Cost to Build an AI Customer Service Chatbot?

Let’s start the discussion about the costs to develop a chatbot.

AI has become the forefront of modern-age personalized experiences. From healthcare to finance, and ecommerce, it has transformed how brands connect with their potential customers and understand them to deliver improved experiences. 

One of the most promising areas of AI development is chatbots and virtual assistants, streamlining customer support with human-like interactions. 56% of businesses use conversational AI, particularly chatbots, which disrupts their industry.

AI-powered chatbots have not only helped customers with seamless shopping or any other online experience but also helped businesses scale across industries. 

The growing demand for personalization, efficient customer support, and automation of manual service tasks drives the rapid growth of AI chatbots.

You can see several prominent examples of AI chatbots asking you questions and concerns whenever you land on any website. 

Understanding the growing demand and streamlining customer support operations, businesses seek an instant AI customer support chatbot, that can help them analyze their customers, their demands, and queries to boost sales and convert missed leads.

But, how do you create an AI customer support chatbot for your business? How much does it cost to build one? Let’s explore the Costs to Develop a Chatbot, factors affecting the cost, challenges, and best practices to get you started with an AI chatbot. 

By the end of this blog, you will understand how OnGraph can be your AI chatbot development partner. 

Expanding Era of AI Chatbots

The global conversational AI market is expected to soar to $169.4 billion by 2025, which reflects an impressive CAGR of  36.2%.

From fintech to eCommerce, edtech, and healthcare, AI chatbots are making strides. Here are some stats that will help businesses the needs of the hour.

• AI chatbots can save 2.5 billion work hours.
• 84% of companies foresee AI chatbots as a crucial element in customer-business communication. 
• AI chatbots report a 3x increase in sales conversions.
• Chatbot-powered lead quizzes boost performance by 20% over static forms.
• In eCommerce, chatbot-driven transactions are expected to reach a massive $112 billion. 
• By 2027, Gartner predicts chatbots will be the top customer service channel for 25% of businesses.

 

Chatbots cut response times, handling simple questions automatically and smoothly transferring complex cases to live agents. 46% of companies using AI chatbots or assistants rely on them for voice-to-text dictation.

Different Types of Chatbots- Use Cases and Costs

Each business has different demands for AI chatbots. Thus, developing different types of AI chatbots may cost differently.

Take a look at the use cases, and how much does a chatbot cost. Let’s breakdown the chatbot pricing comparison.

Chatbot Type	Description	Use Cases	Cost
1. Rule-Based Chatbots	Follows pre-set rules, providing simple answers based on keywords or commands; cannot handle complex questions or contextual understanding.	FAQs, basic customer support, and simple booking systems.	$1,000 – $2,000
2. Machine Learning (ML) Chatbots	Learns and improves over time from interactions, giving more accurate responses; requires extensive training data for better accuracy.	Advanced customer support, personalized marketing, and task automation.	$2,000 – $4,000
3. Natural Language Processing (NLP) Chatbots	Human-like responses, and understanding of context, intent, and emotion; enable more meaningful interactions.	Complex customer service, virtual assistance, healthcare, and financial advice.	$5,000 – $8,000+
4. Hybrid Chatbots	Combines rule-based and AI-driven responses; answers simple queries with rules and switches to AI for more complex issues, offering scalability for businesses.	E-commerce support, lead generation, HR support, educational platforms.	$5,000 – $10,000
5. Voice-activated chatbots	Used in virtual assistants and smart devices.	Virtual assistants, automotive systems, smart home devices, customer support hotlines.	$5,000 – $10,000
6. Contextual Chatbots	Uses deep learning to track conversation history, user details, and context, enabling highly personalized responses and memory of past interactions.	CRM, personalized shopping, healthcare monitoring, and financial services.	$5,000 – $10,000+

 

You must understand, that the cost range is just an estimation. It might vary depending on several factors. We will highlight the costs to develop a chatbot.

Factors That Affect the Artificial Intelligence Chatbot Cost

Every business wants cost-effective solutions. Thus understand what factors can impact the overall development cost of the chatbot. Here are some key factors that might elevate the AI chatbot cost.

1. Complexity of Chatbot

The Costs to Develop a Chatbot may vary depending on what type of chatbot you want for your business. The Costs to Develop a Chatbot will increase with complexity.

The basic chatbot can help you respond to simple queries and is a lot cheaper. While it incorporates advanced features and functionalities, like simulation and emotional analysis to generate human-like and personalized responses, the cost will go up. 

The Costs to Develop a Chatbot range from $1k up to $10k+ from basic to advanced, affecting the cost of chatbot for enterprises

2. Choice of Platform

AI chatbots can be integrated into multiple platforms, such as websites, apps, and social media for wider reach and to target unique audiences.

