AI agents or classic automation: what do you need?

Precise definitions

Classic automation (rule-based or deterministic flow): a sequence of fixed steps and conditions of the type 'if X happens, do Y'. Given the same input, it always produces the same output. It's built with workflow tools, scripts or integrations between systems.

Language model (LLM): a system trained to generate text from text, useful for drafting, summarising, classifying or extracting information from unstructured documents. It doesn't execute actions on its own; it only processes and generates content.

Agent with tools: a language model that, besides generating text, can decide what action to take (query a database, send an email, create a task) and chain several steps together without a fixed, predefined script. Its output can vary even when the input is similar.

Comparison table

Neither option is better in absolute terms: it depends on whether the process is predictable or variable, and how much risk you can accept if the system gets it wrong.

Decision tree

To choose between the two options, answer these questions in order:

• —1. Does the input always follow the same format, and can the rules be written explicitly? If so, use classic automation.
• —2. Is the input free text, varied documents or conversations (emails, PDFs, messages)? Then you need a language model to interpret it, even if the rest of the flow stays classic.
• —3. Does the system need to choose between several possible actions depending on context, without a fixed script? This is where an agent with tools pays off, always with clear limits on what it can do without supervision.
• —4. Would an error have serious financial, legal or customer-relationship consequences? If so, reduce the agent's autonomy and add human validation before the final action is executed.

Hybrid architectures: the most common setup in SMEs

In practice, most good solutions combine both approaches: a classic flow manages the skeleton of the process (receive, validate, file, notify), and a language model or agent only handles the stretch where text needs interpreting or a one-off decision needs making.

For example, when logging supplier invoices: a classic flow detects the new email and saves the attachment; a language model reads the PDF and extracts the data; and another classic step validates it against fixed rules (maximum amount, known supplier) before pushing it into accounting. The agent only steps in where it adds real value.

Controlling costs and hallucinations

The cost of an agent isn't just implementation: every query to the model has a per-use cost that needs estimating against expected volume, and it should be reviewed periodically so it doesn't spiral as volume grows.

To reduce hallucinations (incorrect answers or decisions generated with an appearance of certainty), the agent should be limited to the information sources you give it (not left to 'invent' from general knowledge), asked to cite the source of every extracted piece of data, and paired with automatic or human validation before the action has any real effect (sending money, replying to a customer, changing a record).

When an agent is a bad idea

An AI agent isn't the right solution in these cases:

• —The process is simple, stable and has few variations: a classic flow solves it at lower cost and without hallucination risk.
• —There's no time or budget to supervise it in the first few months: an unsupervised agent can quietly accumulate errors.
• —Decisions directly and irreversibly affect money, sensitive data or regulatory compliance, without an intermediate human validation step.
• —Usage volume is so low that the agent's design and maintenance cost is never recovered through time saved.

How to decide well in your SME

The best starting point is to map the real process (inputs, decisions, outputs) before choosing the technology. Often it turns out that 80% of the process is classic and deterministic, and only a small stretch needs text interpretation or judgement—that's where it's worth introducing an agent.

At AurIA42 we run this diagnostic with no obligation in a free 2-hour session, and if a solution needs building, we offer automations from €600 and functional pilots in 4 weeks from €4,000.