By Dr Navin M Punjabi
A student walking into a classroom today is likely to have already encountered artificial intelligence in some form. They may have used it to understand a difficult concept, summarise a reading, explore ideas for a project or simply find a faster way of getting started.
This is no longer a distant possibility. AI is becoming part of how young people learn, research and work. For higher education, the question is no longer whether students will use AI, but whether they will know how to use it well.
A changing reality
The scale of this change is significant. Stanford University’s 2026 AI Index reports that four out of five university students now use generative AI, while AI adoption among organisations has reached 88%.
Yet institutions are still adapting. A UNESCO survey found that only 19% of higher-education institutions surveyed had a formal AI policy, while another 42% were developing one.
The gap is telling. Students are experimenting with AI faster than institutions are developing frameworks to guide its use. This makes the conversation around AI in education much broader than simply deciding whether students should be allowed to use these tools.
Beyond Tools
AI fluency is not the same as knowing how to use ChatGPT, Gemini or another generative AI platform. A student may know how to write a prompt and still not know whether the response is accurate. They may generate a financial analysis without recognising a flawed assumption, or produce a well-written essay without questioning the information behind it.
Being AI-fluent means understanding what AI can do, recognising where it can go wrong, checking its outputs and making a considered decision about whether they should be trusted.
Put simply:
- AI literacy is knowing what AI can do
- AI fluency is knowing when to use it
- How to use it
- How to question it and
- When not to use it
Every discipline
This capability cannot remain limited to technology programmes.
A commerce student will encounter AI in accounting, financial analysis, banking, marketing and business decision-making. A management student will work with AI-enabled operations and analytics. Students in the humanities will increasingly use AI for research, communication and analysis.
The applications will vary, but the underlying ability will remain the same: being able to work with AI while retaining independent judgement.
This is why AI fluency should be treated much like communication, problem-solving and digital literacy as a foundational capability that students carry with them regardless of their chosen degree.
Human judgement
The workplace is already reinforcing this shift. According to the National Association of Colleges and Employers, more than one-third of entry-level jobs now require AI skills, while 28% of employers say they are looking for early-career talent that can use AI in their work.
But technical familiarity alone will not be enough.
As AI becomes better at producing answers, human judgement becomes more valuable. Students need to learn how to frame a problem, ask the right questions, challenge an output and bring their own understanding to the final decision.
AI can suggest a business strategy. A student must still decide whether it makes sense. AI can identify a pattern in a dataset. A student must determine whether that pattern is meaningful. AI can draft a communication. A student must understand the audience, context and consequences. The ability to question an answer may ultimately be more valuable than the ability to generate one.
Rethinking classrooms
This also has implications for how we teach and assess students.
If AI can produce a polished assignment in minutes, perhaps the more meaningful assessment is to ask students to explain how they arrived at their conclusion, what evidence they relied upon and where they disagreed with an AI-generated response.
This does not mean keeping AI outside the classroom. It means bringing it into the classroom thoughtfully. Students should be able to experiment with AI, but they must also learn to verify its outputs, recognise its limitations and take responsibility for the final work.
At K.P.B. Hinduja College of Commerce, this vision is reflected in our evolving academic offerings, including programmes in Artificial Intelligence & Machine Learning and AI-focused learning in management. Through practical, industry-oriented learning, we aim to equip students to use AI responsibly and be workplace-ready.
Responsible use
There is an equally important ethical dimension. Students need to understand privacy, misinformation, intellectual property, bias, academic integrity and responsible use of data. UNESCO’s guidance on generative AI in education emphasises human agency, privacy, inclusion and responsible use.
The HEI’s that succeed over the next decade will not necessarily be those with the most advanced AI tools. They will be those that produce graduates capable of thinking independently while working intelligently with AI. Technology will continue to evolve. Human judgement must evolve even faster. AI fluency is therefore not another digital skill it is becoming a defining attribute of an educated graduate.
The question should not simply be, “Can AI do this for me?” It should also be, “Should I use AI for this, and what responsibility do I retain for the outcome?”
For higher education, AI fluency is ultimately about preparing students for a workplace that will continue to evolve.
We should not aim to produce graduates who compete with machines on what machines do best. We should produce graduates who know how to think with machines without surrendering their own judgement.
That, to me, is the real meaning of AI fluency and why it should become part of what it means to be a graduate, irrespective of the degree one chooses.
Dr Navin M Punjabi is the Principal of KPB Hinduja College of Commerce.
DISCLAIMER: The views expressed are solely of the author and ETEDUCATION does not necessarily subscribe to it. ETEDUCATION will not be responsible for any damage caused to any person or organisation directly or indirectly.
