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How to Build AI-Powered Apps in 2024: A Step-By-Step Guide

How to Build AI-Powered Apps

Whether you are an established business or a startup owner, you must integrate AI into your operations. That’s because from chatbots to virtual assistants, AI-powered applications are dominating the digital landscape.

Asia Pacific AI Market

A report published by revealed that last year, the global AI market size was valued at $136.55 billion. This figure is expected to grow at a CAGR of 37.7% by 2030.

If you don’t want to miss out on amazing growth opportunities, you should integrate AI into your mobile apps. Read this article to gain a thorough understanding of how to build an AI app.

[Also Read - The Role of AI and AR in Modern Salon Booking Apps]

In this article, we will cover:

  • Top industries that benefit from AI mobile app development
  • Steps to build an AI app
  • List of top artificial intelligence apps
  • How much does it cost to develop an AI app
  • How long does it take to build an AI app

Let’s dive into business and technical details.

Top Industries That Benefit From AI Mobile App Development

AI-powered mobile apps are popularly used by the top 5 industries, including healthcare, finance, retail, manufacturing, and education.

Industries That Benefit From AI Mobile App Development

1. Healthcare

The healthcare sector uses AI-powered applications to reduce costs, enhance the quality of care, and improve patient outcomes.

AI-integrated diagnostic tools are used to detect abnormalities and analyze medical images. It also assists clinicians in making accurate diagnoses and provides patients with 24/7 assistance to help them manage their condition.

[Also Read - Artificial Intelligence in the Healthcare Industry: A Statistical Analysis]

2. Finance

The financial sector uses AI-integrated mobile apps to identify patterns in the data. It also helps automate routine tasks and make predictions.

For instance, AI-integrated chatbots help customers manage finances, make transactions, and provide personalized financial advice. In addition, AI can analyze large volumes of data to detect fraudulent activities.

[Also Read - The Role of Artificial Intelligence in FinTech: Revolutionizing Customer Experience and Risk Management]

3. Retail

Likewise, the retail sector uses AI to offer personalized customer experiences, supply chain efficiency enhancement, and inventory management optimization.

AI-powered inventory management system successfully analyzes sales data to minimize waste, optimize stock levels, and predict demand. Likewise, recommendation engines analyze customer data to recommend products.

[Also Read - AI in E-commerce: 8 Ways It’s Transforming the Business]

4. Manufacturing

Manufacturing is the next industry that uses AI to optimize the overall production process, improve quality, and reduce cost.

For instance, AI-powered algorithms help make predictions, optimize product performance, and control quality to stop faulty products from reaching customers. Similarly, predictive maintenance systems analyze data to detect equipment failure.

5. Education

Lastly, the education field has gained massive benefits from AI integration.

For example, AI-powered adaptive learning platforms analyze data to identify knowledge gaps and provide custom study recommendations. Similarly, chatbots offer 24/7 assistance to students. And AI algorithms analyze data to make relevant predictions.

[Also Read - How AI Is Transforming The Future Of EdTech Industry?]

6 Steps to Build an AI App

How to Build an AI App

Wondering how to create AI app? Follow these six easy steps to get started:

1. Set Your AI App Goals

For successful AI app development, you need to set goals that you wish to achieve with your app. By clearly defining your goals, you can have a smooth development process and can stay purposeful.

To set your goals, you first need to define the problem that your app is likely to solve. Then make sure that your goals are focused on solving the problems.

Once your goals are set, you need to focus on the KPIs that will help you track your app’s success. Ideally, your KPI should follow the SMART framework.

AI-specific KPIs

Common AI-specific KPIs that will help you track and access your AI model’s performance are:

  • Model Accuracy
  • Model Precision
  • Model Recall
  • Model Fairness
  • F1-score

Next, you must set clear development and deployment milestones. This can be easily done if your team uses an agile development methodology like Scrum.

agile development methodology like Scrum

Before you start building your AI app, you need to analyze your resources. The unavailability of sufficient resources can act as a hindrance when training and maintaining AI models.

2. Choose the Right Tools and Frameworks

The next step is choosing the right tools and frameworks to successfully develop and train AI models. Your choice will depend on your specific business needs.

Some of the popular AI frameworks to cut down on development time are:

  • TensorFlow: TensorFlow, an open-source library assists in building and deploying machine learning models. It is used for complex and commercial projects. Airbnb, an industry giant, uses TensorFlow to create an AI image classification model for properly categorizing listing photos. In addition, TensorFlow has an end-to-end platform, which is TensorFlow Extended. You can use it to manage your AI model.
  • PyTorch: Another popular open-source AI library is PyTorch, which is used for flexible and modular design. However, PyTorch does not offer commercial support. It is only inclined towards academic researchers.
  • Google AutoML: If your team does not have sufficient experience with AI models, you can use Google AutoML. It can be used to train custom models with the least effort and expertise.

Besides these three AI frameworks, you can also choose from cloud-based AI platforms like Google Cloud AI, Amazon Sagemaker, and Azure Machine Learning.

3. Collect and Prepare Data

One of the key steps during AI application development is data collection and preparation. Wondering why? Because without having high-quality data, even the best AI models are likely to fail.

So, you must always prioritize data quality over quantity. Also, your data should be properly cleaned and formatted. If not, you will face huge losses.

But first, you need to choose the datasets that you will use to train your AI model. Following this, prepare the data for use by cleaning, preprocessing, and wrangling.

