Today, in practically every industry, from customer service and travel, through to malware removal and personal finance, artificial intelligence, or AI, seems to be destined to have a profound impact on all areas of business.
Not only does AI promise to eliminate issues such as a human error, but it can also reduce a wide variety of tedious, time-consuming tasks, providing us with more time for creativity, as well as a practically endless supply of virtual assistance.
In recent years, AI technology has already reached some rather impressive milestone, as can be seen with products such as Amazon’s Alexa, Apple’s Siri, and Google Assistant. Still, it’s estimated that it could still take up to three to five more years before the AI technology’s full impact will be felt in all areas of industry.
Companies and organisations that have already harnessed AI are making huge strides in improving their operational efficiencies, as well as being able to make faster, well-informed decisions, and innovating new products and services that have the potential to change the course of human society.
On the other hand, there are many challenges still in place for organisations that haven’t yet begun using AI. And, those that lack a clear and viable AI strategy are struggling to make any progress in their respective industries.
What is Artificial Intelligence?
It might be surprising to learn that most current AI and machine learning models are based on cognitive and neural sciences.
The principle is that we, as humans, should not have to program machines to tell them what to do at each step throughout a given process. Instead, we should be teaching machines and computers how to learn and solve problems all by themselves.
This is all made possible through machine learning and its capability to process massive amounts of data, as well as our ability to increase their computing powers as the need increases. That being said, experts believe that instead of thinking about AI in terms of algorithms, we need to think about it regarding cognitive science and neural networking.
For example, neuromorphic computing is one of the leading AI architectures used today because it closely resembles the natural structure of a human neural network.
Additionally, neuromorphic hardware requires very little power consumption compared to most other types of AI technologies and can easily be scaled to meet the demands of a continuously increasing workload. Therefore, neuromorphic computing is expected to gain momentum as the market for AI continues to grow in all areas of business.
Artificial Intelligence and Business
As we’ve already mentioned, AI systems can be used to increase an organisation’s efficiency by improving almost all areas of their operations. This is likely to provide new and emerging market opportunities, as well as a clear competitive advantage for organisations who implement the technology.
Today, countless organisations around the world are already beginning to invest in proof of concept research to determine how they can benefit from using AI technology.
In terms of jobs, most AI experts believe that in as little as 15 to 20 years, a significant portion of human jobs will be automated by artificial intelligence systems. Some even say that this could be as high as 47%, which includes everything from labour and farm jobs, to doctors, lawyers, and judges.
Therefore, one of the main issues surrounding AI isn’t the technology itself, but rather, the need to prepare for the elimination of thousands of jobs around the world that is sure to arise as AI and machine learning continue to be developed and improved.
This leaves many worried about the ever-increasing gap between technological advancement and our society’s ability to deal with its consequences. It emphasises the need for industry leaders and stakeholders to think ahead and ensure that new AI technologies are used to build a better world, rather than increasing disparity and job insecurity.
The Future of AI and Its Challenges
Rather than thinking about AI technologies individually, it’s best to think of it as a fusion of countless advanced technologies with a problem-solving approach, that will likely have a massive impact on all areas of business and society as a whole.
Still, many challenges lie ahead for the future of artificial intelligence. For example, many intelligent machines and computers are far too complex to be built using conventional methods. Therefore, AI technologies call for new and emerging manufacturing techniques such as 3D printing and other types of laser technology.
Future AI technologies also require new sets of skills, which have not previously existed, in order to develop solutions to the problems that today’s technology is still incapable of solving. Therefore, companies and organisations, even those in the tech sector, should not underestimate the challenges that are yet to come surrounding AI and machine learning.
It’s also important to understand that AI is still evolving and we, as a society, need to pursue only meaningful and useful AI technologies, as well as fully considering the impact that they will have once they are developed and implemented.
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