AI App Development Guide to Build an AI App in 2023

Updated Time : January 22, 2024
AI App Development

Table of Contents

If you’re an entrepreneur stepping into the world of AI app development for the first time, you’re probably seeking straightforward and beginner-friendly guidance.

You’ve landed in the right place.

This blog hosts a detailed guide to AI app development personalized just for beginners like you.

Grasp the fundamentals of AI app development by reading this blog and transform your app idea into a powerful tool that stands out in the market.

What is AI App Development?

AI app development is the process of creating mobile or computer applications that use artificial intelligence (AI) to perform smart tasks. 

It involves programming software to learn from data, recognize patterns, and make decisions like a human. 

These apps can do things like speech recognition, image analysis, personal recommendations, and more. 

AI app development combines traditional coding with AI algorithms to make apps that can understand, adapt, and make predictions, providing users with more personalized and efficient experiences. 

If you have an app idea but don’t know where to start, our guide on building custom apps can provide valuable insights and assistance. 

AI’s Rising Influence in the Mobile App Market

Artificial Intelligence (AI) has been making waves in the tech world in recent years, and it’s not slowing down. 

By 2030, the global AI market is predicted to hit a staggering $2 trillion. That’s a massive leap, considering how new this tech is.

But here’s the twist: AI isn’t the only one on the rise. The global mobile app industry is booming too, and it’s expected to rake in over $755 billion in revenues by 2027. 

So, it’s no wonder that AI and mobile apps are teaming up.

The following graph shows how the global market size of AI app development is rising rapidly every year.

how the global market size of AI app development is rising rapidly every year

Differences Between Traditional Apps and AI Apps

Applications, or apps, are integral to our digital lives. We use them for various tasks, from chatting with friends to managing our finances. 

There’s a new wave of apps, called AI apps, which differ from the traditional ones. Wondering how? Look at the differences illustrated in the table below.

AspectTraditional AppsAI Apps
FunctionalityFixed, pre-defined actionsAdaptive based on data
LearningDo not learn over timeLearn from user data
Data UtilizationUse data for basic functionsUse data for predictions
ComplexityLess complex in operationsComplex due to algorithms
InteractivityStatic, based on codingDynamic, based on patterns

While traditional apps have been serving us efficiently for years, AI apps are rapidly gaining popularity due to their ability to adapt and learn. 

They offer more personalized and dynamic interactions, paving the way for smarter and more intuitive digital experiences. 

Benefits of AI Apps for Businesses

So, you’re thinking about investing in AI app development for your business, but what’s in it for you? Well, AI apps can bring a multitude of advantages to your company. 

Let’s break these benefits down in simple terms:

  • Time and Cost Savings: AI apps automate repetitive tasks and processes. This means you save time and money by reducing the need for manual labor.
  • Improved Productivity: With routine tasks automated, your employees can focus on more creative and strategic activities, making your business more efficient.
  • Informed Decision-Making: AI and Machine Learning provide data-driven insights, helping you make better, faster decisions in your business operations.
  • Error Prevention: AI apps are reliable and consistent, reducing the risk of human error, which can be costly and time-consuming.
  • Accurate Predictions: AI can analyze data to make highly accurate predictions about risks, benefits, and trends, guiding your business in the right direction.
  • Discovering New Opportunities: AI apps can help identify new sales channels and opportunities you might have missed otherwise.

When considering building an AI app, remember that it’s a game-changer for your business. 

8-Step Guide to Building a Successful AI App

AI is shaping the future, and you can be part of this exciting journey. Whether you’re a researcher, a business owner, or simply intrigued by AI, this guide will help you understand the process of crafting your AI app. 

Here, we’ll walk you through the key steps to bring your AI-powered dream to life.

8 Steps to Follow for Building a Successful AI App

Step 1: Identifying the Problem

To begin making an AI app, the first step is figuring out what issue you want to solve. 

Think about how your app works and what you want the AI to do. What do you want it to achieve, and how will it be helpful? 

