The race to the forefront of AI adoption is on, with 72% of organizations using it in 2024 – up from 55% in 2023. And those investments are justified: according to Microsoft, every dollar invested in AI yields 3.5x in ROI, on average.
But if you want to succeed at securing buy-in for a new AI project, you need something more than industry stats. You need to calculate the said ROI for your specific use cases, and estimating the development costs is the first step to doing so.
Here’s what determines how much your artificial intelligence project may cost you.
Custom vs Pre-Built Model
If you start from scratch, AI development will entail higher costs than if you customize a pre-built model for your use cases. But, of course, you gain something in return: namely, unparalleled flexibility in technical requirements and implementation techniques.
That’s why custom AI model development is more suitable for:
- Groundbreaking, innovative projects
- Systems with strict compliance, privacy, and security requirements
Pre-built models, in turn, are a cost-effective option for run-of-the-mill use cases, like summing up financial reports or predicting cash flows.
Model Complexity
AI solutions may fall into one of these categories:
- Chatbots (e.g., for self-service customer support)
- Analytics systems (e.g., for data-driven insights into the organization’s financial performance or fraud detection in insurance claims processing)
- Virtual assistants for employees (e.g., versatile ChatGPT-like solutions for streamlining mundane tasks)
The more complex the solution, the more time it’ll take to develop it – and, therefore, the more it’ll cost. That rings true for any development project, from blockchain solutions to AI systems.
That’s why the project costs range from $20,000 to $500,000+. The cost of using pre-built solutions will also fluctuate depending on the required model capabilities, as well as the selected vendor.
Training Data Required
AI models have to be trained on vast amounts of data. You’ll need to verify that data for accuracy and quality, check it for potential bias, and properly label it.
While you may already have this data, it’s unlikely to be ready for usage in training as-is. Preparing it may take hundreds of hours of paid work.
Alternatively, you may get data samples from third parties on marketplaces like Amazon’s Data Exchange. It allows you to choose from 1,000+ free data sets, while paid third-party data sets can cost as much as $440,000 – that’s the price of the Similarweb Single Market Data Feed.
Infrastructure Costs
AI solutions must be deployed in the cloud because they require substantial computing power to function. AI model training is especially resource-intensive and needs powerful instances.
Overall, the infrastructure costs will depend on:
- Selected vendor: e.g., Amazon, Microsoft, Google
- Service modalities: GPU and CPU instances, storage, support services like load balancer, etc.
Tech Stack
Your tech stack may include proprietary tools that entail licensing fees. Using AI platforms like Dataiku or H2O AI, for instance, can cost you between $5,000 and $50,000 per month, depending on the required capabilities and support.
Alternatively, your team can use open-source tools like TensorFlow and PyTorch. They are free to use; however, they require experience and skill to be used effectively.
In-House vs External Development
Finally, you have to factor in the in-house vs external development costs. To put it simply, in-house development means you have to invest in hiring the right talent and managing the project hands-on. (Remember to factor in the employee benefits, potential office space and equipment costs, etc.)
In-house development is usually suitable for companies that already have AI specialists on payroll. If that’s not the case, you can hire a development partner instead. How much they’ll charge you for the project will depend on the factors above, plus:
- The partner’s location (hiring a development team in Poland is cheaper than in the UK)
- Its rates (they depend on the company’s experience, reputation, target market, etc.)
- Desired timeline, team size, and its composition
In Conclusion
At the end of the day, how much your AI project will cost you depends on too many variables to give you a clear-cut formula. So, contacting potential development partners and requesting a cost estimate remains the best way to realistically assess your costs.
Ready to discuss your project with AI development experts? Reach out to S-PRO, an artificial intelligence development partner with 10+ years of experience and 50+ AI and data projects delivered for fintech, energy, healthcare, manufacturing, and more.
