How to Create an AI Software: A Step-by-step Guide

If you want to wow your customers by solving their problems, you should shift your gaze to AI software. AI-powered software can automate your business operations, improve decision-making, and help you achieve your business goals and objectives quickly.

AI applications are already being used to analyze customer behavior, predict sales trends, and automate marketing campaigns. From AI-powered content generation with chatbots like ChatGPT to AI-powered art and designs, each day open-source tech companies are constantly releasing new AI systems.

However, as a business, it is not an easy process, and you must be wondering how to create AI software for your business. To make this process easier for you, this AI software development guide will go through various aspects of AI, such as the benefits of developing AI software, challenges of building AI, and lastly, we will cover how to create an AI software with 6 simple steps and the cost of building AI.

What is AI Software?

AI (Artificial Intelligence) software is a computer program that mimics human behavior by learning various insights and data patterns.

AI software can have several features based on its training however the top features of AI software include machine learning (ML), speech and voice recognition, virtual assistants, and more.

From chatbots to generative AI and image generators, the use of AI technologies across various industries has propelled transformative advancements and unleashed a wave of innovation. By combining AI with machine learning users can get many benefits and make the business process a much simpler one.

AI software is used to develop an intelligent application from scratch with the help of other technologies such as machine learning and deep learning capabilities. With the help of AI software, developers can create smart systems that will not only help businesses but also help us at home. These smart systems can perform multiple tasks for us, right from setting our alarm to switching on/off the lights.

Additionally, AI can help us gather and collect data from different portals efficiently.

Types of AI Software

Before we jump into how to create an AI?, let’s first understand the different types of AI software.

There are many different types of AI software, each with its own specific purpose. Here are the most common types of AI software:

» Artificial Intelligence Platforms: This provides the platform for developing an application from scratch. Many built-in algorithms are provided in this.  The main feature of these platforms is drag and drop facility that makes it easy to use.

» Chatbots: This software will give the effect that a human or person is doing in a conversation.

» Deep Learning Software: Deep learning software uses artificial neural networks to learn from data. This software is able to learn complex patterns in data that would be difficult or impossible for traditional ML software to learn. It includes speech recognition, image recognition, etc.

» Machine Learning Software: Machine learning is the technique that will make the computer learn through data. This software is used in a wide variety of applications, such as fraud detection, customer segmentation, and product recommendations.

AI Operations and Applications

Today, building AI systems is becoming less complex and cheaper. The main thing to focus on when making AI software is collecting relevant data to train the AI model.

AI models are programs and algorithms that allow the AI to recognize specific patterns in large datasets.

The more carefully you build AI software, the more wisely it can analyze vast amounts of data to learn how to perform and respond to a particular task.

There are many real-world AI applications that individuals and businesses use, below are the most common examples of AI software in daily life:

⇒ Speech Recognition

It is also known as Automatic Speech Recognition (ASR), computer speech recognition, or speech-to-text is a type of AI application that allows computers to understand human speech. These systems can be used to convert spoken words into text, control devices with voice commands, and generate speech output.

This application commonly uses Natural Language Processing (NLP) to process human speech into written form. For example, Siri uses speech recognition to conduct voice searches.

⇒ Customer Service

Today, more companies are constantly considering using online virtual assistants for customer services than human representatives. According to the reports, 95% of all customer interactions will include artificial intelligence systems by 2025.

⇒ Computer Vision

AI technology is allowing computers and systems to derive meaningful information from digital images, videos, and other visual inputs. For example, you can see its application in photo tagging on social media.

⇒ Discovery of Data Trends

AI algorithms can also use consumer behavior to find out data trends, allowing small businesses and big companies to build effective cross-selling strategies.

As a result, companies can provide relevant add-on suggestions during the checkout process.  If you use online shopping platforms such as Amazon and Flipkart then you must have experienced it during the order of some products.

⇒ Fraud Prevention

AI applications play an important role in tackling payment and sensitive information fraud. Many companies use AI-based systems to detect and prevent this type of fraud activity in an effective way.

⇒ Automated Stock Trading

Automated stock trading refers to the use of AI software to buy and sell stocks without human intervention. It is also known as algorithmic trading or high-frequency trading.

AI-based high-frequency trading platforms make thousands or millions of trades each day. As per reports, In  2020, half of stock market trades in America were automated.

Why build AI Software?

As a business, it becomes critical to first determine the reasons why you should build AI software instead of jumping into how to create AI software for you.

So in simple terms, AI software can automate your business processes, improve decision-making, and help you achieve your business goals efficiently.

