As artificial intelligence (AI) reshapes the workplace, leaders are asking urgent questions: Which tools should we adopt? Which roles will change? How do we increase productivity? How do we stay ahead?

But one of the most important questions may be the one too few organizations are asking:

Are our people ready for this much change?

Gallup’s State of the Global Workplace 2026 report offers a sobering answer. Global employee engagement declined for a second consecutive year, falling to 20 percent, its lowest level since 2020. Gallup estimates that low engagement cost the global economy approximately $10 trillion in lost productivity last year. At the same time, AI adoption is not yet translating into the broad organizational gains many leaders expected. Among U.S. workers in organizations that have implemented AI, 65 percent say AI has had a positive impact on their personal productivity, but only 12 percent strongly agree that AI has transformed how work gets done in their organization.

That gap matters.

AI may help individuals move faster. But transformation is not just about speed. It requires trust, coordination, learning, judgment, and shared commitment. In other words, it requires human readiness.

One of Gallup’s most important observations is that employee engagement can be understood as “a measure of readiness for change.” This is a powerful reframing. Engagement is often treated as a morale metric, something organizations track to see whether people are happy, motivated, or satisfied. But in a period of disruption, engagement becomes something more strategic. It tells us whether people have enough connection, clarity, energy, and confidence to move through uncertainty together.

That is where meaningful work becomes essential.

Meaningful work is often misunderstood as something soft, personal, or nice to have. But when the ground is shifting, meaning becomes infrastructure. It helps people understand why change matters, where they belong in it, and how they can grow through it rather than simply endure it.

In our research, we found that meaningful work is built through three core experiences: community, contribution, and challenge. In the context of AI and rapid workplace change, these three experiences become three readiness questions every leader should be asking.

Community: Do I trust the people I’m changing with?

Change is much harder when people feel alone.

In uncertain times, employees do not only evaluate the change itself. They evaluate whether they trust the people leading it and the people going through it with them. Will my manager tell me the truth? Will my team support one another? Can I ask questions without looking incompetent? Can I admit that I am worried?

This matters enormously in the age of AI. Many employees are being asked to learn new tools while privately wondering whether those same tools will eventually make their jobs less secure. Gallup reports that concerns about AI-related job loss are rising. In early 2026, 18 percent of U.S. employees said it was very or somewhat likely their job would be eliminated in the next five years because of technological innovations such as automation or AI. Among employees in organizations where AI has already been implemented, that number rose to 23 percent.

Leaders cannot build readiness by pretending those fears are irrational or by offering vague reassurances that “AI will free people up for more meaningful work.” That may be true in some cases. It may not be true in others. Employees know the difference between clarity and vague reassurance.

Community begins with honest conversations and grows when leaders create environments where people can surface concerns, learn together, and support one another through uncertainty. Trust does not eliminate anxiety, but it changes what people do with it. Instead of withdrawing, employees are more likely to experiment, collaborate, and ask for help.

Contribution: Do I understand why this change matters?

People are more willing to change when they understand what the change is for.

This is one of the great missed opportunities in AI implementation. Too often, organizations introduce AI through the language of efficiency—faster workflows, lower costs, increased output. Those benefits may matter to the business, but they rarely create a sense of purpose for employees. In some cases, efficiency language can actually increase fear. If the only story people hear is “We can do more with less,” they may wonder whether they are the “less.”

Contribution gives people a more human reason to engage. It helps employees see how the change improves the lives of customers, patients, students, clients, colleagues, or communities. It connects new tools to real outcomes.

Gallup’s report notes that well-being increases when employees see their work as intrinsically rewarding and good for others. That is an important finding. People are not only asking, “Can I keep up?” They are also asking, “Does this still matter?”

Leaders need to answer that question clearly and repeatedly.

The contribution question is not, “How will AI make us more efficient?” It is, “How will this help us serve better, solve better, care better, decide better, or create better?”

When people understand the human value of the change, they are more likely to bring judgment and commitment to it. Without that connection, AI adoption risks becoming another compliance exercise: People use the tools because they are told to, not because they see the point.

Challenge: Am I growing fast enough, with enough support, to meet this moment?

The third readiness question is about growth.

AI is changing not only what people do but also who they believe they need to become. That can be energizing when employees feel supported. It can be overwhelming when they feel abandoned.

Challenge is meaningful when it stretches people in ways that build mastery, confidence, and possibility. It becomes harmful when it is simply constant pressure dressed up as opportunity. This distinction is critical right now. Many employees are being asked to adapt quickly, while teams are lean, managers are strained, and the future of their roles feels uncertain.

Leaders can help by making growth feel possible rather than punitive. That means being clear about what is changing, naming what is still unknown, and creating real opportunities for people to build new capabilities. It also means resisting the temptation to treat adaptation as a character test. When employees struggle with change, it is not always because they are resistant. Sometimes they are under-resourced, overwhelmed, or unclear about what success now requires.

Meaningful work as change infrastructure

The question is not simply, “Are our people willing to change?” but rather, “Have we created the conditions that make change feel worth the effort?”

This is where meaningful work becomes more than a source of motivation, but a form of change infrastructure. Community helps people trust the people they are changing with. Contribution helps them understand why the change matters. Challenge helps them grow into the demands of the moment without feeling abandoned by them.

AI can accelerate tasks, generate ideas, and reshape workflows. But it cannot create trust on a team. It cannot help people feel that their work still matters. It cannot decide whether a stretch assignment is developmental or depleting. Those are leadership responsibilities.

The future of work will be transformed by leaders who understand that people adapt well to change when they trust the people around them, understand the contribution they are making, and believe they can grow into what comes next.