Once you’ve got your problem and idea, you can start creating a list of what your app needs. This list will help developers understand what they need to do and what tools they need.

During this planning stage, you should also:

  • Decide who you need on your team, both people who know the technical stuff and those who don’t. This might include project managers, business analysts, backend programmers, etc.
  • Talk to the experts about when the work will happen and how long it will take.
  • Start looking for the data you’ll need to train your AI or machine learning model.

Step 2: Preparing Your Data

AI-powered apps rely on data to work. But before using the data, it needs to be collected and prepared in the right way to make a good data model. 

Experts in AI, especially in machine learning, can help with this. They go through the collected data carefully. They often use a process called CRISP-DM, which is like a set of rules for working with data.

The next step is making sure the data is right. This means checking for mistakes, things that are missing, or labels that are wrong. 

This involves steps like:

  • Getting the original data and choosing the parts you need.
  • Picking tools to help with labeling.
  • Labeling and marking the data.
  • Choosing the processed data and saving it in a file.

Once you have the data, you can start comparing different solutions and move on to the modeling part. You use the data you collected to train the machine learning model in different ways.

Step 3: Choosing the Right Algorithm

Selecting the right algorithm is the heart of your AI system. Two main learning types are supervised and unsupervised. 

In supervised learning, you provide a labeled dataset for the machine to train on, while unsupervised learning involves grouping and finding connections between data points. 

Choose your algorithm wisely, ensuring it fits your specific task correctly.

Step 4: Training Your Algorithm

Once you’ve chosen the right method for your AI, the next big step is making sure it learns properly. 

While there’s no fixed rule for how accurate it should be, it’s vital to train and retrain it until it works well within the chosen guidelines.

AI systems rely heavily on data, so the quality and variety of data used for training are crucial.

Investing time and effort in this training process pays off – it leads to better efficiency, cost savings, and a competitive edge in the long run.

Step 5: Selecting the Right Programming Language

To create a successful AI system, you need clear requirements and the right choice of technology and programming language. 

There are several programming languages available, each with its own strengths and weaknesses. Your choice depends on your project’s specific needs. 

Some are great at handling big data, while others are excellent for natural language tasks. To pick the best language for your AI app, you should understand what each language does best. 

Step 6: Platform Selection

When you’re building an AI app, you often use various tools like frameworks and APIs to create intelligent algorithms. 

These tools come with built-in features for things like deep learning, neural networks, and understanding human language. 

Most big cloud platforms offer these tools, making it easy to use pre-made solutions for tasks like recognizing speech, images, and text and handling complex machine learning.

Here are the key things to think about when choosing these tools:

  • Pick the right cloud platform, like a hybrid cloud setup.
  • Consider where your data will be stored and who owns it.
  • Check if the tools work with the programming language you’re using.
  • Make sure the tools are available in the region you need.
  • Think about the costs involved throughout the AI development process.

Step 7: Final Development

Building an AI-powered software app is like making any other app, with a few differences. Here are the main steps:

  • Plan how the app will work.
  • Design how users will interact with it.
  • Create the parts users see and the behind-the-scenes parts.

While you’re making it, you can make it work better, add more features, and get it ready for updates.

Step 8: Testing, Deployment, and Monitoring

Testing your AI app is a crucial part of the process. QA engineers will ensure it functions as expected before deployment. 

After launch, regular maintenance is vital to keep your algorithm accurate and up-to-date. This includes data updates, security patches, and version changes.

Building an AI app is a thrilling journey. With the right guidance and understanding of these key steps, you can create a transformative AI system that makes a difference in your industry.

How Much Does It Cost to Make an AI App?

Generally, building AI software starts at $10,000. But most of the time, it falls somewhere between $30,000 and $100,000. The more complex your app, the higher the cost.

Let’s look into the details.

Factors that Affect the Cost

The price tag of creating an AI app isn’t set in stone. 

It depends on several things, like what features you want, how complicated your app is, the tech tools you use, and how many people are working on it.

Types of AI Apps

First off, there are different types of AI apps, from simple ones like chatbots to complex systems for analyzing big data in a company. 

