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HiTech
15 minutes read

How to Create an AI App

By Jonathan Tarud
A face, half android, half human.
By Jonathan Tarud
HiTech
15 minutes read

AI app development has captured the imagination of businesses and consumers as the power of the impressive natural language processing and generative AI application ChatGPT has been demonstrated. Now nearly every business is seemingly building AI mobile apps or adding AI algorithms to their existing mobile apps.

You’ve probably heard that Artificial Intelligence (AI) is the next big thing for finance, healthcare, and a number of other industries. This HiTech technology will help shape the future for one reason: when it comes to developing and implementing great features for apps, few things are as powerful as AI. 

AI has the power to generate content and automate repetitive tasks, saving time and money, but most importantly, it can help improve an app’s User Experience in a number of ways.

Machine Learning and AI models are proven to drive customer satisfaction, which has many businesses scrambling to build AI-powered apps. The most efficient way to build AI apps is to partner with an AI app development company.

However, organizations with their own mobile app development resources might be interested in what it takes to successfully build an AI-powered mobile application.

In this post we explain how to build an AI app from a business perspective, the basics that you need to know, and how to implement Artificial Intelligence into your app.

How to Get Started with AI for Your App

Like with any other subject, the first thing you should do when starting with Artificial Intelligence is to establish a clear conceptual framework and a list of important references.

Machine Learning and AI is a constantly evolving field that moves pretty fast. What goes on today might be very different from what happened two years ago, and although this sounds demotivating, it is actually the opposite.

With each new step, new opportunities arise, and this is very good but also very challenging for your tech stack and app if you want to stay relevant with modern standards and consumer expectations.

For businesses, it is very important to understand where the field is moving and where it will most likely move in the near future. For example, computer vision is an emerging tool in AI app development, whereas speech recognition is a well-established and widely used AI solution.

Also, it is important to have strong app development resilient teams that can easily adapt to new environments. When you have an understanding of what the future of AI app development will look like, your team can position itself appropriately and take the time to learn new programming languages and data science skills.

Lastly, having a clear goal of how you will implement AI platforms and solutions is essential. Having an AI-powered app will do your business little good if you don’t have a clear business strategy for utilizing the technology.

Stay Informed and up to Date

AI’s dynamism makes it a fascinating field of study, but one that nonetheless requires being up to date with the latest advances. When it comes to app development, this becomes particularly true.

It is best to implement the latest AI technology in your app. That way, your app’s User Experience will stand out, engaging users and leaving competitors behind. Using inadequate and outdated technologies can bring long term undesired effects like burdensome legacy systems. 

Take the example of Natural Language Processing (NLP), a promising field of AI that, in short, tries to make sense of human language. In the past couple of years, advances like transformers and generative AI apps like ChatGPT have changed the rules of the game in unexpected ways.

These tools are just being explored, but their potential applications look promising, so much that they can make some well-established technologies outdated and even change the trajectory of human history and language.

Natural Language Processing is the current obsession in AI, but AI development is also pursuing more advanced neural networks and image recognition capabilities that can achieve near-human intelligence.

While AI application development is not capable of true computer vision or general intelligence yet, Artificial Intelligence apps are moving rapidly from simple AI apps to advanced AI solutions. As innovative AI technologies emerge it is vital for your business to stay informed of the latest advancements.

Build Resilient Teams

We can safely expect disruptive inventions to become the norm instead of rarities. As a result, it is important for your organization to be able to easily iterate towards new technologies each time a new breakthrough occurs. This can only be done with the right people.

Having a team of technologists is a great way to get involved with AI. Whether you decide to do this through a third party or in-house personnel, your AI team should be able to address your company’s specific needs.

Prepare your team to adapt to new technologies when the time comes, and most importantly, make it easy for them to implement new processes. Sometimes the greatest threat to implement new technologies comes from within companies, not from outside.

Mobile app development technologies are always evolving. However, AI app development is evolving at a faster rate. As a result, having a flexible development process and team that is able to adapt to the latest Artificial Intelligence innovations and technologies is critical.

The Agile development methodology can help your business instill a flexible mobile app development process that prioritizes innovation and efficiency. With a resilient development team and process, your organization can pivot quickly and build an AI app that utilizes the latest innovations.