According to an Accenture report, AI technology has the potential to double the economic growth rate of some developed countries by 2035. Additionally, the global AI software market size is estimated to reach $126 billion by 2025.

AI algorithms have the ability to process large amounts of data more quickly than humans and offer more accurate results. For instance, AI-powered chatbots can handle customer inquiries 24/7 without any support from the human agent which provides employees the freedom to work on more complex tasks.

Further, many companies are also using AI software to analyze customer behavior, predict sales trends, and automate marketing campaigns. With so many advantages of AI software, building and investing in AI is a smart move for any business or startup looking to gain a competitive advantage.

Benefits of AI Software

Let’s take a closer look at a few more benefits of AI software before we dive into the process of how to create AI software:

1. Reduction in Human Error

One of the primary benefits of AI software is that it can significantly reduce errors and increase accuracy.

Before generating any result,  AI learns from data and uses algorithms to make decisions, which can be more reliable than human judgment.

For example, AI software in the use of robotic surgery systems can perform complex procedures with precision and accuracy, reducing the risk of human error and enhancing patient safety in the healthcare sector.

2. Zero Risks

Another big advantage of AI is that we can overcome many risks by letting AI robots do them for us. Whether we talk about defusing a bomb, going to space, or exploring the deepest parts of oceans, machines with metal bodies are resistant and they can survive difficult atmospheres.

Further, they can offer accurate outcomes with greater responsibility and not wear out easily.

For instance, fully automated production line in a manufacturing sector, the robots perform all tasks, eliminating the risk of human error and physical injury in hazardous situations.

3. 24x7 Availability

Research shows that humans are productive only about 3-4 hours per day. Humans also need breaks and time off for work-life balance. But AI software can work unlimited hours without taking any breaks.

They make decisions faster than humans and they can multitask at a time with accurate results. AI systems can also handle tedious tasks easily with the help of AI algorithms.

For example, an online customer support chatbot, which can offer instant assistance to customers anytime and anywhere.

4. Online Assistance

Today most technologically advanced companies use digital assistants to engage with users or customers, which eliminates the need for human staff. Also, many websites use digital assistants to deliver user-requested content.

Users can get all the required information related to a product or a service of a company by having conversations with these digital assistants.

As we know almost all companies require a customer service staff to address the doubts and concerns of the customers. But, by creating AI software such as a chatbot or a voice bot, businesses can answer all of their customer’s queries quickly using AI.

5. Unbiased Outcomes

We as human beings are always driven by emotions, whether we like it or not. AI systems on the other hand are devoid of emotions and highly practical and rational in their approach.

It is another big advantage of artificial intelligence software Development that it does not have any biased views, which ensures more accurate and reliable decision-making.

For example, an AI-powered recruitment system can screen job applicants based on their abilities, skills, and qualifications rather than demographics. This helps remove bias in the hiring process, leading to an inclusive and more diverse team.

6. Perform Repetitive Tasks

We often perform a lot of repetitive jobs as part of our daily work, such as analyzing data for flaws and mailing different types of notes and other things.

We can also use AI software to efficiently automate these tedious tasks and even eliminate “boring” tasks for other people or employees, allowing them to focus on being more creative.

For example, chatbots can generate multiple types of content from these chatbots such as emails that require no creativity which will save a lot of our time and improve efficiency.

7. Daily Applications

In this digital era, our everyday lives are completely dependent on mobile devices and the Internet. We use a variety of apps such as Google Maps, Alexa, Siri, and OK Google, to take selfies, make calls respond to emails, etc.

With the use of multiple AI-powered applications, we can also anticipate today’s weather and the days ahead.

Today, if you want to go to Bangalore, all you need to do is ask Google where Bangalore is. Google will come up with the best route between you and Bangalore, along with Bangalore’s location and the total time to reach there on Google Maps.

8. AI in the Field of Medicine

AI has also made a major contribution to the field of medicine, with several types of AI software ranging from diagnosis and treatment to drug discovery and clinical trials.

AI-based tools can help doctors and researchers analyze patient data, identify potential health risks, and develop personalized treatment plans.

As a result, it can lead to better health outcomes for patients and help accelerate the development of new medical solutions and technologies.

9. Quick Decision-Making

AI software can make decisions quickly and it is another top benefit of building AI software. By automating many certain tasks and providing real-time insights, AI can help businesses and companies make faster and more informed decisions.

This can be especially useful in high-stakes environments, where decisions must made swiftly and accurately to prevent costly errors or save lives.

For example, AI-powered predictive analytics in financial trading can analyze vast amounts of data in real-time and make informed investment decisions faster than human traders, improving returns and reducing risks.

