Angel One Group Chief Executive Officer Ambarish Kenghe has said artificial intelligence is set to create new kinds of jobs, even as it transforms the nature of work across industries. Speaking on the broader implications of AI for the labour market, Kenghe argued that demand for knowledge work will rise rather than diminish, with the technology acting as a force multiplier for human capability instead of a simple replacement engine.
His remarks come at a time when companies across India are reassessing how automation, machine learning and generative AI will affect hiring, productivity and workforce design. In the startup and venture capital ecosystem, where efficiency and scale are often central to growth, AI is increasingly being viewed not only as a tool for cost reduction but also as a catalyst for new business models, new functions and new forms of specialist employment.
Work Will Be Recast
Kenghe's central argument is that AI will not eliminate the need for human judgment, but will instead shift the centre of gravity of work toward higher-order tasks. As routine and repetitive functions become more automated, demand is expected to grow for roles that involve interpretation, oversight, problem-solving, customer understanding and strategic decision-making. That, in turn, could create a fresh layer of jobs that did not exist in the traditional enterprise structure.
The Angel One executive's comments reflect a wider debate in India's technology sector, where leaders have increasingly moved away from framing AI as a pure jobs threat. Instead, many now describe it as a transition that will reward adaptability. For workers, that means the ability to use AI tools, understand data, collaborate with intelligent systems and move across functions may become as important as domain expertise alone.
Kenghe said the rise in knowledge work would require every individual to transform themselves. That observation points to a significant labour-market challenge: the pace of change may outstrip the speed at which formal education and corporate training can respond. In practical terms, employees may need to reskill more frequently, while employers may need to redesign roles around human-machine collaboration rather than fixed job descriptions.
India's Skills Challenge
For India, the stakes are especially high. The country has a large, young workforce and a deep pool of technology talent, but it also faces persistent gaps in advanced digital skills. As AI adoption spreads from financial services and software into retail, healthcare, manufacturing and logistics, the demand for workers who can supervise, fine-tune and apply AI systems is likely to increase.
That could open opportunities for startups building AI-native products, enterprise software, workflow automation tools and training platforms. Venture investors have already shown strong interest in companies that can help businesses deploy AI at scale, particularly where the technology can improve productivity without requiring massive capital expenditure. If Kenghe's view proves accurate, the next wave of job creation may come not only from AI labs and model developers, but from the broader ecosystem of implementation, governance, compliance and customer-facing services built around AI adoption.
At the same time, the transition is unlikely to be evenly distributed. Workers in roles that are highly structured and rules-based may face greater pressure to adapt, while those in creative, analytical or relationship-driven functions may see their work augmented first. The challenge for companies will be to manage that transition without widening skill inequality inside the organisation.
From Automation To Augmentation
Kenghe's remarks also underscore a broader shift in how business leaders are thinking about AI. The most durable gains may come not from replacing people, but from augmenting them. In financial services, for example, AI can help with customer support, fraud detection, risk analysis and personalised recommendations, while human teams retain responsibility for complex decisions, trust and accountability.
That model suggests a future in which the most valuable employees are not those who compete with AI, but those who know how to work with it. For startups, this may mean building teams that are smaller, faster and more specialised, with AI handling a growing share of repetitive tasks. For larger firms, it may mean reorganising workflows around productivity gains that can be reinvested into new products, markets and services.
The broader message from the Angel One chief is that AI should be seen as a structural change, not a temporary technology trend. If knowledge work expands as he expects, the labour market may not simply lose jobs to machines; it may generate entirely new categories of work that are only now beginning to emerge. The winners, he suggested, will be those who adapt early and continuously.