How to create an AI Application

Cost to Build an App that Uses AI

We live in the era of “Software 2.0,” when artificial intelligence (AI) technologies are widely used in desktop and mobile application development. According to a Gartner report, 85 percent of customer interactions in 2020 are non-human.

If you are interested in innovations, read about the capabilities of such systems, AI app development, and its cost in this article.

How AI Gains a Foothold in the Mobile App Market?

Apps that use AI have long been the object of scrutiny from startups and company owners. The market value of AI is estimated to have exceeded US$17 billion at the end of 2020 (globally) and will be around US$90 billion by 2025. The number of companies adopting artificial intelligence solutions is growing at 37 percent a year.

Among all areas of AI, machine learning (ML) and deep learning are of particular interest. The Relevancy Group found that 38 percent of top executives chose ML to build data management platforms. Intelligent solutions are actively developing in B2C business, manufacturing, healthcare, e-learning, fintech, and many other industries. The reason for it is the benefits of implementing AI.

Using the technology in your business, you can:

  • Improve consumer analytics and customer behavior’s prediction, reduce the research cost and make it deep and comprehensive;
  • Reach the higher security and data loss prevention;
  • Improve overall performance and analyze vast amounts faster and with lower costs of computing resources;
  • Get a better user experience, optimize customer searches, and increase customer loyalty;
  • Integrate your app with IoT to expand the product scope, and therefore its customer base; and
  • Reduce personnel and training costs and minimize human factor risks.

The Variety of Technical Stack for AI Application Development

Typically, programming languages such as Python, Java, and C ++ are used to make AI-based apps. In some cases, program engineers use other languages, for example, C#, R, Lisp, or Prolog, depending on the solution.

To reduce costs, you can use third-party AI and ML platforms and access them as a service (AIaaS). Among the commonly used platforms are Google TensorFlow, Microsoft Azure, and Amazon AML. But developers can choose another solution, depending on the app features and technical tools selected. It could be IBM Watson, Oracle AI cloud services, H2O, Api.ai, etc.

AI, ML, and deep learning frameworks greatly simplify the development of high-tech products and allow you to use third parties through integration with the app. The most popular options include:

  • Microsoft Cognitive Toolkit (CNTK);
  • Amazon Machine Learning (AML);
  • Apple’s Core ML/Create ML;
  • PyTorch, Caffe2, Keras, Scikit-learn, etc.

Third-party APIs and software development kits (SDKs) also help to simplify and speed up the development. Here are some examples from our practice:

  • Azure Topic Detection API excellently recognizes unstructured text using NLP and gives a deeper understanding of customer opinions through sentiment analysis;
  • Microsoft Face API and Google Vision API help you easily integrate facial recognition for a convenient and reliable user experience; and
  • Apple’s SiriKit that processes voice requests into app actions and displays branding and custom content in Siri or Maps.

How to Create AI-based App: Key Steps and Cost

The basic development pipeline can be represented as:

  • Discovery, requirements’ definition, and planning;
  • Data mining and modeling;
  • Minimum viable product (MVP) and final app’s development; and
  • Testing and delivery.

First, you need to identify the idea and problem, create a clear list of product requirements, document them, and determine the composition of the team of technical and non-technical specialists. Then development team has to:

  • Collect the data and prepare it to receive an accurate model,
  • Create and train ML model;
  • Test, evaluate, deploy the model and load it into the app;
  • Build an MVP and full-fledged app: think over the architecture, create the user interface, frontend and backend;
  • Test the finished app with QA engineering tools.

When the application is thoroughly tested, you can deliver it and place it in app stores.

In general, when developing AI software, you will spend at least US$10,000, but the actual numbers vary between US$30,000 and US$100,000 depending on its size and complexity. Keep in mind that you will also have to spend about 30 percent of this amount to support the app in the first year, and each next year this figure will remain at 15–25 percent of the total development cost.

Conclusion

If you are ready to start your own AI app, be prepared for a journey full of surprises and challenges. But don’t give up on difficulties: all you need is to arm yourself with the knowledge and help of an experienced developer and forward to success.

Read more about how to develop an AI app in the full article on our blog!

We solve real-life challenges with innovative, tech-savvy solutions. https://chisw.com/