AI Pricing: How Much Does Artificial Intelligence Cost?

At its core, AI is really just software, right? It’s ones and zeroes working together to first learn from large volumes of data and then create something new. So, like any software, building AI takes time, effort, and – of course – money. And when we’re talking about generative AI services, the costs really start to add up. Why? Because the infrastructure and the computing power needed to train and run these AI models are, as you’d expect, pretty substantial.

So, whether you’re a company thinking about getting into AI or just someone curious about how it all works, you’re probably wondering – is AI expensive to build? That’s exactly what this article will explore. We’ll break down the average cost of creating an AI tool, what drives that cost, and what can be done to reduce it. Let’s start with…

How much does AI usually cost?

The cost of building AI can be tricky to nail down. This is because it really depends on what you’re trying to create and how complex your project is. For starters, you need to ask yourself two questions: how are AI models created, and how much time and effort does it take to produce the type of AI I’m interested in?

With smaller-scale AI projects, the price starts at around $8,000 USD. Naturally, as your project goes bigger – becoming more complex and data-intensive – the cost will naturally go up. Advanced AI projects, the kind that push technological limits, can easily go beyond the cost threshold of $250,000 USD. As you can imagine, AI tools like those created by OpenAI or Google are multi-million dollar projects, so if you aim to create a competitive solution at that level, get ready to spend big.

On the other hand, if your goal is to do something simpler, like an AI virtual assistant or chatbot, the price is much more manageable – anywhere from $5,000 to $45,000 USD, depending on how complex you want the tool to be.

What factors affect the cost of AI development?

As you should expect by now, the cost of AI is driven by several different factors, the first one being the project complexity we’ve already talked about. So, the more sophisticated the model, the more time and resources it needs to be developed.

The second factor is the size and quality of the dataset used to train the AI. Following the same logic as before, the more data you input into the AI to analyze, and the more complex that data is, the more you will need to spend on the AI tool.

The next factor is hardware, meaning all software needs to be supported by the right computing power. For that, you need dedicated AI processors and IT environments that can handle a massive flow of data and billions of calculations done at the same time, almost in real time.

Another factor is the development time itself. Depending on how experienced and large the team working on your AI tool is, it can take anywhere from a few weeks to a few years to make. Of course, to get top-tier professionals to develop your AI tool, you will need to spend more.

And finally, it’s not like the AI can be developed, made available to customers, and that’s it. There’s maintenance to take care of, updates to do, all to make sure your AI tool works not only as expected but also continues to become more effective over time. This, too, will add to the total cost of the AI solution.

How does data volume impact the cost of AI projects?

As mentioned, the amount of data you use in an AI project can really drive up the cost. Generally speaking, bigger datasets need more storage, more processing power, and more time to work with. Plus, the AI has to dig deeper to find patterns and make accurate predictions, which means more computing power is required than usual.

And, of course, the quality of the data matters too – cleaner and more relevant data takes more effort to gather and manage. As the data gets larger and more complex, both the development and infrastructure costs are going to go up.

Learn more: AI and machine learning development services

What are the ongoing costs of maintaining an AI application?

As already mentioned,, maintaining an AI application or service isn’t a one-time thing; it comes with ongoing costs that you’ll need to plan for. Here are some of the key costs involved:

• Performance monitoring – once your AI tool is up and running, you’ll need to regularly check its performance and make sure it’s working as expected.
• Model updates – AI models need to be updated regularly to stay accurate and effective. This means you’ll have ongoing development costs to fine-tune your AI models.
• Storage – as your AI collects more data, the costs for storage and infrastructure will go up.
• Cybersecurity – protecting your AI from potential cyber threats is a challenge, solved only with the right cybersecurity tools and IT security in place. That will add to your overall cost.
• Bug fixes and tech support – like any software, AI applications can run into issues that need quick fixes, and you will be the one required to cover that.  You’ll also need to have a support system in place to address any user questions, complaints, or suggestions for improvement.

What cloud platforms offer affordable AI services?

Considering how popular AI services have become across all industries, some of them are now available at an affordable price, offering really high efficiency. The most notable include:

• Google Cloud Platform (GCP) offers AI services like Vertex AI for building, training, and deploying advanced machine learning models. What’s great about it is that it includes pre-trained APIs for vision, speech, and NLP. Plus, it’s available in a highly flexible pay-as-you-go model which helps keep costs manageable.
• OpenAI API, hosted on Azure, is a service that provides access to advanced models like GPT for text generation and analysis. It offers flexible pricing and is considered an optimal choice for businesses and developers looking for cutting-edge AI.
• Amazon Web Services provides a variety of A tools like Amazon SageMaker for model training and APIs like Rekognition for image analysis. Like Google Cloud Platform, it’s available in a pay-as-you-go model, while its free-tier options for new users make it accessible to businesses of all sizes.
• Microsoft Azure features AI services like Azure Machine Learning for custom models and Cognitive Services for tasks like translation and speech recognition. It’s especially affordable for businesses using other Microsoft products because all of them can be easily integrated.
• IBM Cloud offers high-tech tools for natural language processing, data analysis, and automation. The pricing is competitive, and it’s a good choice for those needing specialized AI features.
• Oracle Cloud comes with a range of AI tools, including pre-trained and customizable models, at lower costs than many competitors.

How to reduce AI costs?

As you can predict from what we’ve discussed, the first thing businesses can do to cut AI costs is to use cloud-based AI services, which offer scalable options and pay-as-you-go pricing. Instead of building custom models from scratch, companies can also save a lot of resources by opting for pre-trained models from other vendors.
Once the AI is set up, keeping costs low involves optimizing workflows and ensuring only quality data is used. Poorly prepared data can lead to bad results, and fixing those issues can quickly turn into a costly and time-consuming process. Lastly, using established AI models to automate tasks can reduce the need for manual labor, resulting in long-term savings – not necessarily lowering the price of AI itself, but definitely cutting down a business’s overall costs.

Tap into the power of AI

Using AI to boost your business operations is the exciting part – and it’s something that almost every company is already exploring or planning to do soon. But let’s be honest, designing, building, and maintaining AI can be a bit of a challenge. For some businesses, it feels overwhelming, but maybe that’s because they don’t realize they don’t have to do it all alone.

At Software Mind, we specialize in AI and machine learning development services, offering support to businesses of all sizes and industries as they dive into the world of AI. Whether it’s computer vision, predictive maintenance, or advanced data analysis, our solutions can help you boost productivity and cut down on operational costs. Get in touch – our experts are eager to listen to your AI goals and offer guidance.