How Much Does AI App Development Cost? Here’s the Answer!

AI apps, like chatbots or virtual assistants, offer a lot of possibilities for your business.

They may improve customer experience and optimize your business operations.

However, you might wonder: how much will it cost to build an AI app?

By knowing the app development costs, you can determine the feasibility of your app development project.

That’s why this article will unveil them for you.

Let’s get started!

An AI app, or Artificial Intelligence application, is a software program that uses artificial intelligence to perform specific tasks.

These tasks can range from simple interactions to complex decision-making, all designed to enhance user experience, improve efficiency, or automate processes.

Here are some examples of AI apps you might already be using:

• Virtual Assistants: AI-powered virtual assistants like Siri or Google Assistant can answer your questions, set reminders, or control smart home devices through voice commands.
• Ride-Sharing Apps: Apps like Uber use AI for real-time traffic analysis, route optimization, and dynamic pricing to ensure a smooth ride experience.
• Music Streaming Services: The recommendations you see for new songs or artists on music streaming platforms like Spotify are powered by AI algorithms

What Is the Typical Cost to Build an AI App?

Developing an AI app can range anywhere from $30,000 to over $150,000. This number can be influenced by various factors, primarily the app’s complexity.

• Basic AI App ($30,000 – $60,000): For instance, simple chatbots with limited functionality or basic recommendation engines. The development time for these apps would be shorter and require a smaller team.
• Average AI App ($60,000 – $150,000): For example, apps with advanced features like AI-powered image recognition or chatbots with natural language processing capabilities. Usually, the development time and team size will increase accordingly.
• Complex AI App ($150,000+): This includes applications with deep learning models or real-time machine learning capabilities. So you need to expect a significant investment in development time and a larger team with specialized skills.

But remember, these are estimated ranges, and the actual cost for your specific app may vary depending on its functionality.

What Factors Influence the Cost of Building an AI App?

The cost of mobile app development depends on lots of factors.

Here’s a breakdown of the key elements that can shape your AI app development budget:

1. Complexity of the AI Model

Simpler AI models like basic chatbots will require less data and development time, which might lead to lower costs.

Conversely, complex models with deep learning features like image recognition or Natural Language Processing (NLP) will require more significant resources.

For example, a basic AI-powered shopping assistant that recommends products based on purchase history might cost $30,000 to develop.

In contrast, an AI-powered medical diagnosis tool that analyzes complex medical data could cost more than $100,000.

2. Quality and Volume of Training Data

AI models learn and improve based on the data they’re fed.

That’s why high-quality data in large volumes is crucial for their optimal performance.

However, acquiring and cleaning such data can be expensive.

A research by HubSpot found that, on average, machine learning projects need around 100,000 data samples to perform well.

And to get high quality training data sets, you need to spend $10,000 to $85,000.

If your AI app relies on publicly available datasets, the data costs might be minimal.

However, if your app requires specialized medical data that needs to be anonymized and prepared thoroughly, it can add a significant sum to your budget.

3. Development Team Expertise

Building an AI app requires a specific skill set.

So, prepare more budgets for hiring an experienced AI developer team.

The cost might also vary based on the team’s experiences and location.

For instance, the median base salary of AI engineers in the United States is $108,043.

At first, hiring a team of freelance developers in a region with lower development costs might seem appealing.

However, if they lack specific AI expertise, you might encounter issues later that potentially increase costs.

Therefore, pick your development team wisely.

4. App Features

The more features your AI app offers, the more development time and resources it will require.

A simple app with core AI features will be less expensive than the one with a complex user interface or multiple integrations.

For example, a basic chatbot app with text-based interactions might be relatively inexpensive to develop.

However, if you want a chatbot that can also understand and respond to voice commands and integrate with your customer support system, the development cost will obviously increase.

5. Deployment and Maintenance

The journey doesn’t end after the development phase is done.

Deploying your AI app on a cloud platform or your own servers will also add to the overall cost.

Additionally, ongoing maintenance and updates are needed to ensure smooth operation and improve the AI model’s performance over time.

In this case, choosing a cloud-based deployment option might be more cost-effective initially than setting up your own infrastructure.

Also, don’t forget to allocate a budget for regular maintenance tasks and potential model retraining to keep your AI app at its best.

How Long Does It Take To Build an AI App?

The development timeline for an AI app can vary significantly depending on the complexity of the project:

• Simple AI Apps (1-3 Months): These apps will only need basic AI functionalities. So, with less data, development time, and resources, they only need a shorter time to build.
• Medium Complexity AI Apps (3-6 Months): These apps will use more advanced AI features Therefore, they usually require a larger amount of data and development effort compared to simple apps.
• Complex AI Apps (12+ Months): Highly sophisticated AI applications, like self-driving car systems fall into this category. They involve massive datasets and intricate AI models, which leads to longer development timelines.

How to Successfully Grow Your AI App?

Developing your AI app is just the first step.

Here’s how to ensure it grows well in the long run:

1. Start with a Minimum Viable Product (MVP)

An MVP is a stripped-down version of your app that focuses on the core functionalities.

So, you can spend time testing the concept with real users and gather valuable feedback.

It is generally less expensive to develop, and helps you validate your app’s market potential before investing in more advanced features.

2. Use Pre-Trained AI Models and Open-Source Tools

There are pre-trained AI models for various tasks, like image recognition or natural language processing.

These models can be a great starting point, which can save you time and resources in developing your own model from scratch.

Moreover, many open-source AI libraries (like AutoGPT) can be used to streamline development.

3. Consider a Cross-Platform Development Approach

Instead of developing separate apps for iOS and Android, use a cross-platform development approach that allows you to build a single codebase that can be deployed on both platforms.

This approach can save time and resources compared to developing native apps for each platform.

4. Outsource Strategically

Outsourcing specific development tasks to freelancers or an app development agency can be a cost-effective strategy as well.

This allows you to tap into specialized skills without having to build an in-house AI development team.

However, careful selection and clear communication are important for building a successful partnership.

What Are the Risks and Challenges of Building an AI App?

While AI offers immense possibilities, building an AI app isn’t without its challenges.

Here are some key areas you need to be aware of:

• Data Quality and Bias: AI models are only as good as the data they’re trained on. Biased or inaccurate data can lead to biased and unreliable app behavior. So, ensuring high-quality and unbiased data collection is crucial.
• Data Availability: Complex AI models often require vast amounts of data for training. Depending on your project, acquiring and managing this data can be expensive and time-consuming.
• Technical Expertise: Building AI apps requires specialized skills in AI development, machine learning, and data science. Finding and assembling the right development team can be challenging.
• Privacy Concerns: AI apps that collect and analyze user data raise privacy concerns. Therefore, it’s essential to implement security measures and ensure user data is handled responsibly according to data privacy regulations.