An analyst arrives at work to discover that overnight, artificial intelligence has completed her morning routine: dashboards updated, insights generated, weekly report drafted and polished. Tasks that once consumed half a day now require mere minutes. What follows? This scenario, once confined to speculative fiction, has become quotidian reality for a growing cohort of professionals as generative AI (Gen AI) transforms workplaces. The question confronting organisations is no longer whether AI will create free time, but how that newfound temporal abundance should be deployed.
“The more thoughtful approach begins before the AI is implemented,” notes Manish Majumdar, head – HR, Centum Electronics. Forward-thinking organisations are anticipating time savings and redesigning roles concurrently with AI deployment. For those whose positions are only partially automated—such as decision-makers or process architects—liberated hours represent potential for deeper analysis, strategic innovation and continuous improvement. Yet this metamorphosis requires deliberate cultivation: organisations must encourage such use of time, reinforce it through recognition systems and incorporate it into performance frameworks.
“The more thoughtful approach begins before the AI is implemented.”
Manish Majumdar, head – HR, Centum Electronics
When a task’s duration shrinks from eight hours to four, does this herald idle hands? Quite the contrary. “You will be engaging yourself, enhancing your skills, or contributing to other areas—be it cross-functional or cross-vertical,” emphasises Anil Mohanty, chief people officer, DN Group. A talent acquisition specialist might invest newly available time in understanding employee engagement or competency mapping, thereby expanding both personal horizons and organisational value.
This pattern reflects a fundamental truth: AI isn’t eliminating work but reconfiguring it. The temporal dividend it yields is optimally invested in reskilling, innovation and deeper cross-functional collaboration. Rather than confining employees to rigid roles, organisations can adopt more fluid structures where individuals pivot across functions as requirements evolve, fostering institutional agility.
“The answer lies in strategic thinking, ideation, and value creation.”
Ravi Mishra, head-HR, BITS Pilani
In numerous workplaces, previously time-intensive tasks—payroll administration, training-needs analysis, scheduling, even drafting correspondence—are now executed instantaneously by AI systems. This swift obsolescence of established processes is generating visible disengagement, particularly among younger staff. However, the dynamics are considerably more nuanced.
As Generation Z leverages AI tools to complete assignments rapidly, more seasoned colleagues—habituated to labour-intensive methodologies—confront an unsettling proposition: Does efficiency equate to worth? “In my team,” reveals Ravi Mishra, head – HR, BITS Pilani, “a 56-year-old and a 24-year-old may be doing the same job—but the younger employee wraps up quickly with the help of tech. This creates friction. The seniors feel undervalued, not because they are less capable, but because the ground beneath their definition of productivity is shifting.”
“You will be engaging yourself, enhancing your skills, or contributing to other areas—be it cross-functional or cross-vertical.”
Anil Mohanty, chief people officer, DN Group
Herein lies an uncomfortable verity: whilst loyalty and experience were once paramount virtues, they no longer suffice in an environment where AI flattens traditional hierarchies of effort. This, Mishra cautions, could precipitate significant unemployment among mid-career professionals unless roles are reimagined proactively.
If routine tasks are increasingly automated, what remains for human attention?
“The answer lies in strategic thinking, ideation, and value creation,” Mishra asserts. He highlights a transition from competitive advantage—where firms outpace rivals through incremental innovation—to added advantage, wherein entirely novel models emerge, often from unstructured thinking. This necessitates fundamental role redesign predicated not on fixed task catalogues but on dynamic capabilities.
A strictly utilitarian approach—where every moment must demonstrate measurable productivity—undermines the transformative potential of AI. If the objective is optimising human potential, then contemplative space, wellbeing and even leisure become integral to the equation. Several hours of slack might provide precisely the breathing room employees require to conceive new ideas, acquire skills or simply recuperate. Organisations already struggling with burnout must resist equating each unallocated minute with wasted capacity.
Simultaneously, as Mohanty suggests, “fostering cross-functional collaboration—such as encouraging HR professionals to understand finance or enabling L&D experts to explore recruitment—cultivates holistic growth and adaptability.”
Human resource leaders play a pivotal role in orchestrating meaningful transition. Strategies including personalised learning journeys, designated innovation periods and structured recovery intervals can maintain engagement despite reduced task loads. Skip-level consultations, employee-led job redesign and AI-readiness evaluations can further empower individuals to shape their trajectories within this evolving landscape.
Critically, employees must be co-architects of this transformation. Their intimate knowledge of workflows offers invaluable insight regarding which functions require human oversight versus automation candidacy. Encouraging experimentation with AI tools, documentation of learning and proposals for role modification fosters cultures of trust and ownership.
What organisations must studiously avoid is replacing human effort with AI-generated output only to burden the same staff with unrelated tasks that neither leverage their capabilities nor align with strategic objectives. As Majumdar aptly observes, “Some people simply don’t have the mindset for continuous innovation or Kaizen-like thinking. Forcing such expectations uniformly leads to disengagement and resistance. One-size-fits-all solutions don’t work in human systems—even if they work for machines.”
The notion that AI will precipitate widespread disengagement represents, according to Mohanty, merely “grapevine” speculation. “There’s no real example of someone working just one hour a day because of AI. That’s a myth. Instead, you’ll see the same tasks being completed within the scheduled time, not beyond it.” The consequence is improved work-life balance, fewer extended workdays and enhanced satisfaction rather than ennui.
The advent of generative AI thus challenges organisations to transcend task-allocation paradigms in favour of purpose-driven human engagement. This represents not merely a productivity narrative but a fundamental recalibration of how work, contribution and value are conceptualised in contemporary workplaces. For those who navigate this transition adeptly, the prize is not just efficiency but a more meaningful integration of human creativity with technological capability.
