Creating an App with Artificial Intelligence

Until recently, AI has not been such a hot topic. Now, it is no longer science fiction but a reality that we face every day.

People are unknowingly getting used to the presence of artificial intelligence in their lives. They use internet search engines and online translators, communicate with chatbots on websites, ask virtual voice assistants questions, play computer games or follow the route specified by the GPS without realizing that they are actually interacting with intelligent machines.

Meanwhile, AI technologies have a great impact on all kinds of businesses — from transportation and healthcare to customer service. The largest global corporations such as Google and Microsoft invest heavily in “smart” technologies. Smaller enterprises also have a strong interest in developing solutions powered by artificial intelligence. Implementation of AI techniques has obvious benefits due to the much higher level of performance in comparison to human specialists. Previously, all “smart” technologies were completely controlled by people, but now developers intend to create systems that learn and make decisions by themselves.

Gartner predicts that AI technologies will be implemented in almost every newly produced software and device by 2020. Many researchers suggest that artificial intelligence will have the greatest influence on the development of software and applications. Not only will the way they are built change, but also their essence.

This article will discuss how to develop an app with artificial intelligence.

AI in App Development

These days, users definitely prefer mobile applications to desktop ones. We can see the rapid emergence of apps developed with AI or machine learning in different industries. The most well-known examples of mobile apps with artificial intelligence are Siri by Apple, Google Assistant, Cortana by Microsoft, and Alexa by Amazon.

Using artificial intelligence in mobile applications is a common trend among enterprises. When applications use fixed algorithms, they can’t adjust to the ever-changing user behavior, which means that they lag behind the market needs and don’t invest in business growth. On the contrary, if apps integrate smart technologies, they are able to provide more efficient and personalized services, change the customer experience for the better and retain more clients.

AI can empower a company by providing new possibilities and enormous potential because of the following advantages:

  • Enhanced data processing speed
  • Processing of a bigger volume of data
  • The ability to collect, analyze and interpret user actions in order to improve performance
  • Information security
  • Higher user engagement
  • Maximum revenue generation

One more advantage that AI is expected to perform in the near future is automating QA. It might be possible that an application will be able to test itself, detect bugs and fix them. Moreover, regular updates are supposed to be installed by the app itself without human interference. In this case, the costs will go down significantly.  

These factors indicate that businesses need to invest in artificial intelligence app development.

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Main Use Cases

AI is a large science field with numerous technologies, and one company doesn’t need to implement. A single intelligent technology can be quite enough to build a profitable solution. The choice depends on the goals and requirements.

1. Automated reasoning

Computers apply logical reasoning to solve puzzles. Simply put, they can play chess or prove theorems. In practice, this ability is implemented in taxi apps to optimize routes and get the passengers to their destinations faster.

2. Purchase predictions

The algorithm analyzes purchase history of every user, anticipates what products may be needed and offers them, thus increasing customer engagement. The information can be also used for the sake of other marketing approaches:

  • Sales and discounts
  • Targeting advertisements
  • Future pricing decisions
  • Stocking shops with the goods people are more likely to buy

The technology is a great revenue source for retail businesses.

3. Recommendation services

The app should provide the end user with the most relevant content. That means making recommendations that are of interest to users. Such a service is able to monitor the choices users make, learn from them and offer relevant information in future. The technology is especially useful and profitable for entertainment applications.

4. Learning behavior patterns

Algorithms carefully study customer behavior and detect certain patterns. They are taught not to make mistakes while interacting with customers and perform seamlessly.

These cases of applying artificial intelligence show its importance for business and increased demands at the consumer end. Forward-thinking companies are implementing AI app development without hesitation.

Risks and Challenges

Nevertheless, there are always pros and cons that are attached to any innovation. We’ve discussed the main advantages of intelligent technologies for business. Now, let’s talk about risks and challenges that companies may face.