With the increasing demand for cross-platform visibility, businesses opt for multi-platform AI chatbot support. Building an AI chatbot that works well with all platforms is higher than the basic AI chatbot that can only work with a single platform. 

The cost may range between $5k to $50k depending on your choice of platform.

3. Third-party Integrations

To make the entire customer support process hassle-free, you need third-party integrations. To connect your AI chatbot to existing systems like CRM software, payment gateways, databases, chat platforms, and APIs, it will add up your development cost.

These integrations ensure that your businesses work smoothly while helping you track and manage every piece of information.

The integration cost ranges between $5k to $$30k.

4. Customizations that align with your business

Each business has different requirements for what their AI chatbot can do for them. Creating an AI chatnor that aligns with specific business needs, including features, capabilities, UI/UX, will cost you more than having a white-label AI customer support chatbot.

The cost of custom on-demand AI chatbot development ranges between $5k to $75k. But you can get your own AI chatbot for just $5k with our white-label offerings. From small UX/UI customizations to one-month free support, it covers it all. 

5. Data Compliance and Security

Where their customer information is related, security becomes the topmost priority of every business. AI chatbot analyzes history data, preferences, and behavior of customers to make smart decisions and offers personalized experiences.

So, ensuring complete security is necessary and businesses need to follow standard security and compliance rules like GDPR. adding additional security features like this will add up the Costs to Develop a Chatbot.

Integrating security from basic to advanced ranges between $2k to %30k. 

6. Customer Conversation Channels

To make your AI chatbot more interactive, it must offer different ways to interact with your customers. For example, your customer should be able to connect with you over chat, email, voice call or audio all initiated by an AI chatbot. To integrate more ways, you need to invest more.

Interaction Channels	Estimated Cost Range
Single Channel (e.g., Text)	$5,000 – $10,000
Multi-Channel (Text, Voice, Email)	$15,000 – $50,000+

 

7. Development team and location

The location of the development team also decides the development cost. Thus, you must explore your options across the globe and outsource the best and most cost-effective development team that will help you scale with sustainable solutions. 

Location	Hourly Rate Range
North America	$100 – $250 per hour
Western Europe	$80 – $200 per hour
Eastern Europe	$40 – $100 per hour
Asia (e.g., India, China)	$20 – $70 per hour

 

The cost also depend whether you want an in-house development team vs hiring a development agency. If you choose to hire your own team, you have to invest in the process from hiring to incentivizing them monthly.

But if you hire a company to do the job, it will cost less. OnGraph is known for its AI customer service chatbot development with white-label solutions. 

8. Consistent Support and Maintenance

For an app to work flawlessly, it requires consistent support and maintenance. Also, to stay ahead of trends, you need to integrate the latest tools, integrations, and technology to engage customers.

From fixing errors to updating, upgrading, and troubleshooting issues, and adding new features, it all costs your business to stay in the league. 

The cost may vary depending on the type of addition or upgrade you require. The costs may range between $5k to $15k. 

9. Train and optimize AI Models

With time new AI models are launching to work better with data analysis and generate more human-like answers. For an AI chatbot to work accurately, it is important to train and optimize your AI model to offer a personalized customer experience while providing accurate answers and insights for better decision-making.

To work with AI models, you need AI experts who can add up your hiring and skilling costs.

The cost of training and optimizing AI models ranges between $5k to $30k (per year).

Other Hidden Factors

These are the core factors that add up to the AI chatbot development costs. There are some additional development costs that you should also consider.

• Cost of prototyping and MVP
• Infrastructure and hosting costs. You can choose AWS, Azure, or GCP cloud options that decide your costs. You can choose the best AWS expertise, offering cloud-ready solutions within your budget. 
• Testing and QC costs. Testing is an important aspect that helps you understand the flow and check all functionalities of the AI chatbot. It helps you fix issues, improve performance, and reduce potential bottlenecks. Testing requires a skilled tester that adds up the costs. Also, these costs will increase with the app’s complexity.
• Licensing and subscription costs. If you choose to subscribe to services from other companies, you need to pay its monthly costs- adding up the Costs to Develop a Chatbot. 

Technology and tools costs involved in developing an AI chatbot

What technology you use defines its functionality, scalability, flexibility, and costs. Here is the AI chatbot pricing.