The budget for these can be quite different.

Time and Team

Here’s a rough idea of how long it takes to build an AI app:

  • Simple AI App: About 3 months
  • Complex AI App: Double that time, so around 6 months

The image below will help you have a more detailed idea about the time different roles involved in the ai development process take to accomplish their targets.

Time Needed to build an ai based mobile app

Maintenance Costs

Even after your app is up and running, you’ll need to spend around 30% of the initial budget in the first year to support and update it. 

After that, it’ll be about 15-25% per year. So, it’s not a one-time cost; you have to keep it going.

Creating an AI app is like investing in a smart helper. It makes things easier and more convenient for users. Yes, it costs money, but it’s an investment in the future. 

Choosing the Right Tools for AI-Based Apps

When it comes to building AI-powered apps, the choice of technology is crucial. 

So, let’s explore the tech stack for creating these smart applications. It’s not as complicated as it sounds; we’ll break it down for you.

Programming Languages, AI Platforms, and Libraries

Here, we have listed the programming languages, libraries, and AI platforms you would need to develop an AI app.

  • Python, Java, C++: These are like the building blocks of AI apps. They give the app its foundation. Think of them as the base of a house.
  • C#, R, or Prolog: Sometimes, developers use these too. It’s like adding some special features to your house, making it unique.

To save time and money, developers use AI and Machine Learning platforms. Here are some popular ones:

  • Google TensorFlow: This is like a super-smart toolbox. It helps developers build AI projects from start to finish. It’s flexible and can work on different devices.
  • Microsoft Azure: It offers lots of tools and can understand many languages. It’s like having a multi-language dictionary for your app.
  • Amazon AWS: This helps create, train, and launch complex AI apps. It’s a bit like having a super-fast computer for your app.

And there are more, like IBM Watson, Oracle AI cloud services, and others. They’re like different flavors of ice cream – you choose the one you like.

Frameworks and Application Programming Interfaces (APIs)

Frameworks and APIs are like shortcuts to building smart features. They make it easier and quicker. Some popular ones are:

  • Microsoft Cognitive Toolkit (CNTK): This is like a recipe book for AI. It helps developers create different AI models.
  • AWS Machine Learning: It’s like a connection between your app and the cloud. It helps make predictions.
  • PyTorch: Think of this like Lego blocks. It helps developers build complex systems quickly.
  • Core ML/Create ML: These are great for Apple devices. They help make apps smarter on iPhones and iPads.

And there are more, like Caffe2, Keras, Accord.NET, and others. They’re like different tools in a toolbox, helping developers create unique and smart features for your app.

5 Use Cases of AI in Mobile Apps

Ever wondered how your smartphone seems so smart? A big part of that intelligence comes from the wonders of artificial intelligence (AI). 

From chatbots that answer your questions to security features that protect your data, AI is revolutionizing the mobile app experience. 

Let’s identify some of the standout uses of AI in mobile applications.

5 Use Cases of AI in Mobile Apps

1. Chat Automation

Ever felt frustrated waiting for a human agent to answer your questions? AI chatbots are here to help. 

They use natural language processing, meaning they understand and respond to human language.

Features

  • Quick response time
  • 24/7 availability
  • Cost-efficient

Did you know? Chatbots are saving companies a lot of money. According to Gartner, by 2026, chatbots might help cut labor costs in contact centers by a whopping $80 billion.

2. Digital Assistance

Imagine controlling your app just by talking to it. Virtual assistants like Siri or Google Assistant let you do that. They use voice recognition to understand and act on your commands.

Features

  • Hands-free interaction
  • Voice command execution
  • Accessibility for differently-abled users

Thinking of sales or customer support? AI can also guide your team with real-time dialogue suggestions, making every interaction smoother and more effective.

3. Security

Everyone’s concerned about security, especially in apps where personal and financial details are stored. AI can give that extra layer of protection.

Features

  • Quick threat detection
  • Improved biometric authentication
  • Continuous learning from past security threats

With AI, not only can you detect potential threats but also prevent them, ensuring your users feel safe and secure.

