Artificial intelligence is all the rage right now, and it’s becoming more and more accessible to businesses of all sizes. While some companies have hopped on board with AI implementation, others are still pacing in the gray area. Of course, it’s natural to be cautious of the unknown, but businesses shouldn’t let their skepticism of AI stop them from examining its potential.
Experimentation is a great way for leaders to face their reservations about AI while evaluating its capabilities and limitations. In fact, it is swiftly becoming apparent that businesses that aren’t actively considering how to leverage AI in their processes are doing themselves a disservice.
It can be difficult to grasp how exactly businesses can leverage artificial intelligence, especially with our impressions of AI shaped by pop culture references like Johnny 5, R2-D2, and HAL 9000. The difference is that, unlike AI, as it often appears in pop culture, the AI we’re referring to hasn’t (yet) become sentient, autonomous, or antagonistic.
Instead, as it exists today, AI is more accurately described as the capability for computers to “learn” by collecting and storing data and to “think” by accessing that data and processing it to solve problems. This makes it more similar to The Brain, the supercomputer from Isaac Asimov’s short story Escape!, albeit not nearly as advanced. Rather than working on a hyperspace drive, as The Brain was tasked with, today’s AI can be used to predict activities based on past actions. The larger the database the AI has to access, the better the inferences that can be developed.
This phenomenon is known as machine learning, where technology improves its predictions as it accumulates more data. A basic example of machine learning can be found on Amazon and similar websites, where your purchase history is compiled with those of other users who match your demographics. This data allows these sites to recommend products you may be interested in and to direct their advertisements more effectively. As more layers of data are collected, machine learning is upgraded to deep learning, where the additional data makes predictions more accurate and refined.
There is so much to cover about AI in the IT space, so let’s look into familiar AI and AI for SMBs and how they differ.
FAMILIAR AI
Millions of people utilize artificial intelligence every day without even realizing it. Virtual personal assistants, such as Amazon’s Alexa and Apple’s Siri, are prime examples. These assistants use machine learning to improve with every question they answer, each update bringing better inferences and conclusions. Even Netflix leverages machine learning to deliver recommendations to its users based on their viewing history.
AI IN THE SMB
There are a variety of perceived benefits that AI can bring to small and medium-sized businesses, whether it’s streamlining general operations, improving a customer’s experience, or simply remaining competitive in an evolving industry. Whether it’s working to improve the experience of a client or automating time-consuming processes internally, artificial intelligence can give your business a heavy advantage.
However, before AI can be leveraged, you need to be sure that you have the technology infrastructure to support it.
SOFTWARE AND APPLICATIONS
There is a good chance you’re already leveraging AI through your line of business applications. This means that even if you aren’t planning to vet and implement AI for time or budgetary constraints, you may already be reaping the significant benefits that artificial intelligence has to offer.
While Marvin the Paranoid Android may not be your employee anytime soon, businesses will continue to utilize AI as a part of their business intelligence and operations, and small businesses have increasing opportunities to leverage AI to their—and their clients— benefit.
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