How to reduce AI app development costs

13 min read
October 24, 2023

The cost of AI app development is one of the biggest barriers for companies looking to build an AI app.

But, your costs won’t be as high if you play your cards right.

There are a number of ways you can significantly reduce them.

Here, we’ll discuss the steps you can take to reduce your AI app’s cost.

Let’s dive in!

Start with clear goals

Starting with clear goals is essential for any project, big or small.

It’s a key step if you want your app to succeed.

And having clear goals will help you reduce your AI app’s development costs.

A handy framework you can use to set clear goals is the SMART goals framework.

With it, you’ll set goals that are:

  • Specific
  • Measurable
  • Achievable
  • Relevant
  • Time-bound

Clear goals will help you focus your development efforts and get your AI app to market faster.

And as AI is a rapidly evolving field, that can be the difference between failure and success.

Now, let’s discuss exactly how starting with clear goals will reduce your app’s costs.

How starting with clear goals reduces AI app development costs

One major danger you’ll avoid by starting with clear goals is scope creep.

Having clear goals will help you define your project’s requirements and your AI app’s development timeline.

Scope creep can end up costing you a lot of money.

And it’s especially easy to get carried away by the endless possibilities of AI.

Let’s say you want to build an AI-powered e-commerce app.

AI and e-commerce

source: EuroDNS

It will be tempting to jump right in and immediately integrate AI for:

  • Personalized recommendations
  • Customer service chatbots
  • Predictive analytics
  • Inventory management

But, this would balloon your costs and you would end up wasting a lot of time and money.

Starting with clear goals will help you prevent that from happening.

Also, having clear goals from the start will help your engineers, too.

It will help you create an achievable and realistic project roadmap that will make their job easier.

And that can save you a lot of money.

Key tips for setting clear goals

  • Stay focused – don’t get sidetracked by the possibilities of AI and prioritize getting your MVP to market
  • Prioritize core features – integrate the essentials first before adding other AI features
  • Set SMART goals – the SMART framework will help you set relevant and concise goals

Use pre-trained models and open-source tools

The high AI model training costs are a serious obstacle if you want to start developing an AI app.

That’s where pre-trained models and open-source tools come in.

Using them will allow you to integrate advanced AI features in your app at a fraction of the cost of a custom AI model.


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You can also fine-tune them with your own data to improve their performance and accuracy.

So, where can you get these models?

You can find them on sites like:

All of the models uploaded to these sites are open-source and you can freely use them.

Also, PyTorch and TensorFlow in particular have active community forums that can help your team if they have any questions.

Now, let’s talk about how pre-trained models reduce your AI app’s costs.

How pre-trained models and open-source tools reduce AI app development costs

Using pre-trained models helps you bypass the costly AI model training process.

If you built and trained an AI model from scratch, it would massively drive up your AI app’s development costs.

Building an AI model from scratch requires a lot of investment in infrastructure and uses up a lot of resources.

Open-source, pre-trained models help you bypass those costs.

Let’s say you’re building an app with AI facial recognition.

AI facial recognition

source: IEEE

Training a deep learning model that can do it from scratch would take up a lot of your time and resources.

But with Dlib’s CNN face detector or OpenCV’s DNN-based face detection and recognition models, all you need to do is fine-tune them with your data and you’re all set.

And this will reduce your costs and get your app to the market faster.

Key tips for using pre-trained models and open-source tools

  • Fine-tune the model – use your own data to fine-tune the pre-trained model for better performance
  • Engage with communities – they’ll be able to help you if you have any questions
  • Select the right models and tools – make sure the models and tools you use align with your business goals and needs

Use cloud-based AI platforms

Using cloud-based AI platforms is another great way you can drive your AI app’s cost down.

Much like the open-source pre-trained models, with cloud-based AI platforms, you can get advanced AI features in your app at a fraction of the cost of in-house AI model training.

The top cloud-based AI platforms on the market are:

They all offer a wide range of pre-trained models you can quickly and easily integrate into your AI app.

Just take a look at the AWS machine learning stack:

AWS ML Stack

source: AWS

And they have several advantages compared to using open-source models, too.

For starters, your engineers will have an easier time integrating their models compared to open-source models.

Open-source AI models might not have up-to-date documentation and can vary in quality.

With cloud-based platforms, you get a guarantee of quality and built-in integration tools.

Another advantage they have is commercial support.

If you run into any issues with any of the models, you’ll be able to solve them more easily.

Now, let’s talk about how exactly cloud-based AI platforms reduce your AI app development costs.

How cloud-based AI platforms reduce AI app development costs

One way cloud-based AI platforms reduce your AI app’s cost is by eliminating infrastructure costs.

If you use them, you won’t need to buy dedicated AI hardware like GPUs and TPUs.

But, the main way they reduce costs is by speeding up your app’s development.

With them, you don’t have to spend time and money on building and training an AI model.

Microsoft AI platform

source: Bisser

And since they’re end-to-end services, you can go from training to deploying an AI model in your app without ever leaving the platform.

Also, many of their AI models are available as APIs, so your engineers can integrate them into your app even if they don’t have experience with AI.

So, if you use cloud-based AI platforms, your AI app will go to market faster and at a lower cost.

And those are compelling reasons why you should go with them.

Key tips for using cloud-based AI platforms

  • Explore all of their services – these platforms offer a wide range of off-the-shelf AI models and services, make sure to make the most of them
  • Use their customer support – if you run into trouble with integrating their AI models, don’t hesitate to contact their customer service
  • Use their built-in integration tools – this will make deploying their AI models in your app even easier

Prioritize developing an MVP

Another good way you can cut down AI app development costs is if you focus on developing a minimum viable product (MVP).

An MVP is a bare-bones version of your app that contains only its core features.

