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Tushar Thorat
Product Lead, Research and Innovation, Incubation, TCS
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The COVID-19 pandemic caused an unprecedented collapse in socio-economic activity and has threatened the global economy. There has been a radical change in the way we work, commute, socialize, and communicate even as the lockdown eases and businesses worldwide reopen. Just like how past health crises, like the SARS epidemic, brought in attitudinal shifts in society and business models, experts are speculating a V/L/U shaped recovery for businesses in a post-pandemic environment with a corresponding attitudinal shift in the approach to business. There is no one clear answer on what will work, and organizations need to be prepared to adapt at short notice and develop business resilience as well.
To weather the storm and get back on the path of building resilience and growth, organizations need to adopt machine learning in business more aggressively, invest in new-age technologies like AR/VR, and deploy self-service applications like chatbots to automate manual business processes and engage with customers, thereby giving human-like conversational experiences. A need for quick, data-driven decision-making sees the emergence of a data-driven AI-powered economy, where data and AI in business will be at the core in the effort to drive enterprise digital transformation.
In this paper, we present a strategic framework that highlights the importance of each phase of rebound, and due considerations that need to be given during each of these periods.
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