10. Pattern Identification

It is another key area where AI systems are useful. With its ability to identify patterns and trends by analyzing vast amounts of data,  AI can help small businesses as well as established companies better understand customer behavior, market trends, and other important factors.

Further, this information can be used for businesses to make better decisions and improve outcomes.

For instance, AI software in fraud detection, where machine learning algorithms can identify patterns and anomalies in transaction data to detect and prevent misleading or fraudulent activities, improving security and reducing financial losses for individuals and businesses.

Which Programming Language Is Used in AI?

Hopefully, after going through the above-mentioned top 10 benefits of AI software, you know how AI software can save a lot of your time and money, by automating typically routine businesses.

Once AI is in place, you can ensure that those tasks will be handled quickly and with more accuracy than can be achieved by a human being.

However in order to start with our how to create an AI software, it is equally important to know what programming languages you need to develop an AI system for your business.

There are multiple programming languages that can be used to build an AI system. But the most important and commonly used programming language is Python.

Despite the fact that it was created before AI became crucial to businesses, Python is one of the most popular languages for Artificial Intelligence development. Python is the most widely used programming language for Machine Learning, which comes under the umbrella of AI.

One of the key reasons Python is so popular in AI creation is that it was developed as a powerful data analysis tool and has always been used within the fields of big data. Another big reason why Python is always ranked near the top is that there are AI-specific frameworks that were created for the language.

For instance, one of the commonly used frameworks is TensorFlow, which is an open-source library created specifically for Machine Learning (ML) and can be used for training and inference of deep neural networks.

A few other AI-centric frameworks include:

» scikit-learn – for training Machine Learning (ML) models.

» PyTorch – visual and natural language processing.

» Keras – serves as a code interface for complex calculations.

» Theano – library for defining, optimizing, and evaluating mathematical expressions.

Lastly, Python is also one of the easiest languages to learn and use, which makes it one of the best languages to use for AI development.

How to Create an AI Software?

Now, let’s come to our main topic how to create an AI software. The AI development process is similar to building any other software development application but with a few more steps.

Here are 6 main steps you should follow to build AI software. It is also important to note that I focused on the AI-specific development steps.

Step 1: Identify the problem you want to solve

The first and most crucial step in creating AI software is identifying the problem you want to solve. Regardless of whether you decide to build AI software or any other software, the main idea is to align the client’s business goals with the intentions of your AI program being created.

At this stage, you need to focus on the following points:

» Define the problem

» Select a software development company

» Agree on business objectives

» Set up a project roadmap

» Decide on the technology that your business may need

» Set a budget

» Roughly estimate software development time

Before we dive into the next step of building your own AI software, we'd like to highlight that it's perfectly fine to set overly broad goals when planning to build an AI software.

Step 2: Gather Data

The next step is to gather data for your AI software. When you’ve framed the problem that you want to solve, you need to choose the right data sources.

It’s more important to get high-quality data than to spend time on improving the AI model itself. This data falls under two categories:

⟩ Structured Data

Structured data is clearly defined information that includes certain patterns and easily searchable parameters. For example, names, addresses, birth dates, and phone numbers.

⟩ Unstructured Data

Unstructured data doesn’t have any patterns, consistency, or uniformity. It includes elements such as audio, images, infographics, and emails.

After you have gathered the data you need to clean the data, process it, and store the cleaned data before you can use it to train the AI model. Data cleaning is all about fixing errors and omissions to improve data quality.

Step 3: Choose an AI Algorithm

There are multiple different AI algorithms available. Which algorithm is right for your problem?

Consider the type of data you have, the performance metrics you need to achieve, and the resources you have available. When instructing computers what to do, you also need to choose how it will do it. That’s where the computer algorithm comes in. In simple words, these AI algorithms are mathematical instructions.

It is important to create a prediction or classification Machine Learning algorithm so the AI model can learn from the dataset.

Step 4: Train your AI Model

Moving forward with how to create an AI software, you need to train the algorithm using the collected data. This can be a time-consuming process, but it is crucial to train your model until it achieves the desired performance on your evaluation metric.

It would be best to optimize the AI algorithm to achieve AI software with high accuracy during the training process. However, you may need to gather some additional data to improve the accuracy of your model. Model accuracy is the essential step to take. Therefore, you need to establish AI model accuracy by setting a minimum acceptable threshold.

Step 5: Deploy your AI Model

After your AI model is trained, you need to deploy it so that it can be used to solve your problem. This step may include integrating your model into an existing software system or developing a new software application.

You can also consider this step as a pre-final stage, where the last errors are caught and the ability of the AI system to withstand the flow of users is checked.

