Agentic AI: definition, how it works, and what is at stake
Agentic AI refers to artificial intelligence systems that pursue a goal in several steps: they read a request, plan, use tools (email, business software, databases) and carry out actions, under the control of a person. Where a chatbot answers, an AI agent acts. At Blue Lemon Agent, an agent only carries out what you have authorised: decisions with legal or significant effect remain yours.
Agentic AI is an evolution of generative AI. Generative AI produces a text, an image or an answer; agentic AI uses it to accomplish a task: look up a database, fill in a form, prepare a letter, trigger a step in a process. An AI agent combines a language model, tools connected to your information system, a working memory and rules that bound what it is allowed to do.
Chatbot, automation, assistant, agent: what is the difference
- Chatbot — Answers questions in natural language; does not act beyond the conversation.
- Classic automation (RPA, scripts, rules) — Always runs the same sequence of actions on structured data; fails as soon as the input falls outside the expected frame.
- Assistant (copilot) — Helps a person inside a tool: suggests, drafts, summarises; the person keeps every action.
- AI agent — Receives a goal, breaks the work down, chooses and calls tools, chains actions and reports back; a person supervises and approves sensitive acts.
How an AI agent works: goal, tools, memory, planning, action, control
- Goal — A written, bounded instruction: what the agent must achieve, for whom, within what scope.
- Tools — The authorised connections: email, calendar, CRM or ERP, document base, telephony; each tool is declared, with strictly necessary rights.
- Memory — The useful context from one step to the next (the case in progress, your document templates, your business rules), without keeping what is not needed.
- Planning — The agent splits the goal into steps and chooses the order; for broad tasks, several specialised agents can share the steps under an orchestrator.
- Action — It reads, writes, sorts, prepares, sends; each action towards the outside is either approved by you or carried out within a scope you have authorised.
- Control — Deterministic rules (ceilings, auto-approved categories, always-human cases) and a log of the actions, defined at deployment. A ceiling enforced by a model is not a ceiling: this layer is code, not an instruction. Details on the page “How a Blue Lemon Agent agent works”.
- See the sheet “Multi-agent system for a company department”
What a Blue Lemon Agent actually does
- Automated invoice processing (purchase-to-pay) — Entering, matching, getting approval, paying: processing supplier invoices is a repetitive, high-volume process that invites mistakes. With electronic invoicing arriving, it is also a shift every company has to absorb. An AI agent takes the whole flow end to end — up to the approval, which stays human.
- AI agent for sorting and routing requests — Your agent reads the incoming request, classifies it under your categories and proposes the department to handle it, explaining what it relies on.
- AI ticket management agent (IT helpdesk) — Your agent categorises each request, proposes the applicable procedure from your knowledge base, and prepares a complete file for the cases that have to be escalated.
- AI assistant for chasing unpaid invoices by email — Your agent tracks the due dates, spots the invoices to chase and prepares the letter at the right stage of the sequence, in your tone.
- AI agent for town hall secretaries — An assistant that drafts routine correspondence and official acts, prepares deliberations and answers residents — while you keep control of every decision.
- AI for responding to tenders — Responding to a tender takes days of work: going through the specifications, writing the technical submission, gathering the documents, meeting tight deadlines. For lack of time, many companies give up on contracts they could have won. An AI agent takes on most of that work — the decision remaining yours.
- The full catalogue: AI agents for businesses (by sector and use case) and AI agents for the public sector (by role).
Limits and supervision
An agent makes mistakes about what it does: understanding, sorting, drafting. A wrong classification sends a request into the wrong queue, and that shows in the log; it cannot grant a discount above a ceiling or trigger a sending that required approval, because those decisions are not entrusted to it.
For AI systems classified as high-risk, Regulation (EU) 2024/1689 requires effective human oversight during use (Article 14) and automatic recording of events (Article 12). Most office agents do not fall into that category; the classification is made during scoping, processing by processing.
Three limits to know before starting:
- It can produce a wrong answer with confidence — Hence the cited sources, the written rules and human approval on anything that commits you.
- It does not decide — No decision with legal or significant effect is taken by an agent; every action towards the outside is approved by you or carried out within a scope that is authorised, bounded, tested before going live and logged.
