Truly understanding how much does a chatbot cost means looking beyond the subscription price. In 2025, the true investment will be measured in TCO—Total Cost of Ownership—that is, the entire project lifecycle, which includes the various phases of development, maintenance, integrations, security, and data governance.
This is where the hidden costs that many companies initially overlook emerge.
The technologies available today—no-code platforms, development frameworks, and LLM models—offer different approaches, with vastly different impacts on costs, control, and management complexity. This is especially true when it comes to sensitive data: choosing an advanced platform simplifies governance, while creating a chatbot independently with an LLM, even a business version, increases liability, risk, and unpredictability of expenses.
In this article, we explore how to realistically calculate the cost of a chatbot, the elements that make up the TCO, and the technological choices that enable a truly sustainable project over time.
Estimated reading time: 9 minutes
Table of contents
What is TCO and HOW IT DETERMINES HOW MUCH DOES A CHATBOT COSTS
According to the most recent industry analyses (Gartner, Deloitte, Forrester), over 58% of the real costs of conversational AI projects aren’t apparent in the initial phase, but rather in the first year of use. This is where the concept of TCO—Total Cost of Ownership—comes in.
TCO allows you to calculate how much does a chatbot cost and how does it cost maintaining it over time, answering the question every manager should ask themselves before creating a chatbot:
“How much will it cost me not just today, but every month, every year, for the entire duration of the project?”
To truly understand how much does a chatbot cost, you need to consider all the components that impact the project, including:
- Technical infrastructure and governance: This includes servers, hosting, APIs, language models, and control tools. It determines the stability of the chatbot and defines who can access, modify, or monitor the system.
- Development and initial configuration: This includes designing flows, training the model, customizing the tone, and setting up basic functionality.
- Ongoing maintenance: This involves reviewing content, correcting errors, optimizing responses, and monitoring performance over time.
- Integration with business systems: This refers to connecting the chatbot to CRM, ERP, ticketing, e-commerce, or internal databases, which is essential for achieving real automation and personalized responses.
- Security and compliance: This includes data protection, encryption, permission management, and compliance with GDPR and internal policies to prevent legal risks and unauthorized access.
- Updates and improvements over time: This covers the evolution of the chatbot through new features, modules, languages, or optimizations based on user feedback.
- Data management: This includes collection, storage, retention, auditing, conversation tracking, and classification of sensitive information.
Items determining how much does a chatbot cost
Creating and managing a chatbot involves a series of costs that go well beyond initial development and the platform subscription. Determining how much does a chatbot cost depends largely on the chosen technology: from initial configuration to conversational flow design, from model training to integration with databases, CRMs, or other business systems.
Each solution—no-code platform, custom framework, or LLM—requires specific activities that directly impact the TCO. Maintenance costs are also added, as a chatbot exists in a constantly evolving company: new services, internal policies, commercial offerings, and processes require constant updates to maintain the accuracy and quality of responses.
Recurring operating costs, related to licensing, API usage, conversation monitoring, data storage, and reporting to continuously optimize the conversational flow, should not be overlooked.
Internal team training is also essential: monitoring, updating, and interpreting the data generated by the chatbot helps improve its performance and make it an effective tool for the company.
Finally, in 2025, the speed of technological evolution is a critical factor: continuous updates, new features, and increasingly sophisticated architectures require ongoing investments in time, resources, and expertise, which contribute significantly to the project’s true cost. In short, estimating how much does a chatbot cost means considering a complex ecosystem of initial, recurring, and strategic expenses, all of which are essential to achieving a sustainable return on investment.
How much does a chatbot cost based on the technology used?
Choosing the right technology can significantly simplify TCO and transform hidden costs into predictable expenses. No-code platforms, for example, allow you to reduce development costs, speed up releases, manage updates, and integrate AI models in a secure and governed manner. At the same time, using LLMs or customized frameworks can also be effective, but requires careful planning and oversight to avoid inflating the budget. Essentially, understanding the differences between available technologies is the first step to maximizing your chatbot’s ROI and determine how much does a chatbot cost over time.
Framework
Creating a chatbot through custom development offers maximum freedom and customization. However, it comes with significant challenges: it requires a dedicated team, development times are long, initial costs are high, and maintenance increases exponentially with the project’s complexity. This approach only makes sense if you require highly specific functionality or solutions unavailable elsewhere..
no code PLATFORM
No-code platforms currently represent the most competitive solution for creating a chatbot with controlled costs and a predictable ROI. They allow you to:
- reduce development costs, without the need for expert programmers;
- rapidly release the chatbot to the market;
- autonomously update workflows and content, without complex IT interventions;
- integrate AI models in a governed and secure manner.
