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jobs
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October 12, 2026
The rise of the 'unhireable' candidate: When good professionals don’t fit recruitment filters
The term 'unhireable' does not mean that the person cannot do the job, but that a recruitment platform filter has already decided not to show them to recruiters
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September 21, 2026
What industry leaders really want in 2026 and beyond
This shift is driven by the dissolution of traditional boundaries between fields like finance, technology, and operations, making holistic, cross-functional expertise a prerequisite for success
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September 07, 2026
Job churn? Where new jobs are popping up
The electric vehicle (EV) ecosystem is a prime example, projected to create four crore jobs by 2030, extending beyond manufacturing to encompass financing, sales, and servicin
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September 02, 2026
Was AI really behind massive Uber layoffs of 3,300 employees? What CEO said about company's 'autonomous future'
This is Uber's sharpest series of job cuts after it let go of a whopping 6,700 jobs, or about a quarter of its global workforce, in May 2020 due to a massive crash in demand driven by the COVID-19 pandemic
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July 15, 2026
India's jobs crisis needs a skills revolution, say experts | World Youth Skills Day
A skills-first ecosystem is crucial for India to realise its demographic dividend and move beyond a degree-centric education model, according to experts at the Skills First India Leadership Dialogue
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July 14, 2026
OPINION | The skills economy: How industry and academia can shape India’s next generation of talent
World Youth Skills Day: India’s industry and academia need to come together and collectively co-create the curriculum so that learning translates into livelihood
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July 03, 2026
OPINION | India’s AI jobs are booming: Can our graduates do the work or only talk about it?
While employers seek AI talent, a stark reality is that many graduates, despite having degrees, lack the hands-on skills to be deployable
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June 26, 2026
OPINION | The limits of algorithmic hiring: Why AI cannot judge human potential
AI reliance, while efficient, carries significant risks as these systems are trained on past data, potentially perpetuating existing biases and overlooking candidates with untapped potential