How You Can Scale with AI

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We use AI in our daily lives in various ways. Major corporations that we interact with everyday have managed to incorporate the use of AI into websites and apps in ways that seem miraculous at first. For example, have you ever browsed your favorite website and then later went on social media to see an advertisement of the exact items you clicked as you browsed? It’s almost as if the items were calling your name and a signal was being sent from some unknown source hinting that you should go back and purchase the items. Companies have learned to be creative. 

 

Here’s another one. Have you ever gotten book recommendations in your inbox or song recommendations after listening to a particular artist? These are examples of how artificial intelligence is used everyday. In education, one way AI is currently being used is a source of student support and guidance. Through apps, students can receive recommendations on which courses to schedule, which majors may be best, and even what career paths the student may want to consider based on the students grades, previous student profiles, and other factors. Computer scientists consider a significant amount of data when designing such applications. While there are circumstances where the recommendations may be inaccurate, these applications are highly efficient.

 

While these are just a few of the ways in which AI has eased its way into everyday existence, one of the best benefits is its scalability. While machines are not teaching full classes, yet anyway, there is no doubt that AI systems are capable of completing more tasks, reaching more individuals, and getting more jobs done than a human could ever do in the same timeframe. This allows organizations to reach new heights, grow in ways unimaginable, and ramp up the quality of the customer or student experience.

 

AI can be used to promote successful experiences, streamline business processes, and even help with managing resources. Still, it does have its challenges. Remember the massive amount of data used to design these systems? Well, the fact is the system can only be as good as the data provided. If any of the data is outdated or incorrect, the results of the use of such data will be affected. Additionally, the quality of the data must be a huge consideration. A good question to ask is whether or not the data represent the large majority of the users, students, or customers. If not, then neither the data or the system will be as useful as intended. 

 

Investing in tools that help exceed your goals can be game changing. When weighing the pros and cons, two things are clear. One, based on substantial evidence that proves there are many benefits and uses, AI is certainly here to stay. And two, when organizations consider the cost-effective ways to use AI, such as custom applications, and the ways these applications or systems can improve the quality of processes and experiences, it seems quite obvious that artificial intelligence is definitely a useful tool.