Artificial Intelligence is already changing how different sectors operate. Businesses and organizations can now integrate AI technology to enhance their internal operations. Through AI, businesses can track customers’ behaviors and identify appropriate marketing approaches to use to reach out to a specific audience. However, installing AI into your system to enhance operations isn’t just something you wake up one day and decide to do. It takes processes, from understanding the AI models and functioning of AI to optimizing AI to meet your target objectives. This means you must have a set budget to meet all the processes.

With many industries already embracing machine learning, it can be quite hard to estimate the costs of the processes. Keep reading this guide to get useful insights on AI development costs and how you can embrace the technology to scale your business to higher limits.

Factors that influence AI development cost

The cost of AI development varies depending on a number of factors. It all starts from the main concept of why you need the AI technology in your business, features that will enable the AI technology to perform specific tasks, and the teams working on the project, among many other factors. Below are some of the main considerations of factors that will influence the cost of AI development:

AI type

Based on your company’s requirements, you can go for varied AI software solutions such as:

Chatbots – The purpose of chatbots is to automate processes and enhance customer interactions, thus helping your business grow to higher limits. You can integrate chatbots into your websites and varied social media platforms. Through chatbots, customers get useful insights and recommendations for products, services, and event updates. In fact, chatbots create a convenient platform for customers to buy products and services.

Analysis systems – This is a sophisticated system that helps analyze, interpret, and take action from data generated from your business performance. Especially when you want to make data-related decisions on sales and marketing approaches, analysis systems will come in handy. Analysis systems will improve advertising and marketing strategies, which in turn maximizes productivity.

Virtual assistants – Virtual assistants play a key role in managing and completing daily tasks to maximize productivity while saving time. Examples of mainstream virtual assistants include Google Assistant, Siri, and Cortana. However, depending on the dynamics of your business processes, you might require customized virtual assistants to respond to employee or customer requests.

The AI solution you select for your business will impact the overall cost of AI development. For instance, it will cost you at least $35,000 to build a customized analysis system, while it will cost $60000 to create a customized chatbot.

Project type

Depending on the nature of your project, you can opt for a custom-built or a pre-built AI solution.

For instance, you can select TARS, HubSpot, or Drift AI solutions if you want a pre-built chatbot integrated into your system. Ideally, custom-built solutions are expensive compared to pre-built solutions. However, this doesn’t mean to shift your focus, especially if you want custom-built solutions. You only need to re-evaluate your budget and plan for what you want.

AI features

Different AI solutions or business dynamics require different features, and this will affect the overall AI development costs.

For instance, if you want a customized chatbot with the capabilities of integrating your content management system, you might need to select a highly-priced plan with all the required features.

Similarly, a customized data analysis system that incorporates the best AI software will attract more charges. Ideally, if you want a solution that will meet all your business needs, as far as security is concerned, then you will have to plan for a higher budget to get good returns.

AI management (type of team)

Of course, you will have to choose a team that will handle AI development processes. The type of team managing the whole process, from developing, launching, managing, and updating, influences the overall cost of AI development.

• In-house AI management:

With in-house development, the team handles everything, from developing, launching, managing, and updating. This implies that you must have all the professionals required for different AI development phases under one roof.

Ideally, maintaining an in-house team is quite costly when compared with the outsourcing model. An in-house team approach attracts extra expenses, including hiring costs, employee benefits, and employee salaries.

The best element about hiring an in-house team is that you will be working with a team that understands the nature of your business, brand identity, and end-users of your products or services. This makes it easy for the team to tailor the AI development processes to meet the objective of your business and the needs of the end-user, all at the same time. Besides, an in-house team understands the best AI solution for your business; hence, they can advise on the appropriate choices that will scale your business higher.

• Outsourced AI management

Outsourcing an AI development team is the exact opposite of an in-house team. With this model, you simply engage a dedicated development team partner, a contractor, an agency, or a freelancer who handles the AI development processes from the development stage to launching, management, and maintenance.

The outsourcing model is less costly when compared with the in-house team because this model doesn’t attract extra costs such as hiring costs and employee benefits. Depending on the plan you choose, you can pay monthly only once, and the AI development partner takes care of the rest.

One good thing about the outsourcing model is that your business can land in the hands of professionals who understand the market dynamic and the latest technologies and resources that can scale your business higher. This means you get experts to handle your project without spending more! Besides, you can get highly qualified people for your project, especially if your project is quite complex.

In any case, selecting an in-house team or an outsourced team to handle your AI development processes will influence the overall AI development costs.

Project duration

The timeframe you need to have your AI development process finished affects the overall development costs. The shorter the time frame, the more the costs, and the longer the time frame, the less the costs.

If you need your project within a shorter timeline, it means the development team will dedicate more time and resources to concentrate on your project, especially when outsourcing a development partner. Still, if you are using an in-house team yet you want the project within a shorter time frame, you will have to hire more experts, hence the extra charges.

Therefore, as you budget for your AI development process, always factor in the time elements. Don’t cut off some useful features just because you want the project done. Still, you shouldn’t push the team to hurry up the project as they might skip some useful phases. It is better to spend more but get satisfying results that will create a positive impact on your business.

