How to Create an AI App: An Ultimate Guide [Steps + Cost + Timeline]
6 Simple Steps to Create an AI App
Developing an AI app might look complex as it requires advanced working with advanced technologies such as artificial intelligence, machine learning and data science. But, following the streamlined process helps you to build an AI app faster. Let’s discuss each step in detail.
Define Your Problem and Perform Market Research
Before you begin the process of developing an AI app, you have to first identify the problem that your app is going to address. These problems can range from:
- Struggles to handle large volumes of data efficiently.
- Faces challenges in personalization and interactions.
- Falls short in reducing operational expenses.
- Lacks to understand customer behaviour.
- Fails to cater to individual user preferences.
This step sets the goal for your AI mobile app development. Once you have identified the problem, your next task is to create a solution through AI app development. Let’s make you understand by taking an example.For example,
Suppose you want to build an AI app that helps clinicians diagnose rare diseases precisely. By focusing on “rare diseases,” you can narrow down the types of data you’ll need and the machine learning models that would be most effective.
Now that you have clearly defined your problem, you need to do market research on the AI app you are going to develop. You should consider various aspects, such as:
- Search for similar AI apps on the App Store and Play Store.
- Compile a list of the strengths and weaknesses of competitors’ AI applications.
- Analyze the design, user interface, and how easy it is for users to navigate through competitors’ apps.
- Identify the unique features that set competitors apart and the specific audience the competitor caters to.
- Take note of any errors or areas where competitors’ apps could be improved.
- Determine the platforms or channels where competitors host AI apps, whether it’s on the web or through mobile apps.
Quick Tip: When you do competitor analysis, check the reviews of your competitors where users have mentioned a specific feature that is not present in their apps. You can then consider adding this feature to your app in order to stay ahead.Contact an AI Development Company
You already know that the success of your project depends largely on the expertise of the app development team. So selecting a reliable AI app development company is so important for your app.
You can start finding reliable AI mobile app development companies through various platforms such as Clutch and IT Firms. But before starting your research you need to consider the following factors for selecting an AI development company.
- Look for a company that specializes in artificial intelligence and machine learning.
- Review the company’s portfolio and past work.
- Make sure the team consists of data scientists, machine learning engineers and developers with AI expertise.
- Verify that the company uses the latest AI frameworks and tools.
- Discuss project costs and timelines upfront.
Once you get in touch with an experienced AI app development company, your idea gets validated and you get suggestions, and you get the cost and timeline to build an AI app for your business. Now that you have selected an appropriate company for AI mobile app development you need to think of the design of your app.
Design the UI/UX of the AI App
This step is essential because an app requires a user-friendly and appealing interface to capture user attention. A well-planned UI and UX design not only enhances customer satisfaction but also ensures that users interact seamlessly with your AI-powered application.
Based on the research and business requirements, the BA team sketches out initial wireframes for the app. These wireframes serve as a blueprint for the UI/UX team, outlining the basic structure and elements of the app.
Once the wireframing is completed, the UI/UX team begins the process of transforming the wireframe into a full-fledged design. This involves selecting color schemes, typography, and visual elements that align with the brand identity. The UI/UX team uses tools like Adobe XD to add hues to your design. UI/UX designers create a sample design to know your color preferences.
Quick Tip for BA Team
Create wireframes for the core screens first. Choose the screens that are the most important for the user flow. It will make it easier to iterate your design.
The BA and UX/UX teams collaborate to make necessary adjustments based on this feedback, ensuring that the design is responsive and works seamlessly across various devices and screen sizes.
Development of Your AI App
This step involves the development part where two things are prioritized including the data collection and selecting an appropriate AI algorithm and training it. To help you understand it better let’s discuss it in detail.
Collect Data for Training and Testing Your AI App
Consider data to be a starting point to drive your AI application. To get your project started, the development company needs to collect a large dataset that is closely related to the app’s purpose. Here’s a complete breakdown to help you understand.
