AI fluency drives results. Learn how leaders can align training, experimentation, and workflows to build it in three months.
Julie Jares
Director, Newsroom, Thought Leadership
Workday
Across industries, leaders are discovering a hard truth: access to AI does not equal value from AI.
Research from Workday revealed that while a majority of employees are experimenting with AI tools, only 14% report deriving meaningful value. Meanwhile, McKinsey found that just 1% of leaders consider their organizations truly mature in AI deployment.
It’s a disconnect with major implications during a pivotal moment in the business world. AI fluency—the ability to confidently understand and apply artificial intelligence within a field—will be a defining characteristic of high-performing, innovative organizations going forward.
For HR leaders in particular, the challenge goes beyond adoption. They are increasingly responsible for reimagining how human employees and AI agents work together as a unified workforce.
With the right framework, teams can be quickly brought up to speed—even those that are currently struggling to see the value. It starts at the top, with HR leadership accepting and embracing the main challenges in front of them: communication, positioning, and training.
Report
High AI fluency correlates with a 45% higher likelihood of achieving strategic objectives.
The AI Fluency Gap Is a Leadership Challenge
Organizations are investing heavily in AI training. Workday’s global study found that 66% of leaders cite skills development as a top priority. Yet only 37% of employees who spend significant time correcting AI output say they have increased access to meaningful training.
That means they’re spending a lot of time mired in the downside of AI without having the proper guidance to minimize it. And largely, it’s not about tool access, but how people are taught to think about and work with AI.
Too often, AI is viewed as a threat to jobs, a shortcut to productivity, or a managerial authority that “knows best.” Instead, organizations need to frame AI as something else entirely.
The most successful organizations are developing a collaborative, teammate-style relationship with AI—not treating it as a boss, evaluator, or oracle. Research shows that while 75% of workers are comfortable teaming up with AI agents, only 30% say they are comfortable being managed by one.
When employees think of AI as a manager:
When they frame AI as a teammate:
Mindset drives behavior, so spearheading this mental shift is key. The human–agent collaboration model requires clear boundaries:
When a collaborative approach clicks, the results follow: Per Anthropic’s AI Fluency Index, “the most common expression of AI fluency is augmentative—treating AI as a thought partner, rather than delegating work entirely. In fact, these conversations exhibit more than double the number of AI fluency behaviors than quick, back-and-forth chats.”
The most successful organizations are developing a collaborative, teammate-style relationship with AI—not treating it as a boss, evaluator, or oracle.
Cultural transformation doesn’t happen overnight, but real progress can take place within a focused 90-day framework.
Days 1–30: Align on Business Outcomes
Start with the business case instead of the technology:
AI fluency improves when employees understand why AI matters to the business, versus just figuring out how to prompt a tool and move faster. Successful adoption begins with clarity around outcomes, accountability, and trust.
Days 31–60: Create Room for Experimentation
Fluency requires practice:
This is where psychological safety is a big factor. Employees must feel empowered to test, refine, and question AI outputs. Position the objective not as “AI training hours,” but collective workflow improvement.
Organizations should train employees not only on how to use AI tools, but on how to use the time AI creates. When routine tasks are automated, employees can focus more on work humans do best: strategy, creative problem-solving, relationship building, and innovation.
It’s critical to empower managers to put these messages and practices into action. Workday’s research found that only 28% of leaders prioritize manager enablement, which can leave employees feeling stuck on an island.
Days 61–90: Embed and Measure
By the third month, experimentation should transition into embedded practice:
Equally important is understanding how employees are reinvesting the time AI frees up—whether in higher-value decision-making, more strategic work, or deeper collaboration across teams.
AI fluency is multidimensional. It includes judgment, adaptability, and ethical reasoning. Measurement has to reflect that complexity.
Only 5% of U.S. workers are considered AI fluent, according to Google.
One of the most common mistakes organizations make is launching AI training programs disconnected from daily work — overemphasis on technical features and too little attention paid to the true operational impact.
That’s why developing a shared view of desired business outcomes during those first 30 days is so important. When training initiatives are tied to results, everyone can see what they’re working toward and why. From there, experimentation is more focused and measurement is more meaningful.
Fluency accelerates when training and practical exercises align to real work. One opportunity? Weaving AI capabilities into actual roles and job descriptions so people can clearly see why and how the technology is valuable to their function. Workday research finds that, in organizations struggling to achieve net productivity gains, less than 25% of roles have been updated to reflect AI capabilities.
When training initiatives are tied to results, everyone can see what they’re working toward and why. From there, experimentation is more focused and measurement is more meaningful.
For HR leaders, the task of building AI fluency is never finished. It has become a core focus of the job, now and going forward. The framework above shows how an organization can take intentional steps to go from confusion and stasis to socialized, structured AI usage across teams.
When employees view AI tools as teammates, working side-by-side with accountability and trust built in, that’s AI fluency, and readiness for what’s next.
Report
62% of leaders welcome AI, but only 55% of employees feel the same way. Closing this AI trust gap and ensuring that your organization is prepared for widespread AI implementation will prove decisive to your company's future success.