Technology and Tools for AI Chatbot Development	Purpose	Examples	Estimated Cost Range
Natural Language Processing (NLP) Engines	Helps chatbots understand human language, identify user intents, and extract details.	Google Dialogflow, IBM Watson Assistant, Microsoft Bot Framework, Amazon Lex	Free to $0.075 per request, custom pricing for enterprise plans
Machine Learning (ML) Models and Frameworks	Trains chatbots to improve responses through deep learning and data analysis.	TensorFlow, PyTorch, Keras, Custom ML Models	Open-source (free) to $10,000–$50,000+ for custom models
Cloud Services and Hosting Platforms	Provides the storage and computing power to run chatbots.	AWS, Google Cloud Platform (GCP), Microsoft Azure	$500–$25,000+ annually, as per usage
Messaging and Communication APIs	To communicate across popular messaging platforms.	Facebook Messenger, WhatsApp Business API, Twilio (SMS & Voice), Slack	Free (Messenger) to $0.005–$0.02 per message/voice minute
Development Frameworks and SDKs	Speeds up development by providing pre-built chatbot libraries and features.	Rasa, Botpress, Microsoft Bot Framework SDK, Botkit	Open-source (free) to $990+/month for enterprise features
Data Storage and Databases	Manages and stores user data, conversation history, and training data.	Firebase, MongoDB Atlas, Amazon RDS, Google Cloud Firestore	Free tiers available, $25–$10,000+ annually based on storage needs
Analytics and Monitoring Tools	Tracks chatbot performance, user interactions, and potential issues.	Google Analytics, Chatbase, Mixpanel	Free (basic plans) to $1,000–$5,000+ for custom monitoring

 

You can choose any technology based on your business’s requirements and costs. To choose the right one, you can take expert guidance, they will help you understand-

• Which type of AI chatbot will work for you, 
• What features will help your business scale
• What technology and tools will save you costs

If you seek expert guidance, they will also guide you on how can you reduce or optimize AI chatbot development. 

Tips to Optimize AI Chatbot Development Costs

Developing an AI chatbot is an expensive process, but with these tips and implementations, you can save significant costs without impacting the quality. 

Here are tips that you must know.

1. Choose White-label AI Chatbot Solutions 

Instead of developing your AI chatbot from scratch, choose pre-built solutions. It covers your Costs to Develop a Chatbot, you only have to pay for the customization, added features, and tailored functionality that aligns with your brand. 

2. Choose open-source tools and platforms

Free tools like Rasa, Botpress, and TensorFlow are excellent for building AI chatbots without high license fees. Using these open-source tools allows businesses to create and customize chatbots while saving money.

They are also very flexible and come with a strong support community, making them a smart choice for budget-friendly chatbot development.

Estimated Savings:

• Rasa: Saves up to 60% compared to paid tools.
• Botpress: Free Community Edition; cuts down initial setup costs.
• TensorFlow: Free to use; costs only include development time.

3. Choose MVP Approach

Launching a basic version of the chatbot, or MVP, allows businesses to include only the most essential features first. This way, they can get user feedback and make updates based on actual needs.

It also avoids spending on extra features that might not be necessary. By focusing on essentials, companies save time and money.

Estimated Savings:

• Basic MVP: Saves up to 40% on initial development costs.
• Adding Features Later: Reduces future development and maintenance costs.

4. Leverage Pre-trained AI Models

Training a machine learning model from starting is costly and consumes data and computing power. Rather than train your model, businesses can use pre-trained models from companies like Google, IBM, and Amazon. These models are already highly accurate and save both time and money.

Estimated Savings:

• Google BERT, IBM Watson: Save up to 70% on training and setup costs.
• Amazon Lex: Avoids the need to build a custom language model.

5. Use Cloud Services

Cloud platforms like AWS, Google Cloud, and Microsoft Azure let businesses adjust chatbot resources based on demand. With pay-as-you-go pricing, companies save on upfront costs and manage resources efficiently.

These services also include built-in security, saving time and money on setup and maintenance.

Estimated Savings:

• AWS, Google Cloud: Lower setup and maintenance costs.
• Microsoft Azure: Reduces expenses with scalable pricing and built-in services.

6. Use Agile Development

Agile development helps manage time and resources better by breaking the project into small, repeatable steps. This approach allows teams to adjust features based on feedback, reducing the chance of going over budget and ensuring the chatbot meets user and business needs.

Estimated Savings:

• Iterative Development: Saves up to 30% on rework and adjustments.
• Sprint Planning: Makes the best use of development time and resources.

7. Streamline Data Collection and Labeling

If custom training is needed, improving how data is gathered and labeled can save time and money. Using techniques like semi-supervised and active learning reduces the amount of labeled data needed. Partnering with data labeling companies is also a cost-effective way to get quality training data.

Estimated Savings:

• Semi-Supervised Learning: Saves up to 40% on labeling costs.
• Third-Party Labeling Services: Cost-effective for preparing data.

These tips can help you save significant Costs to Develop a Chatbot. Once your AI chatbot is ready to launch, you can start monetizing it. 

How to Monetize Your AI Chatbot? Different Monetization Strategies That Work

Generating revenue is the ultimate goal of AI chatbot development. Here are some strategies that help you generate revenue from your AI chatbot development.

