How to Build an AI App? [2025 Guide]

According to statistics, the AI mobile app market is growing at a 33.7% compound annual growth rate and is expected to achieve a valuation of over $249.8 billion by 2033. Undoubtedly, businesses worldwide are adopting new technologies to achieve competitive advantages, reduce expenses, and enhance their customer experience. However, apart from big enterprises, most businesses still have no idea how to create an AI app.

So, this blog will be talking about everything AI app development, the complete process, technology stack, costs, use of artificial intelligence (AI) in mobile apps, development challenges, and everything that you should know to integrate this amazing technology into your business. As an innovative AI development company, The NineHertz believes in the power of this technology to transform and grow any business. So, our team operates on the vision of making AI app development affordable to all.

What Is an AI App?

Before we jump on “how to build an AI app”, it is important to understand what AI apps are and their role in modern businesses. So, AI apps are the software programs that use industry 4.0 technologies like machine learning, computer vision, and natural language processing to perform tasks with more efficiency, speed, and accuracy. The AI apps are highly dependent on data analysis to understand the input and provide the expected output. You might be interested to know the difference between Artificial Intelligence vs Machine Learning.

For example, an app is designed to edit images based on the command provided by the user in the text format. So, the app will use artificial intelligence to understand that command, interpret it in the required computer language using natural language processing, perform the task, and provide the output to the user.

We have been using mobile apps for quite some time, and thus, it might be challenging for anyone to differentiate between traditional apps and AI-powered apps. If both are the same, what is needed to build an app? So, here is a short table that will help you understand the difference between a normal app and an AI-powered app-

Benefits of Developing an AI App

No matter if you perceive things from the business-centric perspective or the customer-centric perspective, building an AI app is beneficial for each associated stakeholder. For the workforce, it automates tasks, reduces manual efforts, increases productivity, and saves a lot of time. Similarly, for the end-customers, the AI applications provide the personalized user experience that helps them make better and quicker decisions.

Let’s have a glance over some of the core benefits that AI app development brings along-

1. Data-Driven Decision Making

With AI app deployment, you no longer need to make vague commitments and decisions as you have a smart assistant that will analyze a huge amount of data for information-driven decision making. Whether controlling the inventory, stocking the goods, buying a trade, or just creating the content for your target audience, the AI apps analyze the historical data to give you insightful information on what call you should take.

2. Workflow Automation

Creating an AI app ensures that you no longer need to waste time in unproductive, repetitive tasks like sending emails, setting reminders, or taking the minutes of meetings. The AI agents and application are designed to perform such tasks without even giving the manual command each time. At the same time, these bots eliminate the chances of human errors and thus promise increased accuracy.

3. Personalized Experience

No matter if you have a hundred or a hundred thousand customers, the AI apps take care of each of them according to their preferences and tastes. Building an AI app will ensure that you collect the required information about customer preferences, buying behavior, demographics, and much more. Thus, the application even helps in suggesting the relevant product to the customers and increases the revenue.

4. Cost Efficiency

AI solutions are a highly cost-efficient solution for startups as well as big enterprises. Such apps can seamlessly automate the range of tasks that would otherwise require a huge workforce. At the same time, it helps to increase efficiency and save time, which enables you to invest your time in other crucial tasks. Moreover, the AI tools are versatile in different environments and changing trends, which eliminates the need for frequent updates and infrastructure investments.

5. User Penetration

One of the biggest advantages of building a mobile app is that it makes user penetration very easy. AI apps are optimized for smartphones, and thus, businesses can expand their reach to billions of smartphone users within a short time. Also, the mobile apps make the AI application easy to navigate, which results in high user adoption.

6. Competitive Advantages

While businesses are continuously adopting artificial intelligence, there is still a big space where AI has yet to be explored. So, this is the best time for the firm to leverage amazing competitive advantages by integrating artificial intelligence into their operations. The differentiating factor can help significantly to the businesses to stand out from their competitors and grab attention.

7. Sustainable Growth

AI app development doesn’t require an aggressive investment, and thus it supports sustainable business growth. The technology can handle the bulk of tasks, withstand the increasing and changing user demand, allow the demographic expansion, and adapt to the changing business needs without compromising the overall quality.

Which Industries Can Use AI the Most?

Artificial intelligence is not an industry-centric technology. It is a versatile concept that can adapt to different industrial standards and requirements to make the processes quicker and assist the stakeholders. Whether it is healthcare, entertainment, sports, or finance, AI app development can be customized according to different industrial requirements.

