Understanding the cost of AI can help businesses make an informed decision about whether they should invest in AI or not.
While the current market is already sizeable, the global artificial intelligence market size is projected to increase by over 13x over the next 7 years.
If you ask me, that's quite a huge increase, and that's the reason why many businesses are looking to invest in AI.
In this article, I will help you understand what AI is and its cost by breaking down the factors that affect AI pricing, sharing tips on how to reduce the cost of AI and explaining what costs are involved with maintaining an AI system.
Understanding and applying these factors can help you streamline business processes, provide better customer service—and ultimately gain a competitive edge.
Before we go into those, let's quickly discuss the cost range of AI solutions!
What's the average cost for AI solutions?
On average, companies can expect to pay anywhere from $0 to more than $500,000 for an AI software solution.
- Custom AI solutions: costs vary from $6000 to over $500,000.
- Third-party AI software: costs vary from $40,000 per year to as little as $0.
- Consulting AI services: Depend on the consultant’s hourly fee. Most AI consultants charge between $200 and $350 per hour.
Available AI software solutions range from pre-built solutions offered by third-party providers to custom platforms developed by in-house or freelance data scientists.
Because the range is big, so is the pricing.
For custom AI solutions, the cost is the highest. It varies anywhere from $6000 to over $500,000, depending on the complexity of the project and the resources required for development and rollout.
For third-party AI software, such as a pre-built chatbot, you can expect to pay up to $40,000 per year, or as little as $0. There are many free solutions available, but they may not meet the marketing needs of larger businesses.
There are also ongoing AI services, such as consulting. They generally cost less and depend on the consultant’s hourly fee. Most AI consultants charge between $200 and $350 per hour.
{{banner-short-v2="/banner-ads"}}
Factors that affect the cost of AI
The cost of AI can vary widely depending on a range of factors that businesses need to consider before investing in AI solutions.
Here are the key factors that impact the cost of AI:
1. Type of AI used
The type of AI used significantly affects the cost of AI.
First, you should consider if you need pre-built solutions or, generally, more expensive custom-built solutions.
Some of the most popular pre-built solutions include:
- Chatbots.
- AI writing software services.
- Recommendation engines.
- Fraud recognition systems.
- Predictive maintenance systems.
These are considered to be less expensive, as they require less customization to get working.
On the other hand, custom-built AI solutions are usually more expensive.
Some of the most popular custom-built solutions are:
- Analysis systems.
- Supply chain optimization systems.
- Process optimization systems.
- Virtual assistants.
Custom-built AI solutions require more effort to design, develop and maintain.
They also require the expertise of experienced developers familiar with AI development techniques, and you may need to hire additional professionals to get the job done.
2. Project complexity
The level of customization and the project's complexity often go hand in hand.
And as the complexity of the AI project workflow increases, so does the cost.
For instance, building an AI system that analyzes language and image recognition, or an analysis system, requires more resources and expertise than a chatbot that automates customer interactions.
3. Size of the dataset
The larger the dataset, the more resources are required to train the AI model and the longer it takes to achieve the desired outcomes.
For example, if a company has a large customer data set, training the AI model on that data will require more resources and time than if the dataset were smaller.
Additionally, larger datasets require more computing power and storage, which can increase the cost of AI.
That's why the size of the dataset directly impacts the cost of the AI solution.
AI maintenance costs: four factors to consider
What's the point of building a sophisticated AI model if you can't keep it running?
The following costs can come into play:
1. Hardware maintenance
Hardware requires regular maintenance, updates and repairs to ensure the system functions correctly.
Additionally, hardware failure can cause significant downtime, impacting the business's overall productivity.
2. Software maintenance
Maintaining the software used to run AI algorithms is another critical factor.
Software updates, patches and bug fixes are necessary to keep the system up-to-date and running smoothly.
3. Data maintenance
Data is the lifeblood of any AI system. Data maintenance involves cleaning, organizing and storing data in a way that is accessible and usable.
Data maintenance is essential for ensuring the accuracy and effectiveness of the AI system. If data is not properly maintained, it can lead to incorrect predictions and decisions.
4. Expertise
Maintaining an AI system requires a high level of technical expertise.
AI professionals with specialized skills are in high demand, and their salaries can be costly. You may have someone who can do this internally, but most companies don't.
