AI: A Place for Authentic Intelligence in the World of Artificial Intelligence

There’s a particular kind of unease settling over organizations right now. AI has stopped being just a tool that speeds things up and has started making calls that used to belong to people — who gets a loan, which resume gets a second look, what a scan might mean. In India, where the IndiaAI Mission is pouring resources into digital and computational infrastructure at national scale, that shift is happening fast. Fast enough that a real question is starting to surface underneath all the enthusiasm: if machines can answer so quickly, what’s left for us to actually do?

The honest answer is that AI has brought to the fore those parts of human judgment that were always the hardest to automate: reasoning under uncertainty, empathy, and the willingness to be held responsible when things go wrong.

When Expertise Becomes Searchable

Junior professionals used to earn their stripes the slow, repetitive way such as by debugging messy code, drafting the same contract for the hundredth time, cleaning up spreadsheets nobody else wanted to touch. Tedious, yes, but it was in that tedium where instinct got built. Generative tools have quietly taken most of that work away, and the result is a workforce that risks never developing the judgment those repetitive tasks used to teach.

Nasscom’s 2026 report on India’s AI-native talent puts a number on this worry. Nearly 70% of early-career tech professionals in India now count as “AI-proficient.” But only around 23% qualify as genuinely “AI-native,” meaning they can direct, question, and orchestrate AI rather than just lean on it. Nasscom’s own leadership has been blunt about the risk: without deliberate effort from both academia and industry, India could end up with a generation that’s AI-reliant rather than AI-native. When the machine hands you a baseline answer instantly, the real skill becomes knowing when to doubt it.

Bias Doesn’t Disappear — It Gets a Better Disguise

There’s a comforting story people tell about algorithms: that math is neutral, so machine decisions must be fairer than human ones. This is false. Models learn from historical data, including every prejudice hidden within that data. Feed a biased past into a model and it simply window-dresses it as an objective score.

NITI Aayog’s Towards Responsible AI for All framework names this problem directly, flagging algorithmic exclusion, the difficulty of explaining why a model decided what it decided, and the near-impossibility of assigning real accountability when something goes wrong. When a flawed model wrongly denies someone a loan, misreads a cardiac scan, or disregards a resume without human oversight, there’s no line of code you can put in front of a review board. Code doesn’t feel the weight of a bad call. A person has to own it — which means organizations can’t quietly hand over “ultimate ownership” the way they’ve handed over routine execution.

So, What’s Actually Still Ours?

Strip away the statistics and pattern-matching, and what’s left is contextual empathy, moral judgment, and wisdom nobody codes into a model because nobody can quite articulate it. Picture Indian healthcare or agriculture: AI can flag cardiovascular risk or forecast a likely crop failure from satellite and weather data, sure. What it can’t do is factor in a farmer’s specific debt situation, or deliver a difficult diagnosis to a frightened patient with the sensitivity the moment demands.

Thus, it is important to advocate for humans actively interpreting ambiguous situations, weighing ethical trade-offs, and reading the unwritten rules of a culture that no dataset fully captures. Value creation in a person has quietly shifted from producing information to making sense of it.

Looking Inward, Not Just Forward

Plenty of organizations can move faster than their people can adapt — that’s not really in question anymore. The harder question is whether speed without direction is worth anything at all. The businesses that come out ahead won’t be the ones that swap humans out fastest; they’ll be the ones that build human judgment directly into how their systems work. As AI absorbs the routine cognitive load, what becomes genuinely valuable is scepticism, ethical reasoning, and emotional intelligence, all of which do not revolve around processing information. AI can hand us answers all day. Only people can tell us what those answers are actually worth.

Anakta is a 2026-28 PGDM-HRM student of XLRI Jamshedpur.