1. Healthcare

• A healthcare institute can create an AI app to compare the disease symptoms to the database and suggest the best treatment using data analysis capability.
• The software helps to analyze the past medical records of the patient to offer a tailored treatment.
• The AI tools are highly helpful at identifying the signs of serious diseases in earlier stages to prevent damage.

2. FinTech

• Building an AI app for the FinTech industry helps in analyzing transaction patterns using machine learning to report suspicious activities.
• A range of financial planning services like insurance and investment can be automated using these smart solutions.
• The automated credit score assessment helps to check if a person is suitable for a loan or not.
• The tools can track the expenses, predict upcoming spendings, and craft a personalized finance management plan.

3. Entertainment

• Most of the OTT platforms like Amazon Prime and Netflix are using AI-based recommendation systems to suggest content to their users.
• The AI technology helps in assessing the user interests in content to provide the content idea for maximum reach.
• AI is highly used in the games to optimize the control settings and enhance the overall user experience.

4. Education

• The education industry leverages AI app development to track learners’ performance and curate personalized learning plans.
• Artificial intelligence is well-designed to assess the challenging topics for the students to help them focus more on them.
• AI apps are highly used to answer questions and explain concepts in various subjects.

5. Hospitality

• AI is highly used to assess user preference and suggest the right routes, restaurants, and hotels.
• The AI-powered chatbots help in providing 24*7 support to the customers for a better experience.
• The AI translation bots help the tourists to interact with local people without a human translator.

6. Manufacturing

• AI comes with predictive analysis that helps manufacturing firms make smart decisions on production.
• Artificial intelligence solutions development assists in analyzing market demands to optimize inventory stocking.
• The predictive maintenance feature of such apps helps in the timely repairing of machinery to avoid damage.

7. Security

• The highly-trained AI models can efficiently identify the anomalies in patterns by analyzing the content receiver and sender behavior, resulting in instant reporting.
• The smart anti-virus software is capable of identifying and protecting the systems from viruses and threat sources.
• An advanced AI security layer automatically initiates the preventive measures that reduce the response time and increase the security.

How is AI used in mobile apps?

When we talk about creating AI apps, the features are integrated into the mobile applications according to the particular client and audience needs. However, as artificial intelligence is ruling the digital market, there are already many mobile apps using this amazing technology in an innovative way. Let’s have a look at some of the best uses of AI in mobile apps.

1. Chatbot and Virtual Assistant

Most of the mobile apps use artificial intelligence to integrate the smart chatbot and virtual assistant feature in their solutions. This application of AI helps the users to easily navigate the functionalities, solve queries, and provide personalized customer support around the clock. At the same time, the AI chatbot in the eCommerce platform helps to suggest products according to the personal preferences of the customers.

2. Speech Recognition

This is a vital application of artificial intelligence where the software can convert the user command from voice input to coding language that a computer can process. There are numerous examples like Siri, Alexa, Google Assistant, etc., that can perform tasks like opening an app, making calls, setting reminders, sending texts, and more.

3. Process Automation

This is also one of the biggest applications of AI in mobile apps. The technology helps in performing the repetitive tasks without human intervention, while ensuring the speed and accuracy. For example, apps like Gmail can automatically sort the emails in different categories like social, updates, primary, and promotions, which help the users to move directly toward the more important emails.

4. Security Enhancement

AI is prominently used in mobile apps to add a strong layer of security and bring users reliability. For example, Kaspersky is a virus protection software that blocked over 33.8 million malware, riskware, and adware attacks in digital devices. Features like advanced algorithms, behavioral biometrics, and biometric authentication have steered utmost security for users on mobile apps.

5. Dynamic User Interface

The first impression of the mobile app is very important to attract the users. Thus, AI is being widely used to create intuitive UI of mobile apps that help to optimize the navigation and efficiently use the overall space. At the same time, the technology also helps to adjust the text, size, and pictures according to the particular demographics of the target audiences.

6. IoT

AI is an integral part of the mobile apps, which helps to control other devices and appliances like television, AC, smart fans, speakers, and more. Artificial intelligence helps significantly to connect the various devices, create an ecosystem, and provide convenience to the users.

7. Image Recognition

You would have come across the eCommerce store and other mobile apps that can identify objects, people, faces, natural things, and even places. All these image recognition features are a part of AI app development. Whether it is searching for shoes with its image or leveraging the OCR technologies to search and manage documents, AI plays an important role.

How to Create an AI App?