Thanks to templates, automation, and integrated governance, no-code platforms offer the best balance between TCO and generated value, allowing companiese to determine how much does a chatbot cost and to scale projects without skyrocketing costs. They’re the ideal choice for those seeking speed, control, and economic sustainability.
LLM (Large Language Models)
Integrating models like GPT allows for powerful, flexible, and conversational chatbots. At first glance, it may seem like the most cost-effective route: it doesn’t require complex development and allows for rapid releases. It offers flexible responses and powerful natural language understanding.
However, the hidden costs are significant: token consumption can become unpredictable, continuous model supervision, filters, and moderation controls are required, as well as variable costs for APIs and internal resources dedicated to monitoring.
With the OpenAI for Business versions, the situation improves: data protection, compliance (SOC2, GDPR-oriented), and administrative dashboards help manage security and governance. But two key problems remain:
- Expenditure remains variable and difficult to predict;
- Vendor lock-in is strong: the company is completely dependent on OpenAI.
For this reason, relying exclusively on an LLM without a platform that controls governance, security, and costs remains risky.
How to really estimate how much does a chatbot cost
Here’s a practical 5-step model to accurately estimate your chatbot’s TCO:
- Define the objectives and context
First, clarify what the chatbot will be used for: customer support, sales, marketing, HR, or IT. The complexity of the project depends on the number of channels, languages, and features required.
- Estimate initial development costs
Consider using a no-code platform, a development framework, or a Large Language Model (LLM). Consider licensing, development hours, and customizations required for your use case.
- Estimate maintenance and upgrades
This includes periodically reviewing conversation flows, adding new content and features, monitoring the quality of responses, and adapting to changes in business processes.
- Consider integration and infrastructure
An effective chatbot must communicate with CRM, ERP, e-commerce platforms, or ticketing systems. This includes technical integration costs, hosting, storage, and any APIs for LLM models.
- Evaluate security, governance, and compliance
Data protection, permission management, GDPR, and local regulations are essential. Choosing a platform with integrated security tools reduces risks, while standalone solutions require additional resources and costs.
Data security and protection
Creating a chatbot means managing sensitive information, from customer data to conversation history, from sensitive logs to internal company information. In 2025, the difference between using a dedicated platform and developing the project “by hand” with an LLM, even a business version, is significant.
If you choose an advanced platform, data governance is already integrated: security, privacy, tracking, and auditing are automatically managed, reducing risks and simplifying the team’s work. Conversely, relying directly on an LLM means that all responsibility falls on the company: privacy, storage, retention, role management, auditing, and conversation monitoring must be designed and controlled internally.
In practice, developing a chatbot independently with ChatGPT involves greater complexity, requires a dedicated team, and significantly increases the TCO, making it more difficult to predict the costs and risks associated with data management.
Conclusion: How much does a chatbot cost in 2025?
Answering the question “How much does a chatbot cost?” means evaluating the entire project lifecycle.
The expense of a chatbot doesn’t end with the initial implementation: it’s an ongoing investment. Creating a chatbot is a strategic choice that, when supported by the right tools, can significantly reduce operating costs, speed up response times, and ease the workload of company teams.
However, the TCO (Total Cost of Ownership) depends largely on the technology chosen. No-code platforms offer predictable costs, integrated governance, and immediate scalability. Development frameworks allow for maximum customization, but come at the expense of higher costs and longer lead times. LLMs like GPT offer extraordinary power and flexibility, but they involve variable costs and more complex data management, especially without a governance platform.
With a structured and informed approach, creating a chatbot stops being a gamble and becomes a sustainable and measurable investment, capable of generating concrete value in the medium and long term.
FAQ – How much does a chatbot cost?
Total Cost of Ownership (TCO) includes not only the platform subscription or license, but also development, maintenance, integration with enterprise systems, data security, updates, and team training costs. Ignoring these hidden costs can inflate the projected budget, making the project much more expensive than it initially appears.
Beyond initial development, hidden costs include:
– Maintenance and updating of conversational flows
– Integration with CRM, ERP, or ticketing systems
– Team training and management
– Response quality monitoring and ongoing optimization
– Security and regulatory compliance for sensitive data
Considering these elements is essential to correctly estimate the cost of a chatbot and ensure a sustainable return on investment.
The technology chosen to create a chatbot has a direct impact on TCO. No-code platforms reduce initial time and costs, while development frameworks require dedicated technical teams and larger budgets for complex customizations. LLMs offer flexibility and advanced responses, but incur variable costs related to token consumption and response supervision. Furthermore, each choice impacts ease of integration, maintenance, and data security, all of which impact the project’s actual cost.rogetto.
