What will future jobs in Artificial Intelligence be like?
A recent Gartner report noted that, by 2020, AI will generate 2.3 million jobs, exceeding the 1.8 million it is expected to replace.
The rapid pace of developments in AI has already begun to disrupt entire industries. While technology is helping replace antiquated systems with agile, innovative tools, it is also set to impact jobs and millions of people. While popular opinion from technophobes suggests machines will entirely take over our jobs, the truth about the future of jobs is a bit complex.
What will future jobs be like?
Technological advancements have had a direct impact on jobs, creating new ones and eliminating the redundant. Today, technology and digitisation have made the lives of consumers simpler, while enabling businesses to leverage advanced tools like AI and Machine Learning to build better products and services. A recent Gartner report noted that the next couple of years will be a defining period as AI will be a major job-creator.
The report stated that, by 2020, AI will generate 2.3 million jobs, exceeding the 1.8 million it is expected to replace. It also revealed that the number of new jobs created by AI and AI-powered tools will reach 2 million by 2025.
A large number of sectors and enterprises that have integrated AI are using the technology primarily for Big Data Analytics through Machine Learning tools. In the digital age, gigabytes of data are created each second by millions of consumers. In order to reach out to customers in a more efficient way, data-driven personalisation is a key element of effective customer service.
Hence, businesses are going to great lengths to ensure they are equipped to use this deluge of data to their advantage—for delivering a higher quality of services and products to customers, and staying ahead of competitors.
Thus, AI has come to play a critical role in key processes like sales and marketing. From powering recommendation engines of Google, Netflix, Amazon that push personalised content towards consumers, to performing complex functions like data and cybersecurity, financial trading and fraud detection, AI can perform a range of functions.
But the application of AI and Machine Learning is largely limited to functions like collecting and processing data, and hence a skilled human workforce is essential for creative tasks and roles that demand human skills, and qualities like emotional intelligence. As of now, less than 5% of occupations are entirely automated, and about 60% comprise 30% tasks that can be automated.
It’s more likely, then, that humans will continue to guide machines, and dominate jobs that require essential skills such as interpersonal relations, emotional range and complexity, dexterity, and mobility, as opposed to the idea that machines will make us redundant.
Upskilling for new-age jobs
Constant learning and skill-building will play a critical role in preparing global workforce to deal with the impact of technology on jobs. Investing in human capital is important for companies to develop skills in employees who are required to work with modern technologies.
The current workforce, both employed and unemployed, should have access to reskilling and upskilling opportunities, and businesses must identify the skills that employees must have, and provide them with the right training. According to a survey by Capgemini of 1,000 organisations, 71% companies have pro-actively initiated reskilling programmes for employees to provide them with skills that equip them to work with AI and automation.
The current and future workforce must have better access to lifelong learning opportunities, which is critical to adapting to an ever-evolving technological and business ecosystem. Simultaneously, we need to fundamentally revise our school and higher education curricula and teaching systems to emphasise more on practical skills and knowledge.
These measures will be crucial to enable both the workforce of today and tomorrow to realise its full potential, and taking the country to the next stage of economic growth.