- It depends on its connections — A capability that relies on a third-party tool (email, telephony, review platform) requires an account, a right or a module with that third party, and sometimes a usage-based cost, specified on each sheet and in the quote.
Choosing a first process: six criteria
- Repetitive and high-volume — The same task, several times a day.
- Rules you can write down — If nobody can say what a “good” answer is, the agent will not know either.
- Accessible data — A shared folder, software with a programming interface, a mailbox.
- A recoverable error — Start with a process where a human review is enough to correct.
- A measurable result — Time per case, response time, reminder rate.
- A responsible person — Someone who approves, reads the log and adjusts the rules.
- You can describe your process in a few minutes on “My AI agent!” and receive a personalised mock-up of the matching agent, or book a 30-minute scoping meeting.
Why agentic AI is taking off now
Model maturity, interoperability protocols (Model Context Protocol, communication between agents) and the integration of agents into everyday tools are accelerating adoption. According to a declarative Cisco survey of 7,950 decision-makers across 30 countries (press release of 27 May 2025), respondents expect 68% of their customer-experience interactions with technology partners to be handled by agentic AI within three years. These are expectations stated by technology buyers, not a measurement of usage. The point is not to endure this momentum, but to make it your own, with method.
What to remember about costs, data and exit
Cost per use
AI model tokens are the main variable part, not the only one: voice minutes, OCR, translations, SMS and third-party platform fees are re-invoiced at cost, with no margin; fixed prices do not change during the commitment. Details on the Pricing page and in Article 7 bis of the General Terms.
Sensitive data
On plans where the model is called at its publisher, a pre-processing filter pseudonymises, masks or withholds sensitive data before transmission, without guaranteeing that no transfer occurs when the processing requires it. Details on the Anonymisation filter page.
Audit trail
The agent’s actions are recorded in a timestamped way, protected against alteration, within the scope defined at deployment. Details on How an agent works.
Reversibility
Your data is returned to you in a standard format on request within thirty days of the end of the contract; the agent’s software remains licensed and is not transferred (General Terms, Articles 12 and 21).
Visibility in generative engines
AI assistants answer instead of listing links: being understood and cited by them requires clear, dated, sourced pages, on top of classic search optimisation.
Put agentic AI to work
Frequently asked questions
What is agentic AI?
AI systems that pursue a goal in several steps: they understand a request, plan, use tools and carry out actions, under human supervision. Where a chatbot answers, an agent acts.
How does it differ from a chatbot or classic automation?
A chatbot answers; an automation replays a fixed sequence of actions on structured data; an agent adapts its steps to each case, calls tools and reports back, within an authorised scope.
Can an AI agent decide on its own?
No. No decision with legal or significant effect is taken by a Blue Lemon Agent agent; acts that commit you are approved by you or carried out within a scope you have authorised, bounded and logged.
What happens when the agent gets it wrong?
The error concerns what it does (understanding, sorting, drafting) and shows in the log; it cannot cross a ceiling or trigger a sending that required approval, because those decisions are not entrusted to it. A first process is chosen among those where a human review is enough to correct.
Which process should we start with?
A repetitive, high-volume process whose rules can be written, whose data is accessible and whose errors are recoverable. “My AI agent!” offers you a mock-up from your description; a 30-minute meeting scopes it.
Editorial responsibility — Written and published under the responsibility of Ronan Le Boulaire, publishing director, President of Lindbergh Formation, the company that publishes Blue Lemon Agent (see "About us").
First published: . Last substantive review: .
Correction policy — A factual, legal or numerical error can be reported to contact@bluelemonagent.ai; it is reviewed within five working days, and any substantive correction updates the date of last review. Technical releases with no change of content do not.
This content is general information; it is not legal advice.
Sources
- European Union (EUR-Lex), Regulation (EU) 2024/1689 (Artificial Intelligence Act), — accessed on — Articles 12 and 14; CELEX 32024R1689
- Cisco, “Agentic AI Poised to Handle 68% of Customer Service and Support Interactions by 2028”, — accessed on — press release; survey of 7,950 decision-makers across 30 countries
- Blue Lemon Agent, General Terms of Sale, online version — Articles 7 bis, 12, 14 and 21
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