- The process begins with identifying the data sources from which data needs to be collected. These sources may involve compiling data from existing databases, user-generated content, or information generated by sensors and Internet of Things (IoT) devices.
- Attention must be given to the quality of the data. To achieve this, data cleaning and preprocessing may be necessary to reduce inconsistencies.
- Ensuring compliance with data privacy and legal guidelines is essential. It’s crucial to verify that all required permissions are in place for data usage and that the project aligns with data protection requirements.
Having data on hand will be helpful in training the AI models to recognize patterns for making accurate predictions and testing the model to assess its performance.
Select an Appropriate AI Algorithm and Begin Model Training
Choosing the right AI algorithm is similar to choosing the core functionality of the AI mobile apps. This decision has a major effect on the app’s functionality.
The first step is to decide whether the AI model will learn from labeled data (supervised learning) or identify patterns on its own (unsupervised learning). Second, depending on the specific problem, different algorithms may be selected. Check out some of these examples to help understand.
- Convolutional Neural Networks (CNNs) for image recognition.
- Recurrent Neural Networks (RNNs) for sequential data.
- Support Vector Machines (SVMs) for classification tasks.
Now, the focus shifts to refining the hyperparameters of the selected algorithm to optimize the performance. In this part, adjusting parameters like learning rates, batch sizes and network architectures is required.
Evaluate and Test Your Trained AI Model
In this step, a systematic approach is required to analyze and test your trained AI model. The validation and preprocessing of data are carried out by the QA team, involving a thorough inspection of the datasets for errors and ensuring it’s in the correct format.
The next thing is to develop performance indicators that are specific to your app’s nature. Testing the model against these measures allows for the identification of strengths and limitations. While stress testing shows how the model responds to extreme inputs.
Integrate automated testing procedures for real-time performance monitoring, which helps identify and resolve issues in the AI model.
- Make sure AI models predict correctly or sort data accurately.
- Helps find and fix mistakes or biases.
- Ensures how well the app works in unusual or extreme situations.
- Guarantees that the data used for model training is of high quality.
- Allows for constant refinement based on feedback and changing data.
Check out why testing is important in AI app development:
Deploy and Maintain Your AI App
After testing, the company chooses a reliable hosting service that includes options like AWS, Azure, or Google Cloud, to deploy AI apps. Apart from deployment, the phase involves maintenance of your app as well. Maintenance ensures that you effectively address any performance concerns, respond to user feedback or complaints, and handle any unexpected bugs that may develop.
The company monitors your app’s performance, security and compliance with relevant regulations like GDPR, depending on your data handling. All of these combined will keep your simple AI app running smoothly while ensuring data protection at its best.
Now that you have a clear understanding of the steps involved in developing AI-powered apps, you might be thinking about the costs associated. To provide you with a better idea, let’s discuss the cost of developing an AI app.
How Much Does It Cost to Create an AI App?
On an average, an AI app development cost can range somewhere between $10,000 to $2,00,000+. Getting the precise cost to build an AI app is difficult as the cost varies based on different factors including project complexity, quality and quantity of data, number of developers, location of developers, and expertise of developers.
Check out this table to get an idea about the cost based on the type of AI app and the timeline to build the app.
| Type of AI App | Examples | Average Cost |
|---|---|---|
| Simple AI App |
| $10,000 – $50,000 |
| Average |
| $50,000 – $200,000 |
| Complex |
| $200,000+ |
Note: The cost listed in the table are average cost and varies depending on specific features to integrate, data requirements, and the customization required for each app.
Once you have an idea of how much it costs to build an AI app, you might want to know about the time it takes for the artificial intelligence app development process. Here is the time estimation.
How Much Time Does it Take to Develop an AI App?
The time it takes to develop an AI app ranges from 1 month to 12+ months. This time frame depends on multiple factors like complexity, team size and project requirements. A simple AI app can take 1-3 months to develop, an average AI app takes 3-6 months while a complex AI app can take 12+ months.
However, the actual time differs based on various factors including.
