In the present times, technologies like Artificial Intelligence are used worldwide in mobile and web app development. A Gartner report reveals that 85% of the customer interactions in 2020 are non-human. Modern technologies like Machine Learning (ML), Artificial Neural Networks (ANNs), advanced analytics based on big data, and deep learning have entirely changed how digital products are created and function.
However, creating an Artificial Intelligence app is a time-consuming process, and it needs a team of software developers, data scientists, and the collective effort of others. And only then can one create an innovative, customer-centric, and cost-effective AI application.
We will discuss the various aspects of creating an Artificial Intelligence app and how to create an artificial intelligence app:
What Is Artificial Intelligence And Industries Using Artificial Intelligence-Integrated Apps?
Today several industries are using artificial intelligence technology, and by the year 2026, we expect the artificial intelligence market to reach $309,6 billion. Here we discuss the many industries using Artificial Intelligence and benefitting from its employment. Meanwhile, as per the app’s purpose and complexity, different types of Artificial Intelligence can be used in mobile apps, such as general, narrow, and super (also known as NAI, AIG, and ASI). These solutions are implemented in industries like:
Today, autonomous vehicles like cars, buses, and trucks, are integrated with Artificial Intelligence technology to offer better transportation services. The transportation industry immensely benefits from features like line-changing, automatic vehicle guidance, and collision avoidance via a combination of light detection & ranging system and AI.
With AI tools, it is possible to automate grading, enabling teachers to focus on the critical aspects of education. Education apps offer AR/VR experiences to their users to visualize app content, assess students while learning, and help them learn at their pace. One of the AI products is digital tutors that quickly adapt to the learning environment.
Several medical & health insurance apps use AI technology that helps doctors diagnose better, even remotely, and make accurate health predictions. Chatbots enable easy appointment scheduling and answering general users’ queries and even offer basic virtual diagnostics.
A number of industrial firms are working to introduce robots into their workflow. They are using this technology to automate & optimize the same tasks earlier performed by humans, resulting in reduced labour costs and increased production volumes.
To keep up with the rising competition, customer-focused organizations must employ artificial intelligence technology. CRM and Analytics platforms use Machine Learning for collecting data & analyse use profiles. Then we have AI-powered chatbots that are today replacing the call center employees, enhancing customer satisfaction, and reducing the staff costs.
How Artificial Intelligence Benefits Businesses?
If you have decided to invest in AI app development, this is how this technology can benefit your business, such as:
- With automatization of routine processes and tasks, increased efficiency with time and money
- Identifies new sales channels & opportunities
- It offers protection from the human error
- Allows making better and faster business decisions based on data provided by AI & ML.
- Reduced workload results in better efficiency and productivity
If you are willing to develop an AI app, keep in mind that this technology has the potential to change how a business operates and can make it more efficient.
How To Create An Artificial Intelligence App?
AI app can be created by following these steps:
Identify A Problem, Define Requirements, And Plan
To create an AI app, you first need to identify a problem. Ponder over the processes & functions of the apps where you want to implement AI stack technologies, what results you are expecting from it, and how it will benefit you.
After identifying the issue, create a clear list of product requirements and document them. Developers like to have proper and structured requirements to understand the purpose of creating a product/software and identify tools and technologies. As you plan, you need to decide on the app development company. Associating with an app development firm will allow you to access a team composition of technical and non-technical experts – from project managers to business analysts to data engineers and backend programmers. Then it is time to create a work schedule with the experts and, finally, explore the data necessary to develop Artificial Intelligence and Machine Learning model.
Pick An App Development Company Offering AI Solutions
Creating an AI app is complex. The app development firm you are choosing must have a great understanding of how AI technology works. Hence, it is advised to hire a reputed AI app development firm to build your Artificial Intelligence app. You can search for the best AI app development companies at Manifest, ITFirms, and Clutch platforms.
Cost To Create An AI App
Determining the cost of creating an app is quite complex as it depends on several factors; however, as it comes to an Artificial Intelligence, it is sure to cost 20-40 percent more than a usual mobile app, as to create an Ai app, the development firm requires to spend more time and efforts in the development process.
App UX & UI And Features
Once you pick the app development firm, it is time that you work on the app design, which plays a crucial role in the success of any app. Prefer to keep the app design appealing and user-friendly. It is also the time to finalize the app features, both basic and advanced features. You can also choose to integrate some unique features to make your AI app stand out among the competing apps.
