AI can make work more meaningful

As a CEO operating within the global supply chain—where every purchase is tied to efforts to end forced and child labor—I think often about what work is for: not just making it faster, but making it matter.

That’s what makes the latest Gallup findings on AI so striking. The headline insight isn’t productivity. It’s something more revealing: We’re becoming more efficient, but not more engaged.

Employees say AI is making them more productive, yet global employee engagement has declined for two consecutive years, now sitting at just 20%. We’re optimizing how work gets done, but for many people, we’re eroding the experience of doing it. That gap is a failure of intention, while many mistakenly think it’s related to technology.

AI GIVES BACK TIME

AI is reshaping how work happens, reducing friction across writing, analysis, operations, and decision-making. In our own business, we look for people who lean into AI. It signals curiosity, adaptability, and a willingness to evolve.

We’re equally deliberate about how we use it. AI helps automate repetitive tasks, streamline workflows, and surface better information. It saves time, reduces cost, and creates capacity that didn’t exist before.

EFFICIENCIES GIVE YOU A CHOICE

AI unlocks speed as well as a choice. And that choice is where strategy lives.

Leaders often treat productivity as the goal, though actually it’s a byproduct. The real question is what productivity enables. Without a clear answer, efficiency gains get absorbed into more output, tasks, and noise.

When those gains are intentionally redirected, something different happens. Teams have more space to think, connect, and focus on the work that differentiates a business. Over time, that shift compounds in performance, as well as in how people experience their work.

YOU CAN’T AUTOMATE MEANING

I saw this firsthand while visiting one of our women-led coffee partners in Ethiopia. Coffee is one of the most widely traded commodities in the world, yet the people behind it are often the least visible.
Women worked side by side, singing as they carefully sorted and dried coffee by hand. It’s slow, skilled work, and there are ways that process could improve over time. But what stood out was the pride.

They were producing coffee while supporting their families, strengthening their community, and connecting to something far beyond their region. That sense of meaning is difficult to describe but easy to recognize. Some things need to be protected instead of automated.

As Robin Wall Kimmerer writes, “All flourishing is mutual.” Work is no different. When people feel connected to the impact of their work and to each other, performance follows.

The same applies inside any organization. When people understand why their work matters, they show up differently. They take ownership, adapt more readily, and invest more of themselves in the outcome. AI can support that environment, but it can’t create it.

WHERE AI STRATEGIES ACTUALLY SUCCEED (OR FAIL)

One of the clearest insights from Gallup’s research is that management is among the top drivers of successful AI adoption.

As Gallup’s chairman, Jim Clifton, has noted, managers account for at least 70% of the variance in employee engagement. That influence becomes more important in the AI age. Employees who feel supported in using AI are far more likely to recognize its value and integrate it into their work.

At the same time, Gallup found that manager engagement is declining. What used to be a strength—leaders who were more engaged than their teams—is no longer something companies can rely on. That’s the real risk in the AI era. Not that machines replace people, but that leaders fail to bring people with them.

AI transforms organizations over time. It gets adopted (or ignored) team by team, manager by manager. Success depends on whether leaders create the clarity, trust, and support required to use it well.

MEANING IS A PERFORMANCE ADVANTAGE

Meaning drives performance. When people feel connected to their work, engagement rises, adoption improves, and teams navigate change more effectively.

As machines take on routine tasks, what remains human becomes more valuable: judgment, creativity, empathy, and care. These are the capabilities that differentiate organizations and shape how work is experienced.

AI is giving companies back time and capacity at a scale we haven’t seen before. That creates a choice: Use it to extract more or use it to elevate what work is for.