Cost to build AI software

Want to know how much building an AI program will cost? You’re not alone! AI is the world’s noncore industry, and financial input is necessary for developmental reasons.

In this guide, we will explore the elements that determine the pricing of constructing AI software and we offer some tips that you can use to understand how to optimize pricing.

But first, let’s take a quick overview of the AI facts and its market.

Facts & Stats of AI

Let’s start by uncovering some intriguing facts and figures about artificial intelligence: 

AI estimated growth
  1. Artificial intelligence is estimated to grow to $738 billion by the year 2030.  
  1. It won’t take long to get to these numbers with doubling or even tripling rates thanks to technological branches such as machine learning, natural language processing, and computer vision. 
  1. AI-enabled programs across the board, that is, from healthcare finance to retail and manufacturing industries, are giving rise to a new tech landscape.  
  1. To cite an example, AI-motivated chatbots are changing the character of customer service, while predictive analytics tools are optimizing the management of supply chains. 
  1. The strategic organizational adoption of AI technologies provides an advantage, as they help boost operational efficiency and allow innovation to be established flows to get opened.  
  1. The evolution of AI has brought about investment from both start-ups and multinational firms to stave off AI disruption. 

After a clear overview of the AI market, ready to grasp the expenses associated in developing AI software. 

Cost Breakdown of Developing AI Software

The development of AI computer software involves multiple kinds of expenses that include, among others, software development, infrastructural expansion, data collection and recurrent maintenance.  

The compilation of expenses doesn’t have a single price. Each solution has its costs based on the capabilities incorporated and the expertise of the solution’s developers. 
Here’s a gross description of the costs that are associated with software development of artificial intelligence: 

Expense Category Description Estimated Cost 
Development Tools For developing Artificial Intelligence (AI), like licenses for software, development environments, and other tools. $5,000 – $20,000 
Data Acquisition Expensive task of obtaining suitable quality data for both training and test parameter settings for AI models. $10,000 – $100,000+ 
Hardware Infrastructure AI resources, for example, GPUs, CPUs, the GPU/CPU servers employed for AI processing. $10,000 – $500,000+ 
Development Team Pays for AI engineers, Data Scientists, Software Developers and Project Managers. $50,000 – $500,000+ per year 
Training and Testing Expenses related to the education and testing of AI models, and costs connected to the usage of cloud computers. $5,000 – $50,000+ per month 
Integration and Deployment The process of integrating AI software into the existing systems and deploying it in a productive manner is another factor that affects AI integration. $10,000 – $50,000+ 
Maintenance and Support Frequent expenses are for the maintenance as well as the servicing of AI software, plus the cost of the user support services. $10,000 – $100,000+ per year 

Total Estimated Cost: The total bill for software engineers who can create AI software ranges from $100k to millions of dollars, particularly if the scale of the project is big, quality data (input) is required, and deployment is needed. 

These numbers give a picture of the best build process and expense breakdown of AI-based software.  

Do remember that these cost estimates could probably vary a lot depending on the proportion of the development team, the solution’s complexity, and the specific needs of the project. 

Factors That Influence the Cost of AI Software Development 

1. Complexity of AI Application: 

Some AI applications appear to be more sophisticated because they are more complex. The cost of the AI often is dependent on the complexity of the algorithms and features required.  

For instance, creating a basic chatbot will be less expensive than constructing a recommendation engine using artificial intelligence. 

2. Data Availability and Quality: 

Data is the backbone of AI to perform adequately. AI algorithms cannot learn well or make right predictions without enough good data.  

The right data is critical for the AI models training. Also note any privacy and regulatory issues. These variables impact both the cost and timing of an AI software platform. 

3. Customization and Integration: 

If you need an exclusive AI solution that is tailored to the specific demands of your business or plan to implement pre-made AI software, the customization and integration steps have a huge impact on the costs.  

Integration of AI in the existing systems might be accompanied with extra costs if the complexity is considered. 

4. Development Team Expertise: 

Developing AI software needs special knowledge areas like machine learning and natural language processing.  

Having experts in your team can be a shortcut for the AI software development and the cost.  

The expertise and competency of your team members are the critical factors which greatly determine the successful implementation of AI solutions. 

5. Infrastructure and Tools: 

AI requires tools and infrastructure reliability for instances like data processing, model training, and deployment.  

The type of cloud services you adopt as opposed to adopting your own systems affects the cost of developing AI software. 

Features to Integrate in AI Software: 

The first step in calculating the price of AI software is to present the features it will have. These characteristics not only determine the usefulness of your AI end-product but also influence the cost of your product in the development phase. 

Features to integrate in AI software

1. Natural Language Processing (NLP): 

NLP is a basis for functioning of AI software which helps the latter to understand and interpret human language.  

It allows for many possibilities, ranging from chatbots, voice assistants, and sentiment analysis programs, among others.  

The expense of NLP depends on the kind of language support that is needed, the degree of accuracy, and needed integration with the third-party APIs. 

2. Machine learning: 

Machine learning algorithms are the core process of AI applications, enabling systems to learn from data and output decisions.  

The sophistication of such algorithms, the number and quality of training data, and continuous software improvement lead to high development costs. 

3. Computer Vision: 

Visual interpretation is another vital element that contributes to the AI systems’ decision-making capabilities.  

