Why AI fluency is new digital literacy for today’s workforce?

In the early 2000s, knowing how to use Microsoft Office made you “digitally literate.” A decade later, digital literacy meant navigating cloud platforms, collaboration tools, or maybe a basic understanding of data dashboards. Today, the bar has shifted once again with AI.

Let’s be clear: AI fluency isn’t about writing code or building large models. It’s about understanding AI tools, knowing how to use them, anticipate their capabilities (and pitfalls), and, most importantly, collaborating with them to drive tangible outcomes. Whether you’re in sales, marketing, admissions, product management, or customer success, AI fluency is now as foundational as reading or using email.

We’ve automated. Now we need to augment!

For the last 10 years, the conversation has been around automation of tasks, of workflows, of data entry. And that made sense. It gave us scale. But the post-ChatGPT world has redefined the playing field. The shift now is from automation to augmentation. From speeding up tasks to reimagining roles. From process efficiency to intelligence empowerment.

This shift isn’t abstract anymore, it’s playing out right now in the job market. Across industries, we’re seeing teams shrink, roles consolidate, and hiring slow down.

According to a recent study, two-thirds of business leaders (66%) say they would not hire someone without AI skills. Furthermore, 71% of employers would prefer a candidate with AI skills even if less experienced over a more experienced candidate without AI know-how. 

In today’s job market, proficiency with AI tools and applications is considered “as essential as basic digital literacy once was”. Traditional office software skills like using spreadsheets or Word are no longer differentiators. Those have become baseline knowledge. 

We’re starting to hear the same from deans, registrars, and directors of educational organizations that we work with. AI tools are moving from IT labs to every desk on campus. At the same time, it’s tempting to think of AI fluency as the domain of software engineers. 

True AI fluency is far broader:
* Sales professionals who use AI to forecast trends and personalize pitches.
* HR teams leveraging AI to screen talent or even eliminate bias in recruitment.
* Marketers who quickly create campaigns that otherwise would have taken a lot of money and time 

One of the most telling indicators of AI’s impact is the rise of metrics like revenue per employee. Companies with high AI fluency, where every employee is empowered and expected to harness AI, see sharper revenue growth. Not by replacing staff, but by amplifying their output.

ixigo, for instance, has embraced this principle deeply. Its co-founder Rajnish Kumar shared that the company began investing in AI as early as 2017, embedding it into core operations like trip planning, customer interaction, and dynamic pricing. 

Today, with over 40% of its codebase AI-generated, ixigo continues to scale efficiently without bloating headcount. “This is only possible if the mindset inside the team is to use technology and AI instead of just hiring more people,” I recall him saying. 

It’s a powerful reminder that AI adoption isn’t just about tools, it’s about culture. So, to operationalize AI fluency at scale, we must prioritize four strategic levers:

Cross-functional adoption: AI must reach beyond IT teams. It must enter marketing, counseling, curriculum planning, student services, and governance.

Scenario-based learning: Training must focus on real institutional contexts. AI fluency improves when teams interact with tools in the context of their day-to-day decisions.

Ethical literacy: Staff should be equipped to evaluate AI outputs for integrity, bias, and appropriateness. A technically correct result is not always an institutionally acceptable one.

Visible leadership alignment: Executive leadership must signal that AI fluency is not a one-time initiative. It is a long-term competency for institutional resilience. Interestingly, cultivating AI fluency doesn’t mean everyone needs to become a programmer or data scientist. 

In fact, many human-centric skills become even more important in an AI-driven workplace. In short, AI fluency is as much about mindset as skillset. It requires knowing how to ask the right questions of AI, judge its outputs critically, and apply ethical considerations. 

For leaders, this balance is crucial. AI is democratizing expertise across the workforce, but to turn that into performance gains, organizations need employees who pair AI tools with creativity and purpose. In practical terms, that means fostering a culture where teams are not afraid to experiment with AI, and also training them in soft skills (like problem-solving, communication, and ethics) that amplify AI’s effectiveness. 

In a climate of growing layoffs and shrinking roles, it is fast becoming the difference between staying relevant and being left behind. With fewer traditional jobs and leaner teams, organizations aren’t just looking for experience, they’re looking for adaptability. 

As we’ve seen across the institutions we serve, the true power of AI lies not in its complexity, but in how fluently it can be wielded by the people closest to impact, educators, administrators, and advisors. AI fluency is no more just the skill of tomorrow. 

The AI age isn’t something coming, it’s already here. And what’s changing isn’t just technology, it’s expectation. 

-- Naveen Goyal, Founder & CEO, Meritto (A Product of NoPaperForms),