- The complexity of the AI algorithms
- The level of customization needed for the AI model
- The availability of the data and quality of data
- The expertise of the AI app development team
- The specific features and functionality required
- The dependencies on external parties
To give you more clarity about the timeframes of developing AI mobile apps, here is a table containing the average timeframes based on some of the factors like the type of AI app and the AI features integrated into the app.
| Type of AI App | Specific Examples | Key Features | Timeframe |
|---|---|---|---|
| Simple | AI-language Translation App |
| 1 – 3 months |
| Average | Health and Fitness Assistant |
| 3 – 6 months |
| Complex | Smart Home Automation System |
| 12+ months |
Note: The listed features are core functionalities, but the actual features vary based on the project goals. Also, the AI app development timeframes in the table are approximate and can be altered by factors such as team expertise, resources and unexpected challenges.
So, now you know how much time it takes to develop an AI app and what factors influence the time. Let’s help you get more clarity on developing an AI app by covering the technology stack used in developing an AI app.
Technology Stack Used in Developing AI App
Creating an AI app involves the selection of a strong technology stack such as to support the app’s AI capabilities. Check out the table below that contains the tech stack used in developing an AI app.
| Technology Category | Key Technologies |
|---|---|
| Programming Languages |
|
| AI Frameworks |
|
| Deep Learning Libraries |
|
| Data Processing |
|
| Neural Network Architectures |
|
| Natural Language Processing (NLP) |
|
| Computer Vision Tools |
|
| Cloud Platforms |
|
| Web Development (Front-end) |
|
| Web Development (Back-end) |
|
| Database Management |
|
| DevOps and Deployment |
|
| Version Control |
|
This technology stack makes it easier to build and run AI models. You may scale your app as per your requirements using cloud platforms such as AWS and Azure. This stack enables developers to create a high-quality AI app that solves your problems.
After learning the technology stack, check out how Space-O Technologies helps you build your AI app.
How Space-O Technologies Helps You Build Your AI App
As a leading app development company in Canada, Space-O Technologies excels at developing AI mobile apps. Space-O Technologies has successfully delivered more than 300 solutions to various industries using methodologies such as Agile, Scrum and Waterfall. These industries include healthcare, transportation, insurance, real estate, events and travel.
- Programming languages: Python, Java, PHP, C++, Ruby and Swift.
- Frameworks: React Native, Flutter, TensorFlow, and PyTorch.
- Cloud platforms: Azure, AWS, and Google Cloud.
- DevOps Tools: Git, Jenkins, and Docker.
Our developers are well-versed in delivering such industry-specific solutions using the latest technologies and tools that include:-
In particular, the company specializes in developing AI mobile apps using OpenAI.
Our developers are experts in utilizing OpenAI models such as Codex, ChatGPT, and DALL·E for AI app development. Not only this, but our developers also have experience in integrating the OpenAI models into your existing business app solutions.
Whether you are looking for AI consultation, aiming to build an AI app, or looking to integrate AI into your existing app, you can reach out to us. With our team of developers who are experts in AI technology, we can help you solve your problems and deliver a powerful AI app.
4 Benefits of AI Apps for Your Business
By developing an artificial intelligence app you can not only streamline your business operations but also provide personalized customer experience, gain data-driven insights, and realize significant cost savings. Check out some of the key benefits of artificial intelligence apps for your business.
Improve Efficiency and Productivity
Artificial intelligence apps are designed to automate tasks that are repetitive and time-consuming. This allows your team to focus on more critical tasks. Whether these tasks involve data entry, customer support inquiries or inventory management, artificial intelligence apps handle all of these business processes with precision and speed.
Enhance Customer Experience through AI App Integration
AI plays an important role in creating a customer-centric business environment. These apps can analyze data of customers, preferences, and behavior to provide personal interactions, recommendations, and offers. Having such personalization builds strong customer relationships and boosts brand loyalty.
For example,
AI algorithms examine a user’s browsing and purchasing history to deliver personalized product recommendations. If a customer routinely purchases athletic shoes, the system offers related products such as sports apparel or fitness equipment, increasing the chances of future sales.