Data Mining & Modelling
Usually, AI-powered apps need large chunks of data for operation, and it is vital to collect and prepare it appropriately to receive an accurate model. At times, data even require labeling by labeling specialists, who are a part of a software development firm that offers AI and ML-based solutions. Software developers study the input information & its sources carefully to prepare the dataset (data for implementation) for further usage. However, they are mainly using CRISP-DM (Cross-Industry Standard Process for Data Mining). Now time to check the input data for any missing values, incorrect labels, errors, and once it is clear, time for data presentation that comprise: select & upload raw data, pick annotation tools, highlight and label data blocks, and choose and save file formats. The gathered dataset enables us to compare solution options and head to the modeling stage. The data collected in the past is used for training ML models via different methods. Once the model is trained, it is tested, evaluated, and deployed. And as you have a model, you can load it into a mobile app.
MVP Model And App Development
Creating an MVP model of the app allows to present the app product in numerous versions and evaluate basic functionality and app viability. Sometimes, businesses restrict themselves to MVP by gathering first feedback, thus reducing one-time costs. However, you need a full-fledged app offering advanced functionality and unique features to get a competitive advantage. Except for the CRISP-DM, developing an AI app is quite similar to other app development. You have to consider the app architecture, User Interface Design and develop the frontend and backend.
As you reach the development stage, you can optimize the app performance, enhance & expand app functionality, and adapt your software product to updates of different operating systems.
App Testing, App Launch & Maintenance
Once you have developed the MVP and the final app is also developed, it is time for the testing with QA experts’ assistance. These experts usually use automated, manual tools or their combinations. After app testing, it is ready to be launched in the app stores. It is advised to regularly update the app to keep supporting the latest OS versions.
What Tech Stack You Need For AI App Development?
To create an AI-integrated app, you require choosing the right technologies and solutions:
Usually programming languages like Java, Python, and C++ can be used for creating Artificial Intelligence-based apps. Program engineers also use languages like R, C++, Prolog, or Lisp, as per the solution. To reduce the hardware & development costs, hire dedicated developers often use 3rd-party AI and ML platforms. The most commonly used platforms are:
Amazon Machine Learning
This platform helps create, train, and deploy models & intelligent apps regardless of their complexity level. AML is based on a simple, flexible, and scalable ML technology used by scientists from the Amazon community. It delivers unique analytics, simplifies creating apps, and routine procedures, supports many data sources, and allows identifying human speech & visual objects through deep learning.
Microsoft Azure has launched its Machine Learning to create, train, & deploy models. This platform offers a myriad of algorithms, high-quality multilingual documentation, and advanced analytical mechanisms. AI and ML’s capabilities include natural language processing, pattern recognition, predictive modeling, recommendations mechanisms, and other services. This service can be used anonymously for eight hours to check capabilities without having an account.
An open-source software library, Google TensorFlow is a pioneering data science environment to make numerical computations using dataflow graphs and creating AI-based projects from ideation to launch. Its flexible architecture enables computing to be deployed across various processors using a standard API. With TensorFlow, you can cover numerous use cases as desired while creating AL/ML app.
Other AI platforms are Api.ai, Wit.ai, a low-code Mendix platform, an open-source Melissa platform, Oracle AI cloud services, IBM Watson, etc.
Frameworks & APIs
Advanced technologies like Machine Learning, Artificial Intelligence, and other deep learning frameworks immensely simplify the development of high-tech and complex products and enable utilizing 3rd party functionalities to integrate them with the app. The popular frameworks and APIs consist of:
This works best to build modular deep learning environments. ML’s open-source & a set of algorithms enables engineers to experiment with various models.
This ML framework & app by Apple are domain-specific and works best to develop AI products for iOS.
A combination of ML library, scientific computing structure, and pre-trained models allows for quickly building complex systems like deep neural networks. This Python-powered framework offers excellent efficiency & flexibility.
Amazon Machine Learning (AML)
This toolbox helps develop highly-complex apps delivering high performance. It can connect apps to cloud services and create forecasts using API.
Microsoft Cognitive ToolKit (CNTK)
This toolbox helps create several Machine Learning models, even the recurrent & convolutional neural networks. You can use this framework to process a range of unstructured data quickly, choose algorithms and metrics, and train the machine to virtually think like people.
Other frameworks are also available, such as SparkMLlib, Scikit-learn, Accord, Net, Keras, etc. You can make the pick as per what solution suits you the best.
For creating an AI app that uses robust technologies like speech-to-text and text-to-speech, big data analysis, and face recognition, you will need to be fully armored. Third-party APIs & software development kits (SDKs) are great at simplifying the task and speeding up development. It consists of Apple’s SiriKit, Google Vision, Microsoft Face API, Azure Topic detection API, and other AI uses products.
If you are keen to develop an AI app, at Inventcolabs, we are a mobile app development company with expertise and experience in creating Artificial Intelligence apps.