand what is expected of me” often reveals more about organizational alignment than a dashboard full of click metrics.
Ultimately, the most important question is the simplest: Did people do what we asked them to do? A safety campaign succeeds when training completions rise, and incidents decline—not when open rates spike. A transformation initiative succeeds when managers can clearly explain the change and employees understand how priorities shifted—not when a town hall hits strong attendance.
New research from Ipsos Karian & Box bears this out: fewer than half of 5,000 U.K. workers surveyed in March said the reasons behind organizational change were clearly communicated to them.
What This Means In The AI Era
For communications and HR leaders, this moment creates both urgency and opportunity.
Leadership teams are expecting communication leaders to bring evidence of activation and business outcomes. Did employee questions shift from confusion to clarification? Did adoption rates improve? Those are the signals that matter at the leadership level.
This is also where agentic AI becomes genuinely transformative. Deployed against the right indicators, AI can identify emerging confusion patterns, surface resistance signals early and connect communication behavior to operational outcomes. These insights help leaders intervene before execution slows.
AI earns its strategic value as an organizational intelligence layer, not just a faster content engine. But AI optimized for the wrong metrics will amplify the problems organizations are already struggling with. More volume, more scanning and a wider gap between what leaders say and what employees do.
The measurement framework organizations choose today will determine what their systems—human and artificial—learn to produce tomorrow.
AI will not solve organizational misalignment. It will scale whatever leadership system already exists, including flawed ones. The outcomes organizations choose to measure and reward today will shape the behaviors their systems reinforce tomorrow.
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