The complexity of an AI solution you’re working on

Understanding AI dynamics, especially for people who don’t have technical knowledge of the whole concept of technology, can be complex. That is why developers should aim at creating a seamless and easy-to-use AI solution.

Elements such as a cloud-driven back end, APIs supporting integration with other systems, ETL or streaming tools, and other user interfaces are what define proper software.

Solutions such as chatbots, as described previously, may not require a complex process to integrate them into the system. However, an AI infrastructure showing your whole business from an angle is a complex process.

Another challenge comes in when scaling the AI system to other use cases. The process is quite complex, and that is why many organizations fail at this stage.

Therefore, an AI solution that entails a complex process will attract more resources and costs, hence affecting the overall AI development cost.

Use cases of AI

There are many use cases where an organization can integrate AI systems into business operations. Below are the top five cases where AI is applicable in an establishment.

• Personal Assistants

Siri, Google Home, and Amazon Echo are among the most common personal assistants. Did you know that they are just softwares and devices programmed to work just like a personal assistant could? Ideally, they only require voice commands to operate smoothly.

They are made with complex programming approaches such as pattern recognition, machine learning, & NLP- natural language processing, which enable them to perform specific tasks.

• Market Research

Everyone, especially entrepreneurs, knows that market research is a crucial step toward making viable decisions on matters concerning business trends and patterns. IBM Watson is one of the best examples here. It is an AI-powered tool that handles market research. It gives reliable tools and solutions that can help a business grow incredibly and overcome any possible challenges that can make a business fail.

• Sales

Every business’s dream is to make as many sales as possible. Besides, a business that makes sales every day has the potential to grow and scale to higher limits. With AI, business owners can optimize their business to sell more compared to traditional approaches.

A reliable AI solution can help answer all prompts from lead generation, help a business stay ahead of the competition, & make incredible sales. AI also has the capability to predict future market trends based on customer behaviors, and this can help a business in making viable decisions.

• Robotic Process Automation

Robotic process automation is a technology that facilitates processes just like humans would. However, the interaction is between digitalized systems and software. These processes are effective in navigating through the system, extracting data, and screen reading, among other tasks in an organization. They are fast, and they maximize productivity while saving on costs and delivering accurate results that can help the organization.

• Fraud Detection

Fraudulent or money laundering activities are common among many business setups. Machine learning, being a branch of AI, has the ability to sense any uncommon activity as far as money and other business resources are concerned. PayPal is one of the best examples. Being among the top brands that deal with money transfers, PayPal uses machine learning and artificial intelligence technologies to sense and block any fraudulent activities.

Tips to help you cut AI development costs

Once you have set a budget for AI development, you can review the following tips, and you might end up saving some extra money:

• Get feedback from stakeholders

Before you initiate the process, get in touch with external and internal stakeholders to get a clear overview of the exact processes and strategies to ensure the AI solution will bring a positive impact to the business as a whole.

• Define priority use cases.

Determine the product prioritization framework when selecting cases where to apply AI solutions and bring value to the business. These use cases will help determine other steps and procedures to take.

• Select the optimum technology stack

You can incorporate off-the-shelf, open-source, and custom-made components to create a vendor-agnostic solution while minimizing overall AI development costs. Don’t forget to keep the focus on UI/UX design. A User-friendly interface will simplify the interaction between AI and stakeholders to get valuable insights while minimizing costs.

• Prepare data subject to AI-driven analysis

Get the appropriate information and assess it from different angles to ensure it meets the required standards. This requires you to use normalization, preparation, and collection of data techniques.

• Create an MVP of the AI solution

Build a minimum viable product based on the use cases previously defined. The MVP will enable you to evaluate and assess the viability of your concept and if it will impact the business positively. Besides, an MVP will enable you to check areas that need improvement and areas that need more work to avoid reworking the processes when the process is already over, thus cutting costs.

• View AI implementation as a work in progress

After the AI solution is ready, you will not get accurate results at the start. Therefore, ensure there is human supervision as the AI system gets used to the procedures. Therefore, keep on acquiring feedback from stakeholders to determine where to make viable changes that will maximize productivity.

How much does artificial intelligence cost?

Having described more insights about AI development, the main question is the cost of the whole AI development process.

While it might be hard to state the exact cost of AI development, especially based on the factors described above, the AI development cost ranges between $35000 to $50,000 for all the processes. In any case, the price can even be lower, depending on the dynamics and features of your AI solution requirements.

What is the future of AI?

The AI market is set to reach $554.3 billion by 2024. The whole market revolves around hardware, software, and services. Therefore, it is upon a business to determine which area needs AI solutions and the processes necessary. This prediction shows potential growth in the AI industry as many businesses are now incorporating AI technology in their operations.

The AI technology is projected to contribute up to $15.7 trillion to the world economy.

Conclusion

AI is transforming many businesses and sectors around the world. Business operations, processes, and productivity have improved and become faster thanks to AI technology.

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