By now, every panel discussion and boardroom debate has echoed the same question: Is AI taking jobs or creating them? That is the wrong question. The sharper one is this: What exactly has AI changed in the economic structure of work?
For decades, India mastered the scale game. We built businesses on manpower leverage, perhaps, a lingering mindset of the Industrial Revolution’s assembly line. The model was a pyramid: large teams handled modular, repeatable tasks. Entry-level engineers wrote code blocks. Analysts processed data. Content teams created optimized drafts and Marketing focused on paid and unpaid metrics. The pyramid worked because labour was abundant and tasks were divisible. More people meant more billable hours. AI has altered that equation.
When productivity per employee rises sharply because machines handle modular work, the firm that generates higher revenue with fewer people becomes structurally stronger. Look at global AI-native startups. Many operate with teams a fraction of the size of legacy players but command disproportionate valuations.
For small and mid-sized Indian firms, this is liberating. They can personalise beyond standardisation. They can move faster, unburdened by internal coordination layers. Today, a five-person firm equipped with AI can produce what once required twenty. Code is generated instantly. Audio and visual content is created in a fraction of the time. Research summaries arrive in seconds.
The economics of output per employee have changed for good but now, the uncomfortable truth.
AI is narrowing the base of the employment pyramid. India produces over one crore graduates every year. Roughly half are considered unemployable by current standards. That means millions of young professionals enter the market annually hoping to begin at the base. Historically it means execution work that allows them to “learn by doing” while seniors are directed. Artificial Intelligence has walked straight into that layer.
This is a structural correction of the employment model. The market will not need as many executors; it now thrives on integrators and orchestrators. It will demand higher-order skills earlier in their career journeys. These are mainly – problem framing, analytical reasoning, and cross-functional thinking. Being technically trained will not be sufficient. Being contextually intelligent will matter more.
The National Education Policy 2020 rightly speaks of multidisciplinary learning and skill integration. But urgency must match the pace of technological change. If institutions especially in Tier-2 and Tier-3 cities do not recalibrate immediately, we risk a “digital apartheid,” where the divide isn’t access to technology, but access to relevance.
AI has eliminated the mediocrity of the middle. It has devalued the ability to simply follow instructions. The future will belong to those who have the judgment to decide which tasks are worth doing in the first place. Experience, and not necessarily by age or the degree, therefore, becomes compounding capital. Seasoned professionals who combine domain wisdom with AI fluency will be amplified. Their leverage increases because they are no longer supervising repetitive labour but are directing intelligent systems. To aim for excellence we will have to let the process of achieving it trickle down from leadership, to senior management, to managers and to freshers. Therefore training must shift toward developing “domain intuition” to make the right decisions and be purposeful.
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