  • Inflated expectations. AI technologies are utilized in many industries, but they are not perfect yet. For example, voice recognition is at a high level today. But there are still lots of problems with the transcription of dialects and slang. This means that machines still can’t completely replace humans (fortunately), and you should set realistic expectations so as not to be disappointed.
  • Lack of technological capacity. You can use deep learning algorithms for simple scenarios without having a huge computing infrastructure, and that will be okay. But if you want to train multilayer algorithms to perform complex tasks, you will need significant computing power. Take this into account before implementing AI into production.
  • Underestimated initial costs. AI integration is supposed to increase revenues and reduce overall costs, that’s true. But don’t forget that initially, you will have to make quite a huge investment to integrate algorithms with the existing system and to develop and manage the code. So, the early days are likely to require much effort, skill and investment.
  • Control issues. Neural networks are already quite mature today: they can learn from previous experience, come to certain conclusions and give recommendations. The problem is that developers themselves aren’t always sure if their recommendations are right or wrong, and don’t always understand how the networks draw some conclusions. It’s a bit frightening to realize that a machine can be beyond your control and start thinking like a human. So, the issue remains open.
  • Lack of skilled workers. It may be quite a challenge to find enough employees skilled in a specific  AI technique. That’s why a skills gap is a significant obstacle to AI adoption in many enterprises.

How to Build an AI Application, and How Much It Costs

Many companies are willing to utilize machine learning and AI to transform their business.

Here is a project plan that may help you develop an artificial intelligence app.

Stage 1. Analysis

The aim of this stage is to set up project goals. You need to conduct a thorough study, analyze the market and customer needs, assess current metrics and infrastructure and define the timeline and the budget. On the average, it takes 5-7 working days, so the cost will be insignificant.

If you decide that AI concept implementation is possible, proceed to the next stage.

Stage 2. Prototyping

At this stage, an AI-based model of the product should be developed in order to test the concept. Prototyping is necessary as it gives the opportunity to discuss the requirements and reduce risks before the development begins. The cost may start at $5,000 and more, depending on the complexity of a project.

Stage 3. Minimum Viable Product

This stage is devoted to the development of a real viable product. Developers can use one of the popular AI platforms like Wit.ai, Google Cloud Prediction API or Microsoft Azure Machine Learning. Like any standard app platform, they provide useful functionality that helps build the solution from scratch. The difference is that on such platforms, it’s possible to add in machine learning and deep learning libraries to create an intelligent application. The average cost may range from $35,000 to $100,000, depending on the total project size.

Stage 4. Product release

This is the last step. The product with a complete set of features should be developed and launched to market. The cost is usually defined on the basis of a minimal viable product cost.

Summary

The final price of AI app creation should be calculated for each project individually, as many specific factors can affect it (requirements, implemented functions, used technologies, project size and structure, etc.), and numbers may greatly differ in practice.

A couple of years ago, only the largest global corporations could afford to develop software using machine learning or artificial intelligence. Nowadays, AI-driven solutions have become more available for mid-size and small businesses. The price range for AI application can be quite reasonable, for instance, $100,000 – $300,000.

AI adoption is the driving force behind the growth and efficient operation of many enterprises. Most companies are ready for the transformation, but they still have to cope with some significant challenges.

What We Offer

SaM Solutions supports common trends and utilizes AI techniques in various projects. Our expertise includes implementation of the intelligent system management and creation of cognitive computing software with intelligent elements.

One great example of AI implementation is the mobile application ViaOpta Hello for Microsoft, which was developed with the help of MS Cognitive Services and voice and image recognition technologies. For this application, Face API Service was built.

Also, our team took part in the creation of some services on the basis of Microsoft Azure:

  • Bing Speech API: speech recognition and transcription into text.
  • Language Understanding Intelligent Service (LUIS): command recognition; can be applied in smart homes.
  • Computer Vision API: allows cataloging images on the basis of tags.
  • Video indexer: allows searching images/events in a video on the basis of tags.

Don’t hesitate to contact us for more information.

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About the author

Natallia Sakovich
Natallia Sakovich

A copywriter at SaM Solutions, Natallia is devoted to her motto — to write simply and clearly about complicated things. Backed up with a 5-year experience in copywriting, she creates informative but exciting articles on high technologies.

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