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.
A report published by Grand View Research 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.
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In this article, we will cover:
Let’s dive into business and technical details.
AI-powered mobile apps are popularly used by the top 5 industries, including healthcare, finance, retail, manufacturing, and education.
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]
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]
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]
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.
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?]
Wondering how to create AI app? Follow these six easy steps to get started:
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.
Common AI-specific KPIs that will help you track and access your AI model’s performance are:
Next, you must set clear development and deployment milestones. This can be easily done if your team uses an 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.
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:
Besides these three AI frameworks, you can also choose from cloud-based AI platforms like Google Cloud AI, Amazon Sagemaker, and Azure Machine Learning.
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.
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:
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.
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.
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.
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.
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:
Here are the top 4 artificial intelligence apps:
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
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
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
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
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:
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.
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.
"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.
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