Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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Driverless cars may put drivers out of business and recruitment automation may take away the jobs of some HR professionals, but we must remember that while 'routine' work gets automated with machine learning and AI, 'knowledge' work will still require human intervention


Mayank Kumar, Apoorva Shankar
We've all heard and read enough-if not actually seen the impact in our day-to-day lives-to figure out that artificial intelligence and machine learning are changing the world as we know it. From driverless cars and automated recruiting processes to connected machines and voice assistants, these developments are rapidly boosting our productivity at home and at work.

The late 1990s to early 2000s was the age of the Indian IT sector, which gave rise to an empowered Indian middle class. The IT movement brought the country recognition for identifying and grabbing a global opportunity just by keeping up with industry trends. The sector employs almost 4 million people directly and indirectly. However, of late, the so-called Fourth Industrial Revolution has hit, leaving data and digital-enabled start-ups, young companies and rebooted traditional organisations in its wake.

So, where do all these new trends leave the Indian IT? Unfortunately, the sector has been unable to keep up this time around. For instance, even though Bangalore is known as the hub for all digital-first reboots, Karnataka's revenue from export of electronics, IT software and BT fell by 65% in 2015-16 from 2014-15. Between 2015 and 2017, more than 30,000 employees have been laid off by giants like Wipro, Infosys, TCS, L&T, IBM, Flipkart, eBay, etc. IT companies are claiming that layoffs are part of the organisation's technology transformations to keep up with the changing business needs.

In the Indian IT industry, revenue from digital technology projects is growing 7x faster than from traditional projects, and by 2020 both sectors together will be generating $225 billion in revenue. This is naturally enabling a transformation of the traditional roles within IT as well. Systems administrators are turning into system and network architects, web designers are more focused on user experience, data centre specialists now seek to specialise in information insight enabling, and once a project manager is now a product manager.

Driverless cars may be putting drivers out of business and recruitment automation may make the job of some HR professionals redundant; however, we must be cognisant of the fact that where some 'routine' work gets automated with the use of machine learning and artificial intelligence technologies, 'knowledge' work will continue to require human intervention. Even if technology can give us the answers, human beings will always be the ones to know which questions must be asked. Dave Wright (CIO at ServiceNow) recently said in an interview that the biggest misconception was job loss due to new technologies, "Machine learning and AI do not take jobs away; they augment the skills of IT professionals."

The narrative of fear around job losses has known to repeat, periodically, over the years when industries are poised for change-the impact of power loom on textile workers, washing machines on professional hand-washers of clothes, etc. But each time more jobs have been created as these technologies have built capabilities, requiring talent to manage them and freeing up time for knowledge work. This time around, too, the gloom is superseding the optimism on the number and types of opportunities emerging due to new technologies. Where traditional IT roles are facing extinction, new roles like data scientists, mobile app developers, compliance officers, social media architects, cloud integration specialists and many more are emerging.

However, these opportunities will only make themselves truly available to those who take charge to upskill themselves for the careers of tomorrow. It is unrealistic to expect the knowledge we derive on educational campuses to remain consistent and relevant for years after and on the job. One must continue to unlearn and relearn as they go along to tap into new and upcoming industry trends. Employers say that 65% of the IT workforce is not even re-trainable! No wonder the fear factor on job losses is so high.

As mentioned earlier, there are many new roles that are being carved out due to the rise of artificial intelligence and machine learning. Some of the structural changes taking place within businesses and organisations in the future could also relate to the usage of chatbots to facilitate communication between staff and management as well as between IT teams/firms and the client; and the learning based on the type of issue. Roles of CIOs will be augmented by the appointment of chief artificial intelligence officers, and data analysts will increasingly manage artificial intelligence, which, in turn, will drive innovation and evolution for software developers because of an increased focus towards data science. Other support functions such as HR, recruitment, administration and finance will also be revolutionised.

Some of these new-age buzzwords for a professional can be confusing. But that is not the intent-what's needed is an embracing of these new skill areas. Artificial intelligence and machine learning etc are nothing but interdisciplinary areas that combine management, statistics and computer science, augmenting and improving upon what one can do with data-enhancing efficiencies and predictive elements.
In the face of a faster, more agile working world, it is necessary for working professionals to upskill themselves in order to avoid redundancy-machine learning and artificial intelligence are not just making us smarter at chess or replacing real-life assistants, but are redefining whole industries and functions. Those who don't embrace and ride the wave, run the risk of being left behind.

Mayank Kumar is co-founder and CEO, UpGrad, the provider of online education programmes. Apoorva Shankar is head of UpGrad Online Scholarship and head of Content Marketing at UpGrad

Source: Financial Express
Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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