It gives capabilities like object detection, image recognition, and facial recognition.  

The cost of the computer vision implementation into AI considers the complexity of the image analysis tasks, dictated by the need for specialized hardware or software libraries, and the required accuracy level. 

4. Predictive Analytics: 

Forecasting is the main power of predictive analytics. It is based on historical data and statistical algorithms to predict future trends or outcomes.  

By having predictive analytics capabilities at its core, AI software can be utilized to improve business processes, avoid risks, and take advantage of informed decisions.  

Obviously, predicting consumer behavior, financial market trends, and equipment failures, AI-enabled predictive analytics adds tremendous value to AI-powered solutions. 

5. Chatbots and Virtual Assistants: 

AI chatbots and virtual helpers are chat interfaces that copy human conversation, allowing for individual assistance and support 24 hours a day.  

Whether it is customer service and lead generation tasks or scheduling appointments and answering FAQs, chatbots help to organize communication and improve user experience.  

Incorporating chatbots in your AI software may help reduce the routine work, improve the overall engagement and increase the scale of the operations efficiently. 

Whether you use NLP to make conversations more human or machine learning for data analysis or computer vision for visual perception, each feature adds complexity and influences the development prices.  

Besides that, the evaluation of your demands and the prioritization of the features based on both the budget and goals of the project are of great importance for the success of the development of the AI. 

Contact AI experts

Most importantly, you must know how to reduce AI costs and start benefiting from AI right away. 

The below section gives you an understanding of the cost optimization techniques.    

How to optimize AI development costs? 

AI development costs can have a wide range, contingent upon variables such as the complexity of the model, its functionality, and the skills of the development team.  

1. Define Clear Objectives:  

Before designing your AI, specify the goals and objectives which you want to attain, and how you want to achieve them.  

This will simplify the development process and save the money spent on unnecessary activities/works not included in the project’s initial scope. 

2. Consider Open-Source Solutions:  

Consumption of open-source AI frameworks and tools can help lower development prices.  

Development processes can be sped up and custom coding efforts can be eventually lightened as platforms like TensorFlow, PyTorch, and scikit-learn provide developers with many pre-built algorithms and models. 

3. Iterative Development Approach:  

Be agile and iterate. Build your AI model in small increments and test constantly.  

This will help you immediately spot the problematic points as well as ensure that most of the rework and cost overruns will be minimal. 

4. Data Efficiency:  

The costs involved in data gathering and processing may account for a sizable portion of AI development expenses.  

Emphasize collecting the best-formulated and important data and apply the cleaning and pre-processing processes to improve efficiency. 

5. Cloud Services:  

The utilization of the cloud computing AI services by Amazon AWS, Microsoft Azure, or Google Cloud Platform can be considered.  

These cloud systems provide you with usable infrastructure resources as well as AI services on the model of a pay-as-you-go service which can be used based on demands without any initial investments in the hardware. 

6. Outsourcing Non-Core Activities:  

Outsource some activities that are not in line with the core activities such as data labeling, annotation, and model training to the specialized service provider.  

This is a way to better maximize efficiency, reduce operational expenses, and bring tangible results out of the allocated resources. 

7. Choose the Right Development Partner:  

Working with an experienced AI development company is beneficial as this helps you save both your time and money in the long run.  

If you want to create your own AI, then look no further than BigOhTech, our expert engineers have frequently shown their abilities during projects, completing tasks on time and within budget. 

But one questions that need to be answered that, 

Also Read: Generative AI In Fintech

What makes BigOhTech a perfect choice for building your custom AI software? 

Not sure about the design of your AI software product and want to create it?  

Don’t worry! 

This is the right place for you.  

We do Build customizable AI applications at BigOhTech, keeping in mind that needs and budget determine your decisions. 

1. Transparent Pricing:  

We understand the price is the main element for you to make a specific plan. That is why we offer transparent cost modelling and estimation at the beginning of each project stage to clarify your expectations. No hidden charges or surprises. 

2. Expertise in AI Development:  

After all these years working in the field of artificial intelligence our team has mastered the required skill sets and knowledge that enable us to make your vision a reality.   

We provide AI solutions for use in the healthcare, finance, and e-commerce sectors. 

3. Flexible Solutions:  

It is known that each of the projects is unique, so our services are specially tailored to suit your specific needs.  

We can deliver exactly the type of AI solutions that you need, from chatbots to machine learning, and our expertise and resources enable us to exceed your expectations. 

4. Cutting-Edge Technology:  

We always source the latest and greatest AI technology to ensure that your software is the most innovative on the market.  

Starting from NLP to CV, we implement the most advanced AI tools and techniques, designed to assist our customers with AI-driven products that create value. 

5. Dedicated Support:  

The quality of your success is what motivates our BigOhTech business. We are your partner from the first consultancy to post-launch assistance by working alongside you as your guide.  


In the full run, AI software should be considered not only as the initial cost but also as an investment.  

Additionally, it plays a role in the attainment of your company’s long-term goals. Selecting a suitable one is a must. 

With BigOhTech, you are assured that your project is in capable hands.  

Contact us immediately and learn about our AI development services to bring your ideas into the world. Combined, we can come up with something awesome! 

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