By 2030, 70% of the global organizations would have incorporated AI in some form. Among other effects, this also means an intensified war for talent. 375 million (1 in 3 workers) will be pressured to learn new skills.
A new relationship between humans and machines is on the horizon and so is a great economic overhaul. AI has the potential to widen the gap between developing and developed countries, companies and people. With every passing day this gap seems to widen even more. Leading countries can gain a 20-25% increase in economic outputs while developing countries can get at the most a 15% advantage. Non-adopters can lose 20% of their cash flows. To top it all off, singularity threatens to eliminate all human involvement in AI affairs.
But not all is gloom and doom. AI can also be seen as a harbinger of positive economic changes. Here’s what it is expected to bring:
As much as we want to believe that this development has hit us as a surprise, the reality lies in the fact that the foundation for it was laid 200 years ago. In the period between then and now we have come to peace with the fact that sustainable development lies in the automation of industrial processes; from the steam engine, electricity, and transistors to semiconductors and personal computers, automation has brought the world where it stands today. That being said, recent developments in AI are confronting us with a different kind of question — will unemployment be the cost of this progress?
The metamorphosis is so sudden and so fast that even the most assured Gurus are baffled by it. They seem to be shirking away from their obscure prevision with a meek “we don’t know yet.” But here are some things that we do know:
Repetitive jobs are at the most risk of being replaced or reduced in worth. The extent may range from 20-33% while jobs involving non-repetitive tasks and high digital skills will gain 13% of the total wages. Skills that bridge the gap between different disciplines and the ones that enable the translation of digital insights into real-world applications will be in high demand.
While integration of AI in repetitive tasks is familiar now, the real potential of this technology lies in its application in non-repetitive and cognitive jobs like:
Current developments in AI are pivoting around tried and tested models of computer vision, robotic process automation, natural language, advanced machine learning and virtual assistants. In some of the most prominent use cases, AI is improving performance over other analytic methods.
Retail companies are using AI for:
Audi and BMW are using virtual reality to give a feel of their vehicles to customers sitting in their homes. In another use case, people will be able to use autonomous fleets that will give them access to the vehicle they might need at any particular time.
Self-learning monitoring systems are making manufacturing processes more predictable and manageable. These controlled systems are helping companies reduce costs, delays, defects and aberrations.
Siemens is using AI to:
AI is helping Data based diagnostic support. Initially, AI will assist human physicians in their diagnosis and later it will move on to operate autonomously.
Robo-advice is giving people customized investment solutions.
24X7 runtime is possible with the use of autonomous trucking.
Many startups are coming up with personalized content services. AI is expected to help in classification and archiving of these huge content repositories.
Smart meters are enabling customers to track their energy consumption and tailor it to their needs.
While many new use cases of AI are springing up every day, the technology is still in its nascent stages. Only time will tell how it is going to shape our future. But shape it will— for better or for worse, we are yet to see.