The NineHertz builds the AI mobile app while deploying the agile project management methodology. It allows us to divide the entire project into multiple sprints. Our team moves to the succeeding phase only after achieving the expected quality and functional standards at the existing phase. The approach helps us to maintain the overall project quality and get an excellent final product. Here are the core phases of our AI mobile app development process-

1. Problem Identification

The very first phase of the process is dedicated to identifying the business problem and setting the ultimate goal of project development. This information helps us to choose the best technology stack that can be used to build the mobile app that can solve the problem and achieve the final goals.

• Deciding the team composition that will be working on the project is a part of this process.
• The project managers, development team, designers, and quality analysis team are deployed for the project.
• Data exploration is initiated to train the AI models with the best data quality.

2. Data Preparation

Moving ahead, the next phase is dedicated toward collecting and preparing the data to train the right AI model for the development. It is ensured that the data being collected is of high quality to make the outcome fully functional and scalable. Platforms like AWS Data Exchange and Kaggle are used for collecting the data.

• The process includes data clearing that helps to eradicate the duplicacy of information.
• The cleaning process includes the integration, transformation, normalization, and smoothing of the data.
• Data wrangling is then carried out to transform this information into a suitable format to train the AI model.

3. Selecting the Right Tools and Frameworks

As the name suggests, the third stage is all about choosing the best frameworks and tools to build the scalable AI app solution. It is ensured that the tools and framework choice aligns with the business challenges and the overall project goals. Choosing the right tools plays a significant role in accelerating the development process. Here are the best AI frameworks that are widely used for this task-

• TensorFlow– This is an open-source library that helps to build as well as deploy the machine learning models.
• PyTorch– This is a popular tool known for its modular architecture and utmost flexibility.
• Google AutoML– This is the best tool to train the AI model quickly with the least technical skills.

4. Fine-Tuning the AI Model

Just like the data, it is also important to make some customizations in the AI model so that it can be used to perform the particular tasks according to the clients’ requirements. Different types of training techniques can be used in this stage. The techniques are supervised learning, unsupervised learning, and reinforcement learning.

• The right model architecture is selected according to the input data.
• Tasks like data splitting and feature engineering are carried out to modify and create new features in the AI app.
• Data feeding and cross-validation are performed to ensure the effectiveness of the AI model across different datasets.

5. AI Model Integration into the App

This is one of the core steps of the AI mobile app development process in which the prepared and trained AI model is integrated into the mobile app. It is decided if the AI model should be embedded in the front end or back end of the mobile app. For example, a model like a speech recognition system is integrated into the backend for better performance.

• It is decided if the AI model will be processing the data directly on the device or in the cloud.
• The existing APIs are used for the integration that helps to save a lot of time.
• The feedback loop is integrated, which enables the users to report the issues so that improvements can be made.

6. AI Model Testing

Before the deployment of the application on the respective marketplace, the software is tested by the quality analysis team. The process is curated to ensure that the final product does not carry any bugs or errors and that the best version is deployed for the target audience. The testing team identifies the errors and asks the development team to make the necessary changes.

• Unit testing is carried out to test the smallest parts of the app.
• Iration testing is conducted to check if all the components are working collaboratively or not.
• User acceptance testing is deployed to ensure that the final product meets the practical expectations of the target audience.

7. Deployment and Monitoring

This is officially the final stage of the AI mobile app development process. At this stage, the mobile app is deployed to the respective marketplaces like the Google Play Store and Apple App Store. The deployment process helps to make the mobile app available to the end users. The monitoring is carried out to ensure that the software is working according to the predefined standards.

• The app is deployed in the client’s system or the app marketplace.
• All the compliances are ensured to make the software available to the audience.
• Continuous monitoring is deployed to check for the errors and make the corrections.

8. Maintenance and Updates

This is an ongoing process where our development team provides post-deployment maintenance and support. The focus of this stage is to maintain the utmost working potential of the AI mobile app, along with adding new features and eliminating old features according to the market trends.

• It is ensured that all the parts of the mobile apps are functioning to increase the user base.
• The periodic update is provided to make the software optimize for different operating systems and devices.
• New features are integrated according to changing market and industry trends to synchronize the user’s expectations and needs.

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What Is the Best Tech Stack for AI App?

Technology stack refers to the choice of technologies that can be used to build the AI mobile app. It is generally the technical architecture of the software that makes the final product functional and usable. A lot of technologies are integrated to perform certain tasks.