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source: TatvaSoft

It’s the best way to validate your app idea before fully committing to its development.

And it works, too.

Some of the biggest apps on the market today started out as MVPs.

Take Airbnb, for example.

It started out as a simple website the founders used to rent out air mattresses in their loft during a design conference in San Francisco in 2007.

Airbnb MVP

source: Arkenea

And from there, it grew into one of the biggest travel platforms on the market today.

Now, let’s talk about why prioritizing MVP development will help you save money on your AI app.

How developing an MVP reduces AI app development costs

One of the main reasons why MVP development reduces your AI app’s cost is because it shortens development time.

As it’s a bare-bones version of your AI app, it won’t have complex requirements like a fully developed app.

This means that you can get it to market sooner and avoid overengineering and scope creep during development.

And you won’t need to build and integrate a complex AI model, either.

That will help you reduce development costs.

Also, developing an MVP will help you save money if your app idea isn’t validated.

An MVP is, first and foremost, a validation tool.

If your AI app doesn’t resonate with your users, you’ll find it much easier to pivot to another idea if you’ve only developed an MVP.

And that’s why you should go for it.

Key tips developing an AI app MVP

  • Focus on your AI app’s core features – when developing an MVP, focus only on building your app’s core features to show why it’s needed on the market
  • Prioritize getting to market – the point of an MVP is to get your app to market as quickly as possible
  • Be prepared to pivot – if your MVP doesn’t validate your idea, be ready to pivot to another idea

Hire a dedicated team

Outsourcing your AI app development can be a great way to reduce your development costs.

And hiring a dedicated team is the best outsourcing option.

You get all the benefits of an in-house team without the costs associated with assembling one.

But, what is a dedicated team, anyway?

A dedicated team is a development team formed by an agency or a third-party service provider.

Dedicated team

They function just like an in-house team and handle your AI app’s development from start to finish.

And the best part?

The dedicated team is assembled based on your exact requirements.

And that can save you a lot of time and money you’d usually spend on hiring and onboarding new team members.

Let’s now discuss how a dedicated team can save you money during your AI app’s development.

How hiring a dedicated team reduces AI app development costs

One of the main ways hiring a dedicated team can reduce your AI app development cost is by eliminating hiring and onboarding costs.

Hiring and onboarding the engineers you need to develop an AI app can get costly.

Onboarding costs

source: Scribe

A report by SHRM estimates that the average onboarding cost is $4100 per new hire.

And if you need to hire a whole AI app development team, that can quickly add up.

Hiring a dedicated team will help you avoid those costs.

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But, you need to partner with the right AI app development company to reap the benefits of hiring a dedicated team.

It can be tempting to go with the cheaper option and hire a bunch of freelancers.

But, that will likely cost you more in the long run.

With a dedicated team from the right company, you’ll get guaranteed quality assurance (QA) and get your AI app to market faster with fewer issues.

That’s why it’s the right choice for your AI app.

Key tips for hiring a dedicated team

  • Hire a team tailored to your needs – the dedicated team you hire to develop your AI app should be aligned with your business goals
  • Don’t neglect quality assurance – make sure the team you hire has a QA expert to avoid quality issues
  • Prioritize finding a long-term partner – establishing a long-term partnership with an AI app development company is mutually beneficial and will make your app better

Regularly optimize your AI model

In a rapidly developing field like AI, regularly optimizing your AI model is a must.

And it can reduce your AI app development costs, too.

But first, let’s talk about the reasons why you should optimize your AI model.

The main benefit of regular optimization is avoiding model drift.

AI model drift

source: AIMultiple

If you don’t regularly re-train your AI model, it will lose accuracy and gradually generate worse outputs.

Also, regular optimization will help you stay ahead of your competitors.

It’s especially important if you’re developing an AI app in a market sector like stock trading where conditions can change on a dime.

But, an underrated benefit of regular AI model optimization is that it can lower your development costs.

Let’s go over the ways it can do that.

How regularly optimizing your AI model reduces AI app development costs

An optimized AI model uses resources more efficiently and needs fewer computational resources.

And that can significantly reduce your AI app’s development costs, especially if you’re using cloud-based AI platforms.

An optimized model will use fewer resources during:

  • Training
  • Inferencing
  • Retraining

And this translates to lower development costs.

Also, optimized AI models are often smaller in size so you’ll save on storage costs, too.

Another benefit of regular AI model optimization is that you’ll have fewer issues after you launch your app.

It will need fewer large-scale updates which will reduce your maintenance costs.

In short, regular optimization is a great way to reduce your AI app’s costs and keep your app competitive.

And that’s what makes it so important.

Key tips for optimizing your AI model

  • Create a feedback loop – make sure your users can leave feedback on your AI model’s performance
  • Use continuous monitoring tools – these tools will help you keep track of your model’s performance and adjust it accordingly
  • Update your model gradually – smaller updates will cost less and will be easier to implement


The cost of AI apps can be discouraging and stop you from building your own.

Luckily, there are steps you can take to reduce your AI app’s cost without sacrificing quality.

And that’s especially true if you find the right development partner.

If you want to learn more, check out how we build AI apps and get in touch with us if you want to make your AI app idea a reality.

Written by

Mario Zderic

Co-founder and CTO

Mario makes every project run smoothly. A firm believer that people are DECODE’s most vital resource, he naturally grew into the role of People Operations Manager. Now, his encyclopaedic knowledge of every DECODEr’s role, and his expertise in all things tech, powers him to manage his huge range of responsibilities as COO. Part developer, and seemingly part therapist, Mario is always calm under pressure, which helps to maintain the office’s stress-free vibe. In fact, sitting and thinking is his main hobby. What’s more Zen than that?

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