Monetization Strategy	Description
1. Subscription Plans	Offer premium tiers with basic services for free, and charge for premium features via monthly or annual subscriptions.
2. In-app purchases or Transaction Fees	Enable users to purchase products, services, or virtual goods directly through the chatbot.
3. Lead Generation and Affiliate Marketing	Capture customer information and forward leads to businesses that pay per lead.
4. Sponsored Messages and Advertising	Allow advertisers to promote relevant content, products, or services through the chatbot.
5. Data Monetization	Sell insights derived from anonymized interaction data, revealing trends and customer preferences.
6. Chatbot as a Service (CaaS)	Offer your custom-built chatbot platform as a service to other businesses.
7. Freemium with Paid Features	Provide a free version of the chatbot with limited functionality and charge for advanced features.
8. Consulting Services	Offer paid consulting for the setup, customization, and optimization of the chatbot.
9. License and White-Label Solutions	Create a chatbot that businesses can white-label, allowing them to use your solution under their branding for a fee.
10. Pay-Per-Use and On-Demand Services	Charge customers for each interaction or query, particularly for high-value services like legal or medical advice.

 

You can use expert guidance to understand which strategy works well for your businesses and start curating your marketing strategies to make a wider impact.

What is the Return on Investment of Developing AI Chatbot?

The most important thing is to measure your success and revenue generated against your investment. Integrating AI chatbots within your business workflow can help you strengthen your customer relationship. 

AI chatbots offer several benefits and help you streamline your business’s workflows. Here are more returns that you will get for developing an AI chatbot.

1. Cost Savings and Efficiency Improvements

AI chatbots can save businesses a lot of money by responding to multiple customers at the same time. It helps you automate routine tasks, reducing support costs by 30%.

This savings improves return on investment (ROI), especially for businesses with high customer interactions.

2. Increased Customer Engagement and Satisfaction

The best part of having an AI chatbot is its 24/7 availability. They are available for your customers irrespective of time and location. You do not have to worry about having human support working shifts.

This availability boosts customer satisfaction and keeps them engaged. 80% of businesses plan to use chatbots for customer service in 2024 for better customer experience.

3. Revenue Generation Through Upselling and Cross-Selling

AI algorithms help you analyze customer’s preferences and purchasing behavior. It helps recommend products or services that might interest customers.

This enhances the shopping experience and can lead to increased sales. AI chatbots will drive over $112 billion in retail sales by 2024, highlighting their revenue potential.

4. Data Collection and Customer Insights

AI chatbots gather valuable information during conversations with customers. This data helps businesses understand customer preferences, behaviors, and pain points.

Analyzing this information allows businesses to improve their products, services, and marketing strategies, making it easier to target the right customers. 

5. Enhanced Lead Generation and Qualification

AI chatbots can engage visitors to your website and identify potential customers right away. They do this by asking useful questions and collecting contact information, helping businesses find promising leads early.

Chatbots can also set up follow-ups, schedule meetings, and provide information to guide interested customers toward making a purchase.

6. Improved Customer Support Metrics

AI chatbots can enhance key customer support metrics, such as Net Promoter Score (NPS) and Customer Satisfaction Score (CSAT). They achieve this by providing quick, reliable, and consistent assistance.

When customers are satisfied with support, they are more likely to remain loyal and recommend the brand to others, creating more business opportunities.

These benefits will help your business scale with the right investment.

Also Read- How to Use AIML In Chatbot Development with Python

Build Your AI Customer Service Chatbot with OnGraph

OnGraph is your go-to place for creating a strong, secure, and effective chatbot development services. Our chatbot developers will help you from the start, helping you set your goals for deployment.

Whether you need a simple chatbot or a more complex AI-driven one, we provide a solution that can grow with your needs. 

As a top generative AI development company, we take care of everything—design, development, integration, and ongoing maintenance—to ensure your chatbot keeps improving.

With OnGraph, you can create a chatbot that enhances customer service, streamlines operations and opens up new ways to earn money, such as through lead generation and in-chat purchases.

FAQs

Q. How much does it cost to build AI customer support?

The cost to develop AI customer support depends on what type of chatbot you want for your business. The cost of chatbot, from simple to complex, it can range from $1k up to $10k.

But you can launch your white-label AI customer support app for just $5k, ready to launch in minutes.

Q. Benefits of using AI customer support for your business?

• AI offers support at any time, day or night.
• Instant replies to customer inquiries.
• Reduces the need for a large support team.
• Handles many queries at once without extra resources.
• Provides uniform, error-free responses.
• Tailors’ responses are based on customer data.
• Gathers data to improve services.
• Resolves issues quickly and accurately.
• Transfers complex issues to live agents.
• AI improves with every interaction.

Q. What is the process of developing an AI Chatbot?- how to create ai chatbot

Our experts follow a strategic approach that requires the following simple steps-