Enables Data-driven Decision-making
Making decisions based on information is an important advantage for businesses in the age of big data. These apps process large volumes of data quickly and deliver meaningful insights, thus serving as a useful asset in this area. AI-driven data analytics help you make data-driven decisions that lead to strategic benefits, whether you’re monitoring market trends, feedback from customers, or operational metrics.
For example,
AI-based apps help in the diagnosis of medical disorders by evaluating patient data and medical literature. This diagnostic tool evaluates a patient’s symptoms, medical history, and test results to offer a list of potential diagnoses, allowing physicians to make more accurate and timely decisions.
Offers Cost Savings with the Integration of AI
AI-based apps result in major cost savings across various aspects of your business. These aspects include operational efficiencies, a decrease in labor expenses, reduced errors, and optimal resource allocation. AI-based apps allow you to automate operations that previously required manual labor. Also, AI-driven data analysis can point out areas where resources can be distributed more effectively, which will reduce costs and enhance overall financial performance.
For example,
AI tools can help a digital marketing business optimize ad spend. These types of apps can analyze ad performance data, determine the most effective campaigns, and distribute funding accordingly. The agency can improve ROI and eliminate waste by reallocating resources to the most profitable campaigns.
For example,
AI systems for inventory management can track product sales in real time, automatically restore items when stock runs short, and even predict future demand trends. Not only does this reduce the need for manual stock inspections, but it also assures that popular products are constantly in stock, enhancing sales efficiency.
Now that you have a complete understanding of the benefits associated with AI mobile apps. Let’s understand the use cases of developing AI apps for different industries.
Top 7 Use Cases of AI Apps
Check out the following use cases of artificial intelligence applications.
- Healthcare: AI is used to analyze medical images like X-rays to detect and diagnose fractures or abnormalities, aiding radiologists in their assessments and expediting patient care.
- Finance: AI algorithms analyze financial data and execute buy/sell orders automatically, optimizing investment portfolios and maximizing returns for investors.
- Retail: Retailers use AI-powered recommendation systems to suggest products to customers based on their browsing and purchase history, increasing sales and customer satisfaction.
- Manufacturing: Manufacturers use AI to predict when industrial equipment, such as manufacturing robots, will require maintenance, reducing costly downtime.
- Automotive: AI is used to build self-driving cars that can navigate roads and make driving decisions autonomously, which reduces accidents and improves transportation efficiency.
- Education: AI in education customizes lesson plans and content for individual students, tailoring the learning experience to their strengths and weaknesses, improving learning outcomes.
- Entertainment: AI is used to recommend movies or TV shows to users based on their viewing history and preferences, enhancing user engagement and content discovery.
If you still have questions regarding AI mobile apps, check out the FAQ section to get answers to your questions.
FAQ About Developing an AI App
What are the limitations of an AI app?
Here are the limitations of an artificial intelligence app
- Relies on large datasets for training and may perform poorly in data-scarce scenarios.
- Inherent biases present in training data, leading to unfair or discriminatory outcomes.
- Vulnerable to attacks and may compromise sensitive information.
- Lacks true creativity and innovation, often producing results based on existing patterns.
- Requires computational resources to train and run advanced models.
How can I make money from my AI app?
Here are the different ways you can make money from your AI app
- Offer subscription plans with different features to generate steady recurring income.
- Encourage users to purchase extra features or content within your app for added value.
- Generate revenue by displaying ads in your app or partnering with relevant sponsors.
- Provide an API for others to use your AI, charging them for access.
- Offer tailored AI solutions and consulting services to businesses to solve their specific needs.
Is it possible to build an app using OpenAI?
Yes, you can create an app using OpenAI. OpenAI provides various tools and APIs to let developers integrate advanced natural language processing capabilities into the apps. These tools can be used for various AI applications, including chatbots, content generation, and language translation.
Using GPT 3, developers can develop AI-powered applications in such a way that generates human language that is similar to what a person would write. This makes it possible to build an AI app that interacts with users through natural language.
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