Introduction

Whether you are new to the world of AI or have been in this area far longer that it became a buzzword, chances are you have asked yourself the following question.

How do I know if Artificial Intelligence integration is right for my company and will not negatively affect my current workflow? What are some applications of AI that I can integrate into my workflow to improve overall efficiency?

In this article we will uncover common applications of AI in the software development industry to have a better outlook on ways it can be transformative for your business!

Applications- Common Artificial Intelligence Use-Cases

Speech Recognition

Speech Recognition helps turn human communication and speech into text. Speech-to-text platforms such as Speechmatics or Google’s speech-to-text engine allow their users to seamlessly access spoken content in a written form.

One of the many benefits of speech recognition systems is the improved productivity of humans, since we are no longer obliged to waste time on taking notes during online interactions, meetings or other virtual events. While going through daily or weekly meetings we retain too much information. So instead of recording each meeting, try using speech recognition systems to have reliable notes to review whenever you want to quickly rewind your discussions.

Virtual assistants

As you may have noticed, nowadays most basic computer-based interactions are initially carried out by virtual persons. Most computer programs such as AI-based chatbots are more than capable of completing administrative tasks: interacting with humans, answering basic support queries, coming up with recommendations, etc.

Amazon’s Alexa, Apple’s Siri, Google Assistant or a lot of virtual or mobile chatbots are quick and effective when you need immediate answers to your questions that could take humans much longer to research and answer. It’s quick, easy and actually quite affordable. What more could we ask for?

If you're looking for a similar solution, visit our AI, Algorithm Research and development section.

Text Analytics

Text analytics helps to extract meaning from a text. It also helps to uncover trends and patterns. One of the most common uses of text analytics forms is SEO which helps to analyze the positioning of the web page based on content, tags, descriptions, etc.

If you need information on word frequency, entity recognition (identifying names, locations, time period), tags then text analytics will be the “hero to save the day”. This can help your company better understand what your clients are looking for and how to have a competitive advantage to always remain on top.

Sentiment Analysis

Sentiment analysis or “opinion mining” helps to identify emotions or tones behind texts. Let’s try to think of a tone for this article. Is it negative, positive or neutral? Nowadays, most companies hire professional developers to make sense of critical information for their business with sentiment analysis.

“What does my customer think about my latest released product?” or “Are tourists satisfied with the newly-opened attraction park?”. Questions like these may contain hundreds, in some cases thousands of reviews.

Now let’s try to imagine us-humans going over, reading and trying to make sense of this data manually. It will take forever and our conclusions may turn out to be incorrect. Sentiment Analysis helps to analyze enormous chunks of data to help companies improve customer service and satisfaction.

AI-based recommendation systems

Recommendation systems use Big Data (referring to extremely large datasets) to recommend additional services (such as products) for your customers based on their online behavior.

Preferences, choices and characteristics of people all play a huge part in shaping an audience that may be interested in your product or services. Such data is crucial if companies want to make targeted recommendations to their consumers which is usually done based on information such as the user’s gender, age, geographic location, social or personal views, etc.

For more information on industry-specific cases, check SCD Company’s Case Studies on building successful hotel recommendation systems.

RPA (Robotic Process Automation)

Have you ever come across people complaining about bots flooding comment sections or displaying social media human-like presence on various platforms? Well, RPA is often misunderstood.

RPA performs to automate digital processes and certainly does not stand for the physical form of robots. Instead, it is an effective business system automation process which instructs the “robot” to mimic human activities. It’s most usually used to streamline processes such as performing time-consuming and mundane tasks that would take humans hours or days to perform.

Thanks to RPA, companies face increased productivity and less effort spent on trivial activities. In short, if you would like to improve the efficiency of your staff and help them focus on much more important tasks, leave the rest to RPA.

Marketing Automation

Every company wants to increase their ROI and the fastest way to achieve that is to automate repetitive marketing processes. Sending messages, updates, newsletters, campaigns manually would take hours for marketing departments, moreover lead management via CRM systems would become too overwhelming without automation.

According to Finances Online, marketers use automation 76% more than sales teams. Marketing processes can be easily streamlined through automation tools to better target audiences, nurture existing leads via various platforms and build closer relationships with customers. If you have not yet, we suggest looking into investing in that area!

Image Recognition

It’s easy for us-humans to detect, identify and classify objects we see in our everyday lives. But for machines, it’s a highly challenging task. Image Recognition (also known as Object Detection) helps to identify objects in images or videos and recognize which category or class the image belongs to.

Nowadays complex deep-learning algorithms and AI models allow us to analyze even less discernible objects. This is achieved through training neural networks (an AI method that teaches computers to process data similarly to the human brain).

Start by collecting vast amounts of visual data and teaching the system how to annotate the image. How do machines learn to recognize the objects over time? Through showing different and many examples of the same image and training the algorithm to recognize many types, forms, angles, shapes or sizes of the same object.

In the end, based on your data input, it will eventually learn to make accurate predictions itself with high accuracy. Healthcare, AgTech, Sports Analytics, E-commerce, the benefits of image recognition over the years have helped these industries completely transform their business processes.

Conclusion

Artificial Intelligence has taken over the world and instead of diverting from it, we should embrace the positive changes it has to offer. After all, it’s the era of digital transformation and learning how to effectively integrate AI into the workflow can bring forth more pros than cons. As more and more companies are reaping the fruits of AI-based systems, we think it’s time for us to take that transformative road to remain competitive in today’s demanding market.

Will these applications be right for your business area? Should you consider investing in AI systems? What are some areas that AI can help reduce costs for your business? Contact SCD for custom recommendations.