Artificial intelligence is using Automation of making Several human jobs obsolete.

At present, global AI adoption and investment are soaring. Reportedly, 37 percent of organizations have deployed AI solutions. Analysts have forecasted that global AI spending will more than double over the next three years, topping US$79 billion by 2022.

Almost two-thirds of global reports state that AI technologies are enabling their organizations to move ahead of the competition. Sixty-three percent of the leaders surveyed already view AI as "very" or "critically" important to their business success, and that number is expected to grow to 81 percent within two years.

Nature of Work

However, analysts are somewhat uncertain about how much effect AI would have on human jobs. On one hand, AI-driven automation has made most jobs obsolete and on the other hand, new designations of jobs and new territories are being discovered concerning AI operations. While AI adopters express concern about automation as an ethical risk, they emphatically believe that human workers and AI will augment each other, changing the nature of work for the better. Changing how work gets done within the organization by making operations more efficient, supporting better decision-making, and freeing up workers from repetitive tasks- is the core to what companies want to achieve with AI.

Managing the Gap of Skills

To meet their AI aspirations, companies will likely need the right mix of talent to translate business needs into solution requirements, build and deploy AI systems. They would require to integrate AI into processes and interpret results. However, most early adopters face an AI skills gap and are looking for expertise to boost their capabilities. Reportedly, 68 percent of executives confess to a moderate-to-extreme skills gap, and more than a quarter rate their skills gap as "major" or "extreme." The gap is evident across all countries surveyed, ranging from 51 percent reporting moderate-to-extreme gaps in China to 73 percent reporting the same in the United Kingdom. The new designations of this field are AI builders and AI translators. These AI builders refer to researchers to invent new kinds of AI algorithms and systems, software developers to architect and code AI systems, data scientists to analyze and extract meaningful insights from data, and project managers to ensure that AI projects are executed according to plan. AI translators bridge the divide between the business and technical staff—the front and back ends of building AI solutions.

Replacement or Advancement?

The desire to replace workers with new, AI-ready talent is clear, but it is not the end of human jobs at all. Reports reveal a scarcity of AI talent around the world. Canadian firm Element AI recently analysed LinkedIn profiles to gauge the size of the worldwide top-tier AI talent pool and counted 36,524 self-reported PhD-level AI experts (including data scientists and machine learning researchers and engineers). So, it is very clear that when a door is being closed in the job sector, a new, more advanced section of jobs are opening doors on the other side.