While artificial intelligence was once only a theory seen in sci-fi novels and on the big screen, today AI technology is rapidly expanding with numerous real-world applications. What once was known as simple rule-based automation, AI software has now reached a point where it can mimic human interactions and even ‘think’ on its own in certain cases.

As AI software continues to evolve and progress, developers are continuing to find new ways to integrate AI into just about anything. In fact, according to 2016 Gartner research at least 30% of companies globally will use AI in some capacity by 2020.

However, unless you understand the applications of this software, it can be difficult to understand how AI can benefit your organization. In this article, we are going to review 6 ways to use AI software for a more efficient world.

Building blocks of AI software

The first step toward understanding the applications of AI software is to understand how AI technology is created and what building blocks are part of the development process. While AI is obviously a very complex technology with a lot of moving parts, most commercial AI software will be built upon three things: machine vision, natural language processing, and machine learning.

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Machine vision

By definition, machine vision refers to the ability of an AI program to understand visual input such as videos and images. Through the use of training data, the AI software can then identify and classify the visual input into useful data that can then be used for further processing. A common use of machine vision can be found in the iPhone X’s facial recognition software or Instagram’s filter library.   

Natural language processing

While machine vision processes visual inputs, Natural Language Processing (NLP) does the same thing for human voice and text inputs. NLP has come a long way from the early days of AI software and can now be found in the form of chatbots and voice assistants like Siri and Google Home. Not only is NLP vital to sustain AI, but as it continues to advance in capabilities, more use cases and applications will spring up along with it.

Machine learning

The third building block of AI software is machine learning, sometimes referred to as ‘deep learning.’ While machine vision and NLP help to process data fed into an AI software, machine learning takes that data and ‘learns’ to improve itself by finding the most efficient process. While the advances we have made with NLP and machine vision are exciting, most of the breakthroughs you will see in the future of AI will come from machine learning.

Applications of AI software

With a little bit more information on what goes into an AI software, let’s now take a look at a few real-world applications of this software and what they mean for the future of AI development. While many of these applications are still in the rudimentary, it’s clear the massive potential they have for disruption on a large scale.

1. Software testing and development

In the world of software development, it always seems like there is never enough time to get everything done within a project schedule. This is why Agile development has taken off as a way to cut down on time spent on development projects. However, imagine the possibilities if you could use AI software to speed up both the testing and development of software projects.

Some of these tools, such as Applitools, SauceLabs, Test.AI, ReTest, are already working to make this a reality. By using an AI, developers can focus on the core code of their software projects and leave menial tasks like rounding out the code and testing to a program. Once this takes off, the time it takes to develop a software product will likely drop drastically.

2. Fraud prevention

Another area where AI software has huge potential can be found in the banking industry, more specifically in fraud prevention. Imagine an AI system that matches a photo of the user with their financial history in order to avoid identity theft. Not only would this system uncover fraud faster, but it could be programmed to alert the proper authorities and automatically freeze accounts if necessary,

Taking this even a step further, a fraud prevention AI could pick up on anomalies and abnormal behavior to prevent cyber-attacks. While there aren’t any programs available for this type of service yet, the building blocks are there to make this a reality.

3. Customer service

If you’ve visited a customer-facing website recently, there’s no doubt you have seen a chatbot that either welcomes you to the site or asks if you need assistance. These chatbots are AI software that can be used for customer service with surprisingly impressive results. (LINK)

Again, chatbots are still a work in progress, with most of them failing to understand basic prompts. However, with recent advances in machine learning, it won’t be long before these bots have adapted to these changes and improved upon themselves. From there, who knows what they might be capable of?

4. Self-driving cars

Like artificial intelligence, another emerging technology that is gaining a lot of attention in the press is self-driving cars. For decades, auto makers and drivers alike have been anticipating the coming of these autonomous vehicles and what they will mean for society, both good and bad. What you may not know is that the technology that helps self-driving cars work is built upon AI software.

When you are driving, whether you realize it or not, you are making countless decisions at almost every turn. In order for self-driving cars to process these decisions, AI software is necessary to take on the heavy lifting. As self-driving car technology advances, artificial intelligence will play a major role in its development.

5. Logistics and supply chain

Ever since Amazon rolled out their two-day shipping standard, supply chain and logistics companies have been working their hardest to keep up with increase demand on a smaller timeline. Customers are no longer satisfied with long wait times, leading some to believe that soon ‘business days’ will become a thing of the past.

However, with recent advances and integrations with IoT solutions, a solution may be on the horizon in AI software. By fully automating the entire process of the supply chain, organizations will be able to maximize their efficiency, save money, and free up employees for more pertinent tasks like customer service and experience.

6. Healthcare

The final application of AI software we will review is artificial intelligence in the healthcare sector. Now, for years, custom healthcare software has been popular for hospitals and medical centers trying to increase the efficiency and quality of their care. Now, with AI technology, health providers can take this a step further revolutionize their offering and greater industry.

For instance, an AI software designed to diagnose disease could search through millions of data points and provide an opinion in seconds. By handing off this menial task to an AI system, doctors and medical staff can focus on patient care. While this is just the beginning, there is enormous potential in this industry for improving processes with AI.

Final thoughts

As you can see, AI software has come a long way since it first began and yet, has potential to go even further with the right direction. Our advice is to get involved now. Organizations can reduce their costs, improve efficiency across the board, and unveil new human roles by using AI software.

In our world of rapid technological development, finding a system or software that can meet each of these requirements is hard to come by, so get involved now. While robots may not be taking your job yet, they might soon. Better to get ahead of the curve now and build the future, instead of merely letting it happen.