AI development services

How Much Does AI Application Development Cost? Examining The Facts & Figures

Deployments of AI in industrial applications are now actively growing, with more businesses adopting it to improve their outputs. However, the question of high expenses for such complicated technology to install, maintain, and gain from its complexity may come across as a question. In this blog post, we will look at the facts and figures about AI application development costs to make sure you decide what to do next.

An Overview of AI Application Development

The expenses of AI application development must be considered cautiously because of the high differences among project requirements. In addition to the noted elements, other general factors also tend to alter the price. This blog will discuss the various factors that could affect your project’s cost of AI application development.

Size and Scope

The project’s magnitude is the second thing to consider when creating a budget for AI application development. AI projects involving only a few hundred hours of development will need to be built differently compared to projects requiring about a thousand hours to be developed. The algorithm’s number of features and complexity will also be the deciding factors, as the latter is.

Perfect developer

Another aspect to remember involves deciding whether to employ a full-time employee or if your current employees can accomplish the tasks. If you don’t have internal expertise in branding, sourcing for professionals, either from outside or a third-party provider, will be necessary. Thus, choosing could be more expensive but solely designed to achieve a quality result.


As long as the AI applications are used, they will need regular maintenance and backup support. This activity includes monitoring and controlling the system to ensure that any newly accepted data is well integrated. The budget for AI application recurring expenses needs to be factored in for planning purposes.

Artificial intelligence (AI) technologies and how much they cost

An overview of artificial intelligence systems reveals four main categories: rule-based, decision-tree, neural network, and genetic algorithm. When comparing complexity and cost, rule-based systems are simple and inexpensive, while neural networks are complex and expensive.

  1. Decisions in rule-based systems are based on a collection of rules or if-then statements. Perfect for startups and small businesses on a tight budget, light-complex AI systems are easy to build and launch.
    Cost: $30,000–$70,000

2. Decision trees discover the optimal solution for each subproblem by breaking the problem into smaller subproblems. Machine learning’s chunking mechanism learns from its mistakes and builds solutions accordingly. Because of this, they take more time to develop but are more versatile than rule-based systems.
Cost: $75,000–$120,000

3. A neural network mimics how the human brain functions in a computer. As its complexity rises, its ability to learn from past mistakes and make data-driven predictions increases. The most powerful artificial intelligence technology, neural networks, is also the most costly to create and implement.
Cost: — $120,000 — $200,000

genetic algorithms employ evolutionary principles to solve problems, similar to neural networks. They can be used for optimization and prediction tasks. They are ideal for extensive network usage.
Cost: — $200,0$200,000–$280

The Cost of AI Implementation: The Principal Factors.

As with any new technology, constants will not determine the cost of AI and its app. Some of the key considerations include: Some of the key considerations include:

1. The scope of the project: How large and diverse will the AI application you move forward with be? This will significantly affect costs and the time frame.

2. The project’s complexity: How much does the AI application you want to create cost? This will significantly change fees and the timeline.

3. Your team’s skill set: Do you have a skilled team that can promptly develop, analyze, and deploy AI applications? Should you invest in teamwork training? This will also alter development costs.

4. The tools and technologies used: What tools and technologies should be used to build your AI app? This includes hardware and software.

5. The market for AI applications: What would be the availability of AI applications across sectors? This will define what fee you can demand and how the product/service you are developing should be promoted.

How do we minimize the cost of building an AI app?

The AI has not yet reached its full potential, which implies that the cost of developing this app is very high. And yet, you can minimize the cost of preparing an AI app for launch. Below are some tips:

1. Pick Open Source Tools And What You Stand On

Such fees are usually paid for the proprietary software needed for AI projects. However, open-source tools and platforms can be utilized to avoid these costs.

2. Use Cloud Services

Cloud solutions are designed to reduce infrastructure costs. You should only pay for the resources you like, and they will be cheaper than building your infrastructure.

3. Outsource

Outsourcing is a suitable method of eliminating the cost factor. This is good news for startups with limited human resources budgets, which cannot be utilized in AI development projects.

4. Choose Simple Projects

Sumpai-project complex projects will need additional time and financing so that final costs will be rightfully higher. Avoid handling a simple AI project at the very first opportunity is advisable.

Keys to Saving Costs on Product Development

1. Tap into the AI potential at the first instance.

Through your awareness of the chance for AI and an estimation of its contributions to your business, you can grasp the moment when AI companies come into being and, therefore, decide for them or not. This will allow you to avoid those expensive mistakes that have something to do with the development process in your daily life.

2. Based on The Ready-Made Realistic Roadmap

Roland, you need a thoughtful implementation plan after you outline the areas for AI application in your business. In this case, the decision-makers must discuss the means and methods for each step and any risks they see that might make the final cost wrong.

3. Use Existing Data and Resources as Benefit

Innovation in this area requires utilizing available data and resources. This may use information from other business organizations, partnerships, published data sets, or research organizations.

4. Choose the right technology to research.

Aside from the importance of selecting the correct technology platform, cost reduction is another pivotal factor. There are many different platforms, and they are all heterogeneous. It is essential to understand and choose the platform that will be suitable for your specific needs and demands.

5. Test And Iterate

Lastly, one needs to test and optimize during development, thus achieving the best code and application. This area concerns trying new approaches, such as algorithms and models, and taking relevant actions according to users’ feedback. Doing so can increase the quality of AI applications and reduce budgets.

Instances of Successful AI Programs and Their Costs

Google In 2013/2018

The industry’s frontier-touching AI-powered thermostat, Google Nest, costs $250 and was released in 2013. In 2018, Google released the Duplex AI, which can call and book appointments on behalf of individuals. The hidden cost of applying AI is debatable, as it involves a 100+ team of researchers to develop.


In 2016, the IBM Watson team bragged they had beaten human competitors on the quiz show Jeopardy!, the development of which cost them at least $15 million.


In 2014, Amazon introduced the Amazon Echo, a voice-controlled assistant that costs $180.


AI system building may be challenging and costly at the same time. On the other hand, proper guidance and knowledge of AI application development costs allow the business to develop sharp solutions that create tangible benefits. Considering the facts, writing an AI app may have been advantageous when we wanted to make our goals worthwhile. From knowing licensing agreements to sourcing for suppliers with flexible payment terms, your prior knowledge will strongly affect your investment.

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