4. Predictive Analytics

Ever wished you could predict the future? With AI, at least in terms of user behavior and market trends, you can. AI analyzes past data and gives insights into what might happen next.

Features

  • Future trend analysis
  • User behavior prediction
  • Accurate demand forecasts

With these insights, businesses can plan better and always stay one step ahead.

5. Object Detection

From photos to scans, AI can identify objects, people, and even anomalies.

Features

  • Quick image analysis
  • Risk assessment from photos
  • Accurate and fast diagnoses in healthcare

Whether it’s a doctor diagnosing a disease or an insurance agent assessing damage from a car crash, AI can make the process faster and more accurate.

From how we chat to how we shop, AI is reshaping our mobile app experiences. It’s not just about smart tech but about creating meaningful, personalized, and efficient interactions for every user. 

As the world of mobile apps continues to evolve, the fusion of AI promises a future of limitless possibilities. So, next time you use your favorite app, take a moment to appreciate the intelligence behind it. 

Industries Benefitting from Artificial Intelligence Applications

Artificial Intelligence (AI) is revolutionizing various sectors with its vast array of applications, making processes smarter and more efficient. 

Let’s discuss which industries are harnessing AI’s potential and how.

8 Industries That Are Benefitting from AI Applications

1. Finance

In the age of digital transactions, the finance sector faces escalating threats from identity theft and fraud. AI steps in with deep learning technologies to assess trends and detect potential fraud.

Did you know? Through a sophisticated deep learning system that evaluates transactions, PayPal managed to reduce its fraud rate to a mere 0.32% of revenue.

AI, particularly machine learning, is also reshaping the world of trading and investment management. The rise of AI-driven hedge funds and robo-advisory platforms is a testament to this transformation.

2. Automotive

The automotive industry is at the forefront of AI integration. Self-driving or autonomous vehicles have become the poster child for AI in this sector. 

These vehicles rely heavily on AI algorithms, sensors, and advanced mechanics to navigate, avoid collisions, and even park themselves.

According to a report from Statista, the market for fully autonomous vehicles is expected to reach a size of approximately $6 billion by 2025.

AI-driven predictive maintenance can alert drivers about potential issues before they become major problems, ensuring safer drives and reducing overall maintenance costs.

Don’t know where to start with AI in the automotive sector? Our article is your go-to source for insights.

3. Chatbots in Healthcare

Chatbots are becoming increasingly prevalent in many industries, but their impact on healthcare is particularly noteworthy. 

They offer instant responses to patient queries, help in booking appointments, and even provide preliminary diagnoses based on symptoms described by patients.

A report from Juniper Research projects that chatbots will be responsible for cost savings of over $8 billion annually by 2022, up from $20 million in 2017, particularly in the healthcare and banking sectors.

Are you crafting AI chatbots in your plans? Dive into our informative materials and kickstart your chatbot development now!

4. Education

AI in education is personalizing the learning experience. 

AI can adapt real-time content by analyzing students’ behaviors and performances, offering each individual a tailored learning pathway. This ensures that students receive instruction at their own pace and level.

According to eSchool News, 48% of educators believe AI will significantly impact the classroom by 2021.

Administrative tasks are also being automated, reducing the burden on educational institutions and allowing them to focus more on actual teaching and learning.

Looking to develop AI apps for education but unsure where to start? Explore our educational AI resources now!

5. Cybersecurity

As cybersecurity attacks escalate in complexity, businesses prioritize fortifying their security infrastructure. And here’s where AI shines!

So how does AI reshape cybersecurity? AI assists security experts in detecting network anomalies by analyzing patterns. 

Features like predictive analysis can preemptively identify malicious threats, and biometric login systems enhance security measures. 

Leading companies like Google and IBM are already harnessing AI to bolster their cybersecurity infrastructure.

6. Customer Experience

AI is redefining the customer experience. Predictive analytics allow businesses to understand consumer behavior better, ensuring timely and relevant engagement. 

