AI Pricing: How Much Does Artificial Intelligence Cost?

Companies can choose from several different AI software solutions, including:

Chatbots

A chatbot uses AI marketing to help your business streamline, automate, and improve customer support interactions.

You can use chatbots on your website, as well as select social media platforms, like Facebook. With a custom or pre-built chatbot, your business can offer shoppers or business buyers product recommendations, order updates, and even the convenience of making a purchase.

Analysis systems

An analysis system helps your business interpret and take action from large quantities of data.

You can use analysis systems to make data-backed decisions when it comes to your sales and marketing initiatives, like paid advertising or search engine optimization (SEO). This data-driven approach can help your company improve advertising and marketing spend, as well as increase its returns.

Analysis systems have also extended into writing.

Your company can now use AI SEO content writing services, for instance, to assess the optimization of current pages and receive actionable suggestions, like reaching a certain word count or using a specific title tag. Businesses can even use these services to build brand-new pages.

These kind of analysis system and service costs around $600 per page.

Virtual assistants

A virtual assistant helps your company complete general, everyday tasks while saving time.

Mainstream virtual assistants include Cortana, Siri, and Google Assistant. Some businesses, however, require a custom virtual assistant that uses company data to respond to customer or employee questions or requests.

Your AI choice, whether a chatbot, virtual assistant, or data analysis system, can impact how much your business pays for AI. Rates for a custom-built chatbot, for example, start at $6000. In comparison, prices for a custom-built data analysis system begin at $35,000.

When it comes to AI, companies can choose from pre- or custom-built solutions.

If you’re looking to incorporate a chatbot into your website, for instance, you may choose a pre-built option like Drift, HubSpot, or TARS. As expected, these pre-made options cost less than custom-built ones.

Drift, for example, costs $400 to $1500 per month while TARS costs $99 to $499 per month.

In comparison, prices for developing a custom chatbot can start at $6000 and go up to almost $15,000.

That doesn’t mean your business should move away from custom solutions. It is, however, an AI pricing factor that you and your company leaders will need to consider. If you want (or need) a custom solution, prepare a larger budget than for a pre-built product.

What you want in an AI solution also influences how much your artificial intelligence will cost.

Even if you’re choosing a pre-built solution, your must-have features will impact what you pay. If you want a chatbot that can integrate with your custom relationship management (CRM) software, for example, you may need to choose a higher-priced plan.

Or, if you want a custom data analysis system that uses the best AI software available, like IBM Watson, prepare for higher AI software prices. In this scenario, remember that your AI serves as an investment. If you want accurate and fast data analysis, you want an AI platform trusted by the industry.

Additional factors that your team should consider when investing in an AI solution include:

1. Data format
2. Data storage
3. Data structure (unstructured or structured)
4. Data processing speed
5. Minimum accuracy rate for predictions
6. Data visualization
7. Dashboard requirements
8. And more

While you can determine your AI requirements when meeting with AI development companies or data scientist contractors, it’s helpful to discuss what you want, need, and expect from an AI solution before researching providers.

AI management

How you develop, launch, and manage your AI also influences the cost of artificial intelligence.

In-house AI management gives your business complete responsibility when it comes to your AI. Your team develops, launches, manages, and updates your AI solution. That means you maintain an in-house development and data scientist team.

Compared to outsourced AI management, in-house management tends to cost more.

That’s because you must maintain a team, which includes salaries, benefits, and other hiring costs. For reference, data scientists earn an average salary of $94,000. Developers bring in around $80,000 per year.

With in-house management, however, your company can build an experienced team that knows your business, brand, and users. They also understand what your organization needs from an AI solution, whether it’s a chatbot, analysis system, or virtual assistant.

Outsourced AI management allows your business to pass-on the responsibility of your AI. Your dedicated partner, whether an agency, freelancer, or contractor, handles the development, launch, management, and maintenance of your AI solution.

Compared to in-house AI management, outsourced management usually costs less.

That’s because your business doesn’t have in-house hiring costs. You pay a monthly rate or one-time fee (depending on your service plan) and your AI partner takes care of the rest, whether it’s building a chatbot, running data analyses, or fixing a system error.

Outsourcing your AI can also help your business connect with some experienced data scientists and AI companies. You can access top talent without the cost of hiring those individuals in-house. Plus, you can work with specialized people for complex, one-time tasks.

Whether you lead your AI initiatives in-house or collaborate with a partner, know that either decision will influence your AI software costs. If you decide to keep operations internal, plan for some additional expenses. For outsourced services, expect some cost savings.

Project duration

The duration of your AI efforts will also impact how much your artificial intelligence costs.

For example, if you’re looking to build an AI analysis system in two, versus three, months, expect higher costs. Your provider (if you’re outsourcing) will have to dedicate more developers to the build, as well as more hours. If you’re taking on the project in-house, you may even have to hire more team members.

In most cases, a more in-depth AI initiative will require more time, which generates higher AI costs.

For instance, building a complete AI analysis system can encompass several stages, from a minimum viable product (MVP) to a full product rollout. That process can take up to a year in some cases. An AI MVP, for example, often takes four to six months to generate.

As you research AI software costs for your business, take into consideration the timeframe.

That doesn’t mean your company should try and push in-house or outsourced teams to build your solution faster. Or, that you should cut features that your business needs if it wants to make the most of your AI.

Instead, you should look at the duration as a cost factor and budget for it accordingly.