Have a Clear Goal

Keep in mind the nature of your company when implementing new technologies. It is common for companies wanting to implement AI into their processes to see themselves as an AI company. This is a common mistake you probably want to avoid. 

In practice, an AI company is strictly involved in activities like research and development associated with AI. Most other companies will only be casual adopters of AI; your company will most likely fit in this category.

Just like having a website does not make you an internet company, having AI implemented into your app does not make you an AI company. Artificial Intelligence and Machine Learning are technical data science fields. You don’t need to be an AI company to develop and use an AI app.

When building mobile apps or developing new business processes and strategies, it is vital to have a clear goal. This doesn’t mean your goals are fixed and cannot change as you learn more, but it is valuable to have a guiding objective.

If your organization wants to successfully build an AI app, it is important to have a clear objective and understand how your business will use this technology to improve business processes and operations. Blindly pursuing AI app development can lead to wasted resources and frustration.

The Fundamentals of Artificial Intelligence

To stay up to date successfully with this fast-moving field of computer science, it is probably best to start by understanding the theoretical principles and fundamentals behind AI.

To do that, we strongly recommend you check out this course by Andrew Ng, one of the world’s leading experts in terms of AI, and founder of deeplearning.ai, one of the most important organizations in terms of spreading Artificial Intelligence literacy. 

Below we have provided foundational information required to understand Artificial Intelligence. It is critical to understand the terms and technologies before you begin pursuing development so that your business fully understands what it is building and what it can accomplish.

What Is AI?

There are many misconceptions about what AI is or isn’t. For a start, it is important to understand that there are two general types of AI:

  • Artificial Narrow Intelligence: This is often referred to as a one-trick pony because it is designed to perform specific tasks. This is what most AI applications look like. 
  • Artificial General Intelligence: This is what we usually think of when we think about AI. In this form, the technology can do anything a human can. There is still a long road ahead before we get there.
  • Artificial Super Intelligence: This is often portrayed in science fiction and horror stories that involve Artificial Intelligence. Artificial Super Intelligence is fully sentient technology that can do anything a human can do and surpass it. Popular representations of AI like Terminators or HAL are examples of Artificial Super Intelligence.

Artificial General Intelligence does not exist yet, and there is significant debate among technologists, philosophers, neural doctors, etc., about whether Artificial General or Super Intelligence can even be achieved.

We know more about outer space than we do about the human brain or how its produces consciousness. As a result, many theorists argue that it will be nearly impossible to create a fully sentient computer program since we don’t understand our own sentience.

However, Artificial Narrow Intelligence is more than capable of producing incredible results in a variety of fields. ChatGPT and other generative AI apps have already begun impacting our society in significant ways.

Generative AI will continue to improve and has even begun to mimic a sort of Artificial General Intelligence. However, while the latest Generative Artificial Intelligence is impressive, it is important to remember that these tools are not flawless and not sentient.

ChatGPT and other similar generative AI tools are highly sophisticated Machine Learning algorithms.

If you want to implement AI into your business processes, make sure to train your team properly. Also, align your strategy with what you plan to do, both in terms of business and technology. Nonetheless, keep an open mind and give yourself some space to experiment. 

AI and Data

Artificial Intelligence, in all of its forms, uses vast amounts of data. That’s why one of the most important things you need to do is implement a secure data pipeline and DevOps best practices.

By doing so, you will be able to collect, store, manage and analyze data so that it can later be used as an input for your AI systems; a great AI idea without the correct data will work poorly.

Managing user data can be tricky, so make sure to always comply with regulations, and most importantly, make your users feel that they can trust you. Respecting their privacy and giving them the proper privacy guarantees is a must.

In addition to user privacy, companies like OpenAI and others are beginning to face legal scrutiny regarding the data used for training. Several artists, including comedian Sarah Silverman, argue that companies like OpenAI used their intellectual property in their training data without permission or proper compensation.

Data usage will be a major point of contention moving forward, especially when it comes to generative AI. Creators argue that these tools are not generating anything unique, but rather taking their work and rewording it.

These cases will be litigated in the coming years, but if your organization is building a generative AI app make sure that you have the right to use the training data required to build an effective AI-powered application.

What Is Required to Build an AI System for Your App

Nowadays, it is possible for all sorts of companies to build world-class digital products. Thanks to cloud computing technologies, any business can access state of the art computing resources for their apps. This makes it possible to build digital products in a fast way, update them easily, and scale when needed. 

