AI software is a force multiplier for businesses of any size, allowing staff to streamline and automate workflows to improve their productivity and workdays. While out-of-the-box AI software can provide significant benefits to businesses that leverage it, it becomes apparent rather quickly that the only way to maximize AI’s value to your business is to have AI software developed specifically for your use case.
Developing purpose-driven AI software like this isn’t cheap, but usually provides a net value increase to the value of your business when done the right way. That being said, businesses still need to know what the upfront AI software development cost will be before investing in a new project.
This guide will cover:
- What affects AI software development cost
- How to decide on a budget
- What makes a quality AI software development partner
Let’s dive into each to understand better what kind of capital it will take to develop fully custom AI software.
What Affects AI Software Development Cost?
Software projects vary too widely in scale to lay out specific price estimates, but we can explain what will make them more or less expensive. There are several factors that will impact the cost of an AI software development project, including:
- Scope and Scale: The scope of your project’s functionality and the scale at which it will be deployed (number of users/departments) are the two most significant factors impacting the cost of a project. More features and more users will almost always require more money.
- Project Complexity: The number of features isn’t all that matters; the complexity of these features does as well. Complexity is usually increased when an AI software has to leverage multiple disparate databases, connect/automate workflows across multiple departments, or perform more advanced tasks like 3D modeling or video rendering.
- Tech Stack: Many custom AI tools are used to weave the functions of existing tools together, and these existing tools must be licensed in order to be incorporated into a new solution. These licensing fees will increase the cost of the final product.
- Data Requirements: The data required for the use and the training of AI and machine learning (ML) tools can increase development costs pretty substantially for acquisition, storage, and maintenance.
- IT Infrastructure: In addition to software and data, powerful AI tools require hardware to function properly. GPUs, storage drives, and servers are all necessary to maintain comprehensive AI tools, and the larger the scale of a project, the more you’ll need. Renting cloud infrastructure is an alternative route for data storage, and it comes with its own costs.
- Integrations: Integrating tools with your existing software can also add to development costs, though some types of integrations are less expensive than others. Common integrations with big box tools often come cheaper than bespoke-to-bespoke integration.
- Security and Compliance: Higher data security standards and regulatory compliance also add a bit to the cost of developing new software, especially in strictly regulated fields like healthcare.
- Team Quality and Expertise: Hiring a team with a longer and more specialized track record developing the type of tool you’re looking for will cost a bit more, but will be well worth it, as it’s the only way to ensure you’re getting your money’s worth regarding everything else on the list.
While there are other aspects of a project that can move the financial needle a bit, these are by far the most significant contributing factors. While you can compromise on many of them and still get tremendous value out of your tool, we recommend never compromising on the quality and expertise of your dev team. Whether you’re hiring in-house staff or contracting with a third-party custom software developer, it is important to invest in the right people.
A well-executed tool that is a bit smaller in scope is far more valuable than a poorly executed tool that is expected to make a heavier lift. The latter will accomplish nothing but a bigger headache shared by more of your staff.
How to Decide on a Development Budget
When determining what your dev budget will be, you need to consider the different costs associated with the project, how long they will last, and how significant an expense they’ll be:
Development Budget Considerations
| Cost | Description | Duration | Cost |
|---|---|---|---|
| Dev Team | The cost of hiring the staff necessary to develop the application. | Upfront if contracting a third-party or 6-12 months if hiring in-house. | $$$ |
| Maintenance Team | The cost of maintaining the app after it is live. | Perpetual | $$ for an in-house team or $ for a third-party |
| Licensing Fees (if applicable) | The subscriptions necessary for any third-party apps used within your software solution (if applicable) | Perpetual | $/$$ (Depending on the tool) |
| Data Storage Cost | The cost of your data storage infrastructure, whether you’re buying hardware assets or renting cloud storage. | Upfront if buying hardware or Perpetual if renting cloud storage | $$ upfront or $ in perpetuity |
As you can see, there is a bit of control you have beyond just investing less in certain aspects in order to invest more in others. Opting for cloud storage, for example, allows businesses to save money upfront and spread that cost out with smaller payments over time. This can help businesses reduce their initial dev budget without losing any functionality or quality. Businesses can also reduce costs by relying less on third-party apps and choosing low-cost ones where they can.
It is also extremely important to consider fixed perpetual costs, like paying a maintenance team to keep your system up and running. Whether you hire one yourself or pay your development partner to maintain the tool, you’ll want an initial budget that leaves room for this perpetual cost and others like it.
At the top of the list, though, is your development team. Whether you hire your own or a third party, this should be the lion’s share of your AI software development cost. It isn’t enough to simply pay your team more, though, you have to know what to look for in a development partner first.
What Makes a Quality AI Development Partner
Not all custom software development companies are created equal, and much of what determines whether you should invest in them and their business is how much they’re willing to invest in you and yours.
A great AI developer will not only have extensive experience with clients in your industry and with AI and ML technology itself, but also take the time to do a deep dive into your business’s workflows to ensure they know your needs as well as they know their own. A simple series of onboarding meetings may be sufficient for smaller products, but for any significant investment in new IP, businesses should find a partner they can count on to get hands-on with their current workflows and identify comprehensive solutions themselves, as opposed to just taking a list of desired features and running with it.
Custom AI Software Development With 7T
At 7T, we use a “Business First, Technology Follows” approach to implement AI/ML solutions for our clients across countless industries. Our custom-built platforms leverage machine learning and AI technology to deliver significant operational advantages with a robust ROI. Our team will audit your organization’s challenges, often showing up on location to embed ourselves in your business for a time to understand your needs from a first-person perspective. Then, we’ll architect a value-generating solution to transform your vital processes and meet your goals.
7T is based in Dallas, Houston, and Charlotte, NC , but our clientele spans the globe. If you’re ready to learn more about AI software development cost, contact 7T today.
