How much does AI cost for businesses?

AI for businesses: the three cost levels

When companies ask about the cost of AI, they often mean very different things: the subscription for an AI assistant in the browser, connecting AI to their own software, or developing a specialized AI agent. These levels differ in cost model, effort, and benefit – and can be combined well, depending on which tasks the AI is meant to take over.

To get started, licenses for a team and clear usage rules are often enough. As soon as AI is supposed to take over recurring workflows – such as extracting data from receipts, pre-sorting inquiries, or preparing quotes – integration into your systems pays off. That is where the greatest benefit usually arises, because employees no longer have to copy content back and forth between a chat window and a business application.

• Licenses: AI assistants such as ChatGPT, Claude, or Microsoft Copilot, usually per user per month
• API usage: AI integrated into your own processes, billed by consumption
• Development: integration, automation, AI agents, or custom AI software as a project
• Accompanying costs: training, data protection review, operation, and maintenance

ChatGPT for business: licenses, prices, and plans

OpenAI offers ChatGPT for businesses in dedicated Team (or Business) and Enterprise plans, billed per user; comparable models exist at Anthropic for Claude and at Microsoft for Copilot. The plans differ in administration features, usage limits, security features, and contractual commitments on how your data is handled. The providers publish current prices on their websites.

More important than the price per user is what the contract says: Is input used for training? Is there a data processing agreement? Where is data stored? You buy licenses for ChatGPT for business directly from the provider or through sales partners. Make sure you replace your employees' private accounts with centrally managed business accounts.

How much does an AI agent cost?

An AI agent goes beyond chatting: it completes tasks in several steps and uses tools to do so – for example reading emails, looking up data in the CRM, creating a draft, and submitting it for approval. The costs arise from developing the workflows and integrations as well as from AI usage, which is higher per task with agents than with a single chat reply.

Whether you use an agent based on Claude, ChatGPT, or another model depends on the task, quality, data protection, and usage costs; we compare this in a pilot with your real tasks. Control points are important: an agent should only get the permissions it needs and should execute critical actions, such as sending messages to customers, only after human approval.

Having AI software developed: when it pays off

Custom AI software pays off when a workflow is so specific that no standard product fits, when sensitive data is involved, or when AI has to reach deep into existing systems. Typical examples are the automatic extraction of data from receipts and delivery notes, the pre-qualification of incoming inquiries, or an analytics dashboard that summarizes key figures clearly and flags anomalies.

From our practice, this includes, for example, an AI-powered analytics dashboard for mid-sized companies (Mittelstand). We calculate such solutions as projects: AI automations with a clearly defined workflow start in the Starter package from €2,500, and AI agents and integrations across several systems in the Professional package from €8,000. We quote extensive AI platforms with many users and data sources individually as Enterprise projects.

Cloud costs for AI: API, your own servers, or local models

Most companies use AI models through the providers' cloud APIs and pay only for what they consume. For getting started and for fluctuating usage, that is usually the most economical option. Your own servers with powerful graphics processors are expensive to buy or rent and only pay off with high, steady demand or special requirements for data sovereignty.

A middle path is open models that are run in a European cloud or on your own infrastructure. They offer more control over data but require know-how for operation, security, and updates. We compare the options based on your use cases and calculate the ongoing cloud costs for AI before you commit to an architecture.

Free AI for businesses – sensible or risky?

Free AI access is suitable for exploring the possibilities – with non-sensitive data. For everyday work it is mostly unsuitable: depending on the provider, inputs may be used for training, data processing agreements are missing, and the company has no overview of who enters which data into which tool. On top come usage limits that are quickly reached in daily use.

The real costs of free AI therefore arise elsewhere: through data protection risks, inconsistent results, and a lack of control. A deliberately chosen business account for the teams that really use AI, combined with clear rules, is usually cheaper. That keeps the start lean yet clean – and later you can assess the benefit on solid ground.

Hidden costs: training, data protection, and maintenance

Besides licenses and development, there are costs that are often missing from calculations: training employees, the data protection review, preparing data and documents, maintaining templates and prompts, and quality control of the results. The EU AI Act also requires companies to ensure sufficient AI literacy among their staff – this too takes time and budget.

These costs are no reason to forgo AI – but they are a reason to start small and focused. A pilot with one clear use case quickly shows what effort actually arises and what benefit offsets it. How to proceed step by step is described in our guide “How to Introduce AI in a Company” – including training and involving the works council (Betriebsrat).