In this way,  both manual and automated testing is carried out in a real environment.

Step 6: Monitor and Maintain Your AI System

The last step in the process of how to create an AI software is monitoring and maintaining your AI system.  It is necessary to monitor performance and make necessary adjustments.

This may involve observing real-world usage patterns that can help refine the AI model and software further, it also includes retraining your model on new data or fine-tuning its parameters.

After looking at the main 6 AI software development steps, let us move ahead and take a look at the key potential challenges associated with creating AI software.

Challenges of Building AI Software

As of 2023, we have witnessed remarkable advancements in the field of Artificial Intelligence (AI). However, it is also important to acknowledge that the process of building AI software may involve many challenges as well.

These challenges in artificial intelligence include a myriad of complexities that demand careful consideration and strategic approaches.

Here are a few key challenges that businesses often face in the AI software development process:

⇒ Lack of Understanding

Despite the fact that AI is constantly evolving, it is still a relatively new field and there is much businesses have yet to understand about its inner workings.

This lack of understanding may improve complexity in the development of reliable and accurate AI systems.

However, to address these challenges in the AI software development process, businesses can invest in research and development efforts to advance the understanding of AI algorithms, models, and techniques.

⇒ Privacy Concerns

AI models often rely on vast amounts of data to train and operate effectively. But, this data can include personal and sensitive information, leading to privacy and data protection concerns.

To mitigate these concerns, businesses must prioritize implementing robust privacy measures, such as data anonymization and secure data storage.

⇒ Lack of Data

As mentioned previously, AI software heavily relies on large and diverse datasets for training and achieving optimal performance.

However, not all businesses and companies have access to the required volume or quality of data. To address these challenges in Artificial Intelligence development, businesses can collaborate and partner to gain access to relevant data.

⇒ Unclear Goals

Many businesses also face challenges in defining clear goals for AI implementations. AI systems can become difficult and useless without well-defined goals.

However, to overcome these challenges in AI, companies can conduct a comprehensive evolution s of their business processes and identify areas where AI software can bring tangible value.

⇒ Technical Difficulties

Businesses can also face multiple types of technical challenges in the process of AI development and implementation. These challenges may include such as data storage, security, and scalability.

By investing in robust infrastructure that can manage the volume and complexity of AI-related data businesses can overcome these challenges. They can also ensure data security and privacy throughout the AI lifecycle, which plays a critical role in building user trust.

Now, let’s move forward in the process of how to create an AI software, by taking a good look at the costs of developing an AI system.

AI Software Development Cost

The cost of AI software development heavily depends on the features and capabilities of AI software. However, to give you a rough idea, the overall AI software development costs can vary from $50,000 to $300,000.

Multiple other factors impact the cost of creating AI software such as the complexity of the model, the location of the hired software development company, the technology stack used, and the project delivery timeline.

In simple words, one can say that overall software complexity is the biggest factor that impacts the AI development budget.

For example, if you wish to develop AI software that is highly complex and has an intricate feature list, it will ultimately cost you more than simple AI software with minimum functionalities and features.

Future of AI Software

Today, Artificial Intelligence is already changing the way we live and work, and this trend is only going to accelerate in the future.

According to a resort of Grand View Research, the global AI market is estimated to grow by 37.3% from 2023 to 2030 and reach 1,811 billion. The report also shows that the healthcare and finance industries will be major drivers of AI adoption in the coming years.

As AI technology continues to evolve, we can expect to see more sophisticated and powerful AI software that can tackle even more complex problems than an AI-powered chatbot, like ChatGPT.

Hopefully, now you know how to move forward in the process of how to create an AI software for your business. If there are any further questions, feel free to comment below, or for any tech-related queries contact our software development experts at Arramton Infortech.

Read More: Responsible AI: What is it and Why Do We Need it?

Frequently Asked Questions

Q1. How to make your own AI?

Ans. Follow these 6 steps to make your own AI software:

» Identify the problem you want to solve with AI

» Gather data

» Choose an AI technology you want to use

» Build and train the model

» Test the model

» Deploy the model

Q2. What is the first step in the process of AI?

Ans. The first step in the process of AI software development is identifying the problem you want to solve. Regardless of whether you decide to build AI software or any other software, the main idea is to align the client’s business goals with the intentions of your AI program being created.

Q3. How to make an AI on your computer?

Ans. To make AI on your computer you can follow these 6 simple steps:

» Identify the problem you want to solve with AI

» Gather data

» Choose an AI technology you want to use

» Build and train the model

» Test the model

» Deploy the model