Personalized recommendations, chatbots for 24/7 support, and virtual trial rooms in retail are just a few examples.

A Gartner prediction suggests that by 2025, customer service organizations that embed AI in their multichannel customer engagement platform will elevate operational efficiency by 25%.

Ready to discover the world of AI more? Then peep into AI’s role in customer experience with our informative article.

7. Logistics

Logistics firms are looking at AI to revolutionize various operations, from autonomous equipment to predictive analytics. 

According to McKinsey, incorporating AI in logistics could generate between $1.3-$2 trillion in annual economic value. 

Capabilities range from demand forecasting and autonomous vehicles to dynamic pricing and automated office tasks.

8. Personal Assistance

The rise of virtual personal assistants like Siri, Alexa, and Google Assistant showcases AI’s potential to make daily tasks easier. 

These assistants help manage tasks like setting reminders, playing music, or even controlling smart home devices based on user voice commands.

According to Voicebot.ai, as of early 2021, U.S. households had an estimated 126 million smart speakers (like Amazon Echo and Google Home).

Ready to revolutionize personal tasks with AI? Our resources on AI in personal assistance will pave the way!

AI’s imprint on various industries is profound and expansive. The spectrum of AI’s benefits is vast, from enhancing user experiences to optimizing backend processes. 

As we move forward, we can expect AI to be more deeply integrated, reshaping industries in ways we might not even envision yet. 

5 Examples of AI’s Potential in Mobile Apps

Whether you’re asking your phone for directions or getting recommendations for dinner, there’s a good chance AI is working behind the scenes. 

Here we will trace out some popular AI-powered mobile apps and understand their unique features.

5 Popular AI Apps in 2023

1. Siri

Apple’s Siri is more than just a voice on your device. 

This intelligent assistant, integrated across Apple’s vast product range, is designed to understand human language and carry out tasks seamlessly.

Features of Siri include –

  • Understanding and responding to human language.
  • Setting up reminders and answering queries.
  • Providing recommendations based on user preferences.
  • Sending text messages on voice command.

2. Cortana

Microsoft’s Cortana offers a personalized experience by using AI to provide reminders, answers, and recommendations tailored to the user.

Features of Cortana include –

  • Personalized recommendations.
  • Creating notes and managing calendars.
  • Continuous learning to improve user experience.

3. Google Assistant

Regarded as one of the most sophisticated virtual assistants, Google Assistant is accessible on a plethora of devices, making everyday tasks effortless.

Features of Google Assistant include –

  • Voice commands for various tasks.
  • Searching information swiftly.
  • Device control, from smartphones to smart fridges.

4. Alexa

Amazon’s Alexa isn’t just confined to Echo devices. Its versatility and range of functions showcase the advancements in AI-powered virtual assistants.

Features of Alexa include –

  • Answering questions in real-time.
  • Setting alarms and creating to-do lists.
  • Providing updates on weather, traffic, and news.

5. FaceApp

Facebook’s FaceApp leverages AI to let users play around with their images, enhancing their social media game.

Features of FaceApp include –

  • Advanced selfie editing.
  • AI-driven changes to photo appearances.

The infusion of AI in mobile apps is changing the way we interact with technology.

These apps, with their smart features, make our lives simpler and showcase the boundless possibilities of integrating AI into our digital experiences.

Wrapping Up

In a rapidly evolving digital landscape, AI app development stands at the forefront of innovation. 

With endless possibilities and transformative potential, AI-driven applications are set to reshape industries and enhance user experiences. 

As the future unfolds, harnessing the power of AI app development will be a key differentiator for businesses, making them more efficient, insightful, and competitive in the ever-expanding mobile app market. 

So dive into the AI revolution and unlock your app’s full potential today!

Picture of Shahria Emon

Shahria Emon

Emon, a blockchain enthusiast and software development expert, harnesses decentralized technologies to spur innovation. Committed to understanding customer needs and delivering bespoke solutions, he offers expert guidance in blockchain development. His track record in successful web3 projects showcases his adeptness in navigating the complex blockchain landscape.

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