To build an AI mobile app that can adapt to the huge audience base and changing market demands, it is very important to choose a scalable and strong technology stack. Here is the tech stack that we use to develop an AI mobile app:-

Category	iOS Tech Stack	Android Tech Stack
Programming Languages	Swift, Objective-C	Kotlin, Java
Frameworks & Libraries	SwiftUI, UIKit, CoreML	Jetpack Compose, Android UI Toolkit
AI/ML Libraries	TensorFlow, PyTorch, CoreML	TensorFlow Lite, PyTorch Mobile
Cloud Services	AWS, Google Cloud, Azure	AWS, Google Cloud, Azure
Databases	Core Data, SQLite, Firebase	SQLite, Firebase, Room DB
Backend Development	Node.js, Django, Flask	Node.js, Django, Flask
APIs & SDKs	Apple CoreML, SiriKit, Vision API	ML Kit, Google AI APIs
Testing Tools	XCTest, Appium	Espresso, Appium
CI/CD Tools	GitHub Actions, Bitrise, Jenkins	GitHub Actions, Bitrise, Jenkins
IDE & Code Editors	Xcode, AppCode	Android Studio, IntelliJ IDEA

How Much Does AI App Development Cost in 2025?


The cost to build an AI app can range from $30,000 to $160,000. Such apps are designed based on a particular business scope and vision. Thus, all the features, functionalities, technologies, navigation, and designs are imparted according to the particular business preferences. The exact development cost of AI app development can be determined only after a thorough requirement assessment. So, it is a better approach to have an understanding of the factors affecting AI app development cost. Here are the core components that fluctuate the overall pricing of the AI app development project-

• Model complexity and size
• Training data
• Computational resources
• Talent acquisition
• Language and translation capabilities
• Real-time Processing
• API integration and management
• Security and compliance
• Scalability and maintenance
• Licensing and legal fees

The following are the three different types of AI apps that come with different cost brackets.

1. Basic AI Mobile App

The basic AI mobile is the functional software that can execute the different tasks based on the AI model and trained data. It can include a chatbot, recommendation system, predictive analysis software, AI agent, etc.

Estimated Development Cost- $40,000 – $100,000

2. MVP AI app

MVP stands for Minimum Viable Product, which is an advanced prototype of an AI solution. It allows the businesses to test and analyze the software performance by having real-time users using the app.

Estimated Development Cost- $30,000- $80,000

3. Full-fledged AI App

This is an advanced AI solution with complex technology integration. The full-fledged AI apps come with deep learning capabilities, real-time data processing, seamless API integration, and much more.

Estimated Development Cost- $100,000- $300,000

AI App Development Challenges and Mitigations

Creating an AI app can help your business gain competitive advantages while providing a personalized experience to the customers. However, the AI development process consists of a lot of challenges that can potentially affect the overall outcome quality. Thus, it becomes important to know these challenges along with the mitigation strategies that can help to overcome these challenges.

Here are some of the core AI app development challenges and their mitigation strategies-

1. Data Privacy & Security Risks

AI apps are trained on the huge dataset and thus contain a lot of confidential information about clients and customers. The mishandling of this data ultimately leads to security risks like unauthorized access and non-compliance with regulations.
Mitigation Strategy– To mitigate the risk of data privacy and security concerns, strategies like data encryption using AES and TLS are used. Also, data masking is deployed to remove personally identifiable information before further processing of AI models. Access control is another heavily used method to restrict data access.

2. Bias in AI Models

There are huge chances that the final AI solution can provide biased results and answers, which can lead to inaccurate and unfair output. The major reason for this challenge is an imbalanced dataset and no diversity of information used to train the AI model.
Mitigation Strategy: The diverse data is used to train the AI models. Bias audits are a helpful method that regularly analyzes the model performance and makes the corrections. Fairness techniques like re-sampling and algorithmic adjustments are carried out.

3. Computational Costs

The AI app development requires a lot of computational resources. Thus, it becomes very expensive to train the AI model on high-performing GPUs. This challenge affects a lot of businesses’ financial capabilities to use AI for their growth.
Mitigation Strategy: The model compression techniques like pruning and quantization are used to reduce the computational load. At the same time, cloud-based AI platforms like AWS, Azure, and Google Cloud are for scalable AI computing. Efficient training is another method that reduces training time and ultimately controls the overall cost.

4. AI Model Accuracy Issues

Other than the bias, the inaccuracy of the AI model is also a prominent issue that may lead to inaccurate results. This challenge directly impacts the reliability and trust of users on the results generated by the AI model.
Mitigation Strategy: It is ensured that all the datasets used for the training of the AI model are clean and well-labeled. Model parameter techniques like grid search and Bayesian optimization are carried out. The overall AI solution is tested through an A/B quality analysis process.