4. Design and Train Your AI Model

The next step is to design and train your AI model. That’s because your AI apps’ success depends on how properly you have designed and trained the model.

For this, you need to decide on your training approach from supervised learning, unsupervised learning, and reinforcement learning. Then you should design your model’s architecture depending on your specific needs. Some of the top architectures are:

  • Convolutional Neural Networks (CNN)
  • Recurrent Neural Networks (RNN)
  • Generative Adversarial Networks (GAN)

You can start training the model on your data by splitting your data into training data, validation data, and test data. A good ratio is 70% for training, 15% for validation, and 15% for testing.

Following this, you need to feed your AI model with the data so it can recognize and learn from it. Once done, review the model’s accuracy and reliability.

5. Integrate the AI Model into Your App

One of the most critical phases of the AI app development process is integrating the AI model into your app. Failure in integration can break your AI app.

Start by deciding whether you will integrate your AI model into your app’s front-end or back-end. Ideally, you should integrate the AI model in your app’s front end from where your users can easily access it. However, if you have a speech recognition AI model, integrate it into the app’s backend for better accuracy.

Depending on your specific needs, you must decide on how your AI model will process the data- on the cloud or on-device.

Edge Computing vs. Cloud Computing

On-device processing is useful if you wish to develop an AI-powered IoT app. If not, you can go with the cloud-based data processing option.

You must also create a feedback loop for your AI model so users can leave feedback and rate the AI model’s performance. This way, you can improve its performance.

User feedback loop

In addition, inform your users about your AI app’s capability to build trust with your users, while ensuring that any interactions they have with your app are intuitive. No matter how complex your AI model is, the interaction should be simple.

6. Test and Iterate

Lastly, you need to test and iterate your AI-powered app to ensure that it is working perfectly. You must also retrain your AI model with fresh data to keep it relevant throughout its cycle and prevent it from drifting.

You should perform three types of testing:

  • Unit Testing: It is when you test how the individual components of your app work. For instance, if your app has an AI chatbot, you must individually test it to ensure that its greeting function is working properly. You can even automate unit tests to avoid manually testing your app’s components.
  • Integration Testing: Involves testing different components to ensure the app works properly. This way, you will understand how the AI model functions with your app’s other components.
  • User Acceptance Testing: This test ensures that your AI app and model meet the user’s needs. Have a diverse group of people to test your app so you can easily cover a range of user perspectives and improve your app’s performance accordingly.

List of Top Artificial Intelligence Apps

Here are the top 4 artificial intelligence apps:

Google Assistant

This AI-powered assistant is designed for Android smartphones so users can access their devices hands-free. It has capabilities that allow users to manage their smart home products. By saying "Ok, Google" one can easily activate the application.

Features

  • Simple note-taking, meeting, and reminder setup
  • Helps with route planning, flight availability, and vacation planning
  • Let users control device settings and functionalities via voice command

2. Amazon Alexa

Amazon Alexa

Another popular AI app is Amazon Alexa which performs simple tasks like making calls, playing music, and checking the weather via voice command. By properly integrating Alexa with IoT, you can create home automation.

Features

  • Provides home automation
  • Rapid responses to queries
  • Allows you to use voice commands to play music and radio
  • Easily set reminders and alarms

3. Replika

Replika

It is one of the best AI-powered apps that acts as an online buddy. It allows people to have proper communication on multiple topics. People widely use Replika because it talks about their lives and interests.

Features

  • Provides inspirational quotes and thoughts
  • It can tell a meme or joke
  • Can answer text messages
  • Communicate about certain topics

4. FaceApp

FaceApp

FaceApp, an Android app with AI integration, is made to alter images. You can use this app to turn a selfie into a portrait. It offers numerous tools to edit photos. Thanks to the embedded AI filters, the pictures can be beautified.

Features

  • Offers hundreds of pre-made template
  • Allows you to give a realistic look to your photos
  • Offers multiple backgrounds and effects
  • Allows you to post the image straight from the app to your social media accounts

How Much Does it Cost to Develop an AI App?

AI app development cost depends on various factors like tech stack, location of the development company, type of app, and more. But on average, the cost can fall somewhere between $19k to $34k.

Before getting started with the app development process, you must discuss your project with the company to get a more accurate idea of the cost.

Below is the app development cost per location:

AI app development cost

How ÍøºìºÚÁÏ Can Help You?

Although creating an AI-powered application can be difficult, the advantages greatly exceed the difficulties. AI can improve your application's functionality, give users more value, and boost sales for your company.

As an award-winning mobile & web app development company, Protonshub Technologies is committed to staying ahead in this exciting field. We take pride in offering artificial intelligence in mobile app development services that meet and exceed our client's needs.

No matter how big or small your AI app development project is, we can handle it with confidence. Don’t wait anymore. Contact us today with your AI app development needs.

Frequently Asked Questions

The time taken to build an AI app depends on the project’s complexity and the team’s expertise. Creating a simple app takes a few weeks, whereas building complex ones can take up to several months or years. Developing high-quality AI apps requires thorough planning, testing, and research.

There are multiple free AI apps, including Microsoft’s Azure Machine Learning, Facebook’s PyTorch, and Google’s TensorFlow. These apps are loaded with several features and functionalities that can be used for developing an AP project.

Ekta

Ekta Singh

"Senior Content Writer"

Ekta Singh is a rookie food experimentalist and k-drama fan with 4+ years of experience in writing. Bridging gaps between companies and customers through conversion-driven content is her forte. She believes in writing stories for a living and living life for exploring places.