These are the most important things you should consider in order to build a powerful AI software system for your company.

  • Development Team: More important than specific expertise for your team is having the will to learn. Since this field is constantly evolving, being able to learn and unlearn becomes an essential skill for your AI app developers.
  • Technological Tools: Tools like TensorFlow and PyTorch can help you build powerful AI projects based on Machine Learning and Deep Learning. Some tools are open source and have great documentation.
  • AI Strategy: Don’t just follow a trend. Set clearly defined goals and address specific issues that can be easily upgraded in time. Take the time to understand how your company can benefit from AI.
  • Data Pipeline: Without proper data, your AI will lack power. Make sure to review every aspect of your data, from how it is collected to what it will be used for. 

These are the vital aspects of AI development. Luckily for organizations and app developers, there are several robust, open-source AI SDKs and frameworks that can be utilized to build an AI app efficiently.

How to Create an AI from Scratch

If you are literally just starting from scratch to build an AI feature for your app, make sure to perform some good old brainstorm sessions. They are a great way to organize your ideas and see what opportunities may lie ahead.

Rather than doing a leap of faith into the unknown, involve your team members in ideation workshops that can help sketch out a clear idea of what the company needs. 

Onboarding all teams, sharing ideas, concerns, and potential opportunities is a great way to start. Vocalize what needs to be achieved and make collaboration possible across teams. Don’t approach this as a siloed project, but rather as something that is strategic for the company. 

Most companies do not have the local resources to develop AI tools. There’s no need to worry if this is your case. Luckily, companies like Koombea can help you develop the right HiTech tools and configure your IT infrastructure. 

How to Make an AI Robot

There’s recently been a lot of buzz regarding robots and how they can help companies increase their productivity. The main difficulty in doing so is acquiring the robots. They represent an important expense that, even with increased productivity, is hard for many companies to afford. 

A great solution to this is hiring them under a Robots as a Service (RaaS) scheme. However, keep in mind that, even under this solution, you will need a development team that can help you implement the robots into your processes. 

Which Programming Language is Best for AI App Development?

Organizations that want to build an AI app will be eager to learn which programming language is the best for this type of app development project. There are several popular programming languages that are used to build AI mobile apps.

The top languages used to build AI applications include:

  • Python
  • Rust
  • R
  • C++
  • Java
  • Haskell
  • Prolog
  • Lisp
  • Smalltalk

Of course there are other languages that could be used, but the languages listed above are the most capable for these types of development projects. Furthermore, each language has its own strengths and weaknesses.

The most effective way to choose a programming language for your project is to fully understand your development needs and business objectives. Once you understand these, your development team can fully evaluate each language and see which one is the most aligned with business objectives.

Additionally, if your development team has a strong preference in language, this language will likely be the best for your project. For example, if your developers are highly skilled and proficient with Java, it makes sense to use this language instead of trying to hire new developers or teach your team a new language.

How Much Does AI Development Cost?

It is impossible to accurately estimate the cost of an AI app development project without knowing the specific details. However, the most significant factor affecting the cost of development is complexity. The more complex a project, the more expensive it will be.

For example, a simple AI app with limited features and functionality is far cheaper to develop than a feature-rich product. Additionally, type of development affects costs as well. For example, native app development is typically more expensive than cross-platform development.

Not only do you have to build two separate native apps to reach both mobile platforms, but native app development is more specialized, which means the labor is more expensive. These are the most significant cost factors businesses will have to contend with.

Costs will also be affected by the location of the developers. For example, on-shore developers cost more on average than near-shore developers, who in turn cost more than off-shore developers. There are several outsourcing models that can affect costs, and it is important to fully consider them before making a final decision.

Final Thoughts: How to Develop AI Applications

There is no single way to develop an AI application for your business. The best way is to have a team of experienced developers who can understand your needs and translate them into feasible and viable solutions that are built with human-centered design principles in mind. 

The field of Artificial Intelligence is constantly evolving and implementing it into your app will require specialized knowledge and skills. At Koombea we’ve been helping our clients implement powerful AI-based features into their apps. This has allowed them to increase their productivity while at the same time making their processes more efficient.

If you’d like to know more about how we can help you implement Artificial Intelligence HiTech features into your app, contact us for a free consultation.

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