Before building an AI system, you should take these costs into account, as well as any other niche-specific costs that you may have.
How can you reduce AI maintenance costs?
- Outsourcing AI development
- Leveraging open-source AI technologies
- Investing in cloud-based AI solutions
As AI systems become more widely adopted, businesses are starting to realize that maintaining them can be a significant expense. Luckily, there are several ways you can reduce AI maintenance costs.
1. Outsourcing AI development
By outsourcing your AI development to an experienced team, you can benefit from their expertise and reduce the risk of costly mistakes.
Outsourcing can lower labor costs because the development team will be responsible for hiring and training staff.
2. Leveraging open-source AI technologies
Another way to reduce AI maintenance costs is to leverage open-source AI technologies.
For this, you need to be familiar with the available open-source technologies.
Open source can give you a good starting point for your AI development, helping you avoid the costs of developing your own proprietary AI system from scratch.
3. Investing in cloud-based AI solutions
Investing in cloud-based AI solutions is another way to reduce AI maintenance costs.
Cloud-based AI solutions are typically cheaper and more accessible than on-premises solutions.
They also offer scalability, as you can quickly access new capabilities without having to make major investments in hardware or software.
One example of a cloud-based AI solution is Scribe, which uses ChatGPT, a natural language processing technology.
Scribe is a cost-effective tool that can help you automate task documentationm quickly and accurately with AI technology.
With just a few clicks, you can create step-by-step procedures out of any manual or instructions.
With the help of Scribe, you can:
- Build an AI-powered knowledge base.
- Document processes with the help of AI.
- Create visual guides.
Other popular cloud-based generative AI systems like Midjourney are also worth implementing into your existing systems.
{{banner-default="/banner-ads"}}
Is AI worth it for my business?
With AI's ability to automate tasks, improve decision-making and enhance customer experiences, it's no wonder that more and more companies are considering implementing AI solutions.
However, the question remains: is AI worth the investment for your business?
The answer is different for everyone, but understanding its advantages and disadvantages helps. Here are some of the immediate benefits you can gain from AI:
- Increased efficiency and productivity: AI can automate repetitive and time-consuming tasks, freeing up employees to focus on higher-level work.
- Improved decision-making: AI can analyze vast amounts of data and provide insights that humans may miss, enabling better decision-making.
- Enhanced customer experiences: AI-powered chatbots and virtual assistants can provide 24/7 customer support, improving customer satisfaction and retention.
- Competitive advantage: Implementing AI can give your business a competitive edge, allowing you to operate more efficiently and effectively than your competitors.
On the other hand, AI also presents certain risks and challenges for businesses.
The most notable ones are the high costs associated with AI implementation, the potential for bias in AI algorithms and data privacy concerns.
📌 Related resources:
- Benefits of AI: How Companies are Transforming Operations
- Implementing AI: How Your Business Can Overcome Challenges
Key factors to consider before investing in AI
While AI can bring many benefits, it's not a one-size-fits-all solution. Here is a checklist to consider before investing in AI:
1. The AI solution
The type of AI solution you choose will impact the cost and complexity of implementation. For example, a pre-built chatbot may be less expensive than a custom analysis system developed in-house.
2. Level of expertise
Implementing AI solutions requires significant expertise, which may come at a high cost. Depending on your company's needs, you may need to hire a team of data scientists or work with a third-party consultant.
3. Integration with existing systems
Implementing AI solutions can be complex, particularly if they need to integrate with existing systems. Ensure that your IT team is prepared to handle the implementation process.
4. Expected ROI
AI in business can have significant benefits. It's important to weigh these benefits against the cost of implementation. Consider the expected ROI and how long it will take for your business to see a return on investment.
📌 Related resource: The Top 7 Best AI Software to Fast Track Your Team’s Growth in 2023
Reduce AI costs and maximize your ROI
If you're not ready to invest in custom-built AI solutions, but want to maximize your ROI, consider choosing a cloud-based AI system like Scribe.
Scribe AI isn’t just any AI tool. It’s the first AI tool for process documentation. We trained it for one goal and one goal only: to help the go-to person spend waaaay less time documenting processes.
Sign up for Scribe and bring AI process documentation to your organization.