Future Trends: What’s Next for AI App Development?

There is no doubt that we have come a long way in exploring and leveraging artificial intelligence use cases. However, there is no denying that the future is ready to uncover many more amazing innovations that will transform the entire landscape. As a leading AI app development company, our experts have identified some of the key areas in AI where we can expect the utmost advancements shortly.

1. Generative AI Reshaping Businesses

In the current scenario, there are very few businesses that are leveraging the power of generative AI. However, it is anticipated that the capabilities of generative AI will increase in the future, which will help the firms automate many more tasks without deep expertise. For example, generative AI might be the first point of contact for most businesses, and customers won’t need to interact with human customer support for their queries.

Moreover, generative AI will play a core role in strengthening the online presence of brands by producing regular and unique content to connect with customers. The new updates in the AI might include tone and emotion adjustments so that the content can better understand and relate to the target audience.

2. No-Code AI Builders

App and software development require an understanding of programming languages, frameworks, and technology stacks. There is no denying the truth that AI software like ChatGPT is capable of writing the codes, but it can not be used to build the whole app with just a command.

However, we can expect the no-code AI builder, where the artificial intelligence will become smart enough to create basic apps and programs without human intervention. However, there will still be a need for developers and programmers to check the efficiency; the overall development process might become low-code or no-code.

3. AI + IoT integration

We all have witnessed the emergence of smart appliances that can sense the presence of people to take actions. It includes the automated adjustment of AC temperature according to several people in the room, light adjustment according to different times of the day, and much more.

The future might connect IoT technology to artificial intelligence, where the appliances will become even smarter so that manual commands will no longer be needed.

How Can the NineHertz Help You with AI App Development?

Artificial intelligence app development can undoubtedly take businesses to new heights by streamlining tasks and automating operations. However, it is most important that you hire an experienced AI app development company for your project, as the quality of the outcome heavily depends on your development partner.

The NineHertz is a leading AI app development agency with 16+ years of experience. We are a team of 250+ developers who carry excellent expertise in their area of expertise. Our team consists of industry experts who deeply understand the real-time challenges of different industry verticals and build an AI solution that synchronizes the business and user needs.

• Our years of experience enable us to save costs without affecting the overall project and app quality.
• We provide a free consultation to businesses looking for AI app development.
• The NineHertz ensures that the AI app is scalable so that it can provide a seamless experience to the increasing users on the app.
• We offer the best maintenance and support services to our clients, which promises the excellent performance of the AI mobile app for a longer duration.
• A Non-Disclosure Agreement is kept at the top of our development process that ensures the security and privacy of the entire project data.

Conclusion: Build an AI App

It can be concluded that investing in AI app development can be one of the best decisions for a business. Creating an AI app not only provides a competitive edge but also automates repetitive tasks for increased operational productivity. Talking about the development process, it includes brainstorming, data collection and preparation, AI model fine-tuning, seamless integration, and much more. So, it becomes important to have involvement of an experienced AI development team for a seamless execution of the project.

Frequently Asked Questions (FAQs)

1. How long does it take to build an AI app?

The timeline of AI app development ranges from 8 to 12 months. However, the exact development time depends on numerous factors like-

• UI design
• Hiring Model
• Team composition
• Size of dataset
• Platform of development
• Security implementation
• Communication between the stakeholders

2. What’s the best AI framework for AI app development?

TensorFlow, Keras, Apache Mahout, and PyTorch are considered as the best frameworks of AI app development. These frameworks help to build the advanced AI solutions that can be customized to perform different types of tasks according to the particular business needs. At the same time, the large community of these frameworks makes it easier to implement changes, launch updates, and ensure maintenance.

3. How to build an AI app from scratch?

Building an AI app from scratch is a time-consuming process as it comprises different stages and phases of development. Here is a glance at the ideal AI app development process-

• Problem Identification
• Data Preparation
• Selecting the Right Tools and Frameworks
• Fine-Tuning the AI Model
• AI Model Integration into the App
• AI Model Testing
• Deployment and Monitoring
• Maintenance and Updates

4. How much does it cost to build an AI app?

Generally, the cost of AI app development ranges between $30,000 and $500,000. However, the exact development cost depends on multiple factors like-

• Complexity of AI model
• Complexity of AI app
• Dataset required for training
• Third-party and API integration
• Maintenance schedule
• Platform of AI app development
• Designing the app
• Location of developers
• Features of the AI app