Today, AI fluency is rapidly becoming the common language of work and a prerequisite for the next chapter of competitiveness. Workers’ practical ability to use and manage AI in their day-to-day, integrate it into workflows, evaluate its outputs critically, and, increasingly, create with it is transforming how work gets done. Unlike many earlier technological capabilities (such as cloud computing) that were relevant mainly to specialists, the demand for AI fluency is spreading across all types of workers, industries, and wage groups. What began as a technical skill is becoming a must-have capability for knowledge workers, blue-collar workers, managers, students, and everyday citizens.

This shift matters because AI’s economic potential will not be realized through technology alone. The largest gains will come when organizations redesign how work gets done—creating new forms of collaboration among people, intelligent agents, and physical automation. AI fluency is the lingua franca of that transition. As more companies and organizations successfully build fluency, the broader US economy will also gain—indeed almost every national economy could benefit from developing this skill in its people. In the following, we examine the fundamentals of fluency, its direct connection to productivity and value, the steps companies are taking to build it, its economy-wide effects, and the collaboration needed to build momentum.

From digital literacy to AI fluency

The spread of digital literacy has transformed the workforce over the past three decades. It may be hard to remember, but skills such as word processing, spreadsheet manipulation, and web design were once the province of specialists. Today, they are baseline expectations across nearly every occupation. AI fluency seems all but certain to follow a similar path—only much faster.

At its core, AI fluency is knowing when and how to use AI to achieve better outcomes—and then, once work is delegated to AI, knowing how to verify and improve the results. Critically, AI fluency also means strengthening the distinctly human capabilities that become more valuable as AI becomes more capable: framing the right problems, exercising judgment under uncertainty, synthesizing ideas into compelling narratives, understanding other people, and knowing when to challenge or override AI-generated outputs. Taken together, AI fluency combines practical AI capabilities with the human-centered practices—such as sound judgment, adaptability, collaboration, continuous learning, and responsible decision-making—that are needed to apply AI effectively. Like digital literacy before it, AI fluency is fast becoming a foundational capability that amplifies the expertise workers already possess, enabling them to do more—faster and better—when harnessed correctly.

As AI evolves, so too does fluency in its use. Early discussions focused on the ability to use AI tools effectively and manage them responsibly. Today, the definition is already expanding to include creating and developing with AI. New capabilities such as building applications through natural-language prompts, orchestrating AI agents, and even “vibe coding” are quickly becoming part of how work gets done.

Demand for AI fluency skills is almost 14 times higher than it was three years ago (exhibit). Few if any workforce needs have evolved and spread at this velocity.¹ While demand remains concentrated in technical and business occupations, it is already expanding into fields ranging from engineering and skilled trades to education. It’s apparent that AI fluency is not a fixed skill set, but a rapidly evolving capability that is becoming foundational across the entire workforce.

Why AI fluency is the key to value capture

AI-powered agents and robots could unlock an estimated $2.9 trillion in annual value for the US economy by 2030.² But as companies are learning, capturing that value requires more than deploying new technologies. It will require organizations to rethink how work fundamentally gets done.

Organizations will create value from AI in different ways. Some value comes horizontally, by enabling employees across the organization to use AI to improve their own productivity. Additional value comes vertically, by redesigning domain-specific workflows and building AI-enabled solutions tailored to particular functions or business processes.

The biggest gains from AI are unlikely to come from the first category, automating tasks one by one. Companies are already noticing that, while the majority of workers are using the tools productively, enterprise value is lost in the ether. Instead, the biggest gains will come from redesigning workflows around collaboration between people, agents, and robots. For most of the past century, organizations were designed around humans performing work, making decisions, and coordinating with one another. Technology was, at most, a tool that supported those activities. However, work will increasingly be carried out by teams that combine human judgment with machine intelligence. The challenge is not simply adopting AI—it is learning how to orchestrate these new forms of collaboration effectively.

That is where AI fluency becomes essential. AI fluency is the skill that helps workers determine what to hand off to an AI agent, what to verify before acting on a recommendation, what to escalate to a human decision-maker, and where human judgment, creativity, or accountability must remain in the loop. Ninety-four percent of employees are familiar with the tools, and many are already using AI effectively in their own work.³ Now, AI-fluent managers, champions, and advanced users will also redesign workflows and help their teams build new ways of working around AI. AI fluency will be the new language of coordination inside organizations.