By A Ganesh
Artificial intelligence (AI) is no longer simply changing the tools employees use; it is reshaping how work gets done. As technology takes over repetitive, data-intensive and transactional activities, businesses must address a fundamental question: how should the roles themselves be redesigned?
The shift runs deeper than most organisations admit. AI is not merely changing the tasks within jobs; it is making the traditional job description itself obsolete. Organisations must therefore reconsider how work is divided between people and technology, what outcomes each role must deliver and which capabilities employees need.
From task-based roles to outcome-driven work
Consider a credit officer whose goal is to make a sound lending decision. Instead of spending much of the day compiling customer information, the officer can work from an AI-assisted summary, identify gaps and focus on understanding the customer’s cash flow. AI can support parts of the process, but the officer remains accountable for the decision.
This requires starting from a different question: not “what does this role do?” but “what value must this role create for the customer or the organisation?” The next question is which tasks technology should perform and which should remain led by people. The redesigned role is a different job, not the old job with technology attached.
Return to the credit officer. AI and analytics can organise information and flag inconsistencies. But a lending decision also requires knowledge of the customer’s occupation, cash-flow patterns and local economic conditions. An experienced employee must interpret that information and own the final decision.
Shriram Finance’s own experience illustrates this. We apply automation and analytics to credit decisioning and payment collections, where speed and scale matter most. Relationship management remains human-led. Because around 85 percent of our branches are in rural and semi-urban India, our field staff understand why a small business owner’s repayment may slip a month while he reinvests in his business. They can tell the difference between enterprise and default.
This is the real promise of job redesign: not the substitution of people, but their movement towards responsibilities of greater value.
Redesigning skills alongside jobs
Jobs cannot be redesigned without reconsidering skills. But the answer is not a longer list of future skills. What sets professionals apart in the AI era is a specific combination: AI fluency, grounded in domain expertise and expressed through human judgment.
AI fluency does not mean becoming a technology specialist. It means knowing how to use AI tools, frame the right questions and recognise when their outputs need challenging. Domain expertise turns that fluency into value: only someone who understands the business can judge whether the patterns technology finds are relevant, which is why we recruit industry specialists when lending to larger Micro, Small and Medium Enterprises (MSME) businesses. Human judgment makes the combination accountable: someone must weigh context, ethics and individual circumstances, and own the decision.
The manager as work architect
If jobs are no longer fixed bundles of tasks, someone must redesign them continuously. That responsibility falls to the manager, who acts less as a supervisor and more as a work architect. The architect decides what humans and AI should each do, where accountability sits, which tasks technology should own outright, and which must remain entirely human.
Human judgment remains central
Business decisions often involve context, empathy, experience, ethics and accountability. These cannot be read from data alone and remain human responsibilities. AI should support, not replace, human judgment under governance that makes clear who reviews its recommendations and who is accountable for the decision.
Managing the human side of job redesign
Changes in job design can create uncertainty when the conversation is dominated by job displacement. Our position is unambiguous: we do not see AI reducing our headcount. Shriram Finance is more than 79,000 people today, and we continue to hire even as we automate parts of credit decisioning and collections. The parallel is the computerisation of bank branches in the early 2000s. Despite fears of mass job losses, clerks became computer operators, and banks today need more people, not fewer. AI is likely to follow the same pattern, provided organisations invest in learning pathways.
A practical approach to redesigning work
Organisations can begin by examining each role task by task, in five steps:
1. Break a role into its core tasks and decision points.
2. Identify which tasks AI can automate, which it can augment and which require human leadership.
3. Redefine the role around the outcome it must deliver.
4. Assess the employee’s current capabilities and identify the reskilling needed.
5. Measure whether the new design improves productivity, customer experience, decision quality and employee development.
The strategic point is this: competitive advantage in the AI era will not come from adopting AI; every organisation will do that. It will come from redesigning work around AI continuously. The ability to re-divide work between people and machines, reskill employees and redeploy them towards higher value cannot be bought off the shelf.
The most useful question is no longer “Which jobs will technology replace?”
It is “How can jobs be redesigned so that people and technology perform better together?”
Organisations that answer it well, continuously rather than once, will find that AI becomes not merely a source of efficiency but the means of building a more skilled, agile and future-ready workforce.
The author, A Ganesh, is CHRO of Shriram Finance.
DISCLAIMER: The views expressed are solely of the author and ETHRWorld does not necessarily subscribe to it. ETHRWorld will not be responsible for any damage caused to any person or organisation directly or indirectly.