Introduction — €1,997 to learn AI: an investment, or a marketing product?

The promise has become a classic.

An AI course at €1,997 promises you mastery of ChatGPT, Claude, Gemini, Midjourney, Make, Zapier, AI agents, automations and prompt engineering. Within a few weeks, you would be able to save time, produce faster, automate tasks, launch an offer, improve your marketing, sell services or become more effective at work.

On paper, the need is real.

Artificial intelligence is moving into companies, jobs, office tools, social networks, marketing, customer relations, document analysis, code, content creation and day-to-day management. Many professionals feel they need to get trained, but do not know where to start.

So the question is not whether learning AI is useful. Yes, it is useful.

The real question is the price.

At €1,997, this is no longer simple curiosity. This is a serious purchase. For a freelancer, an employee, an entrepreneur or a very small company, it is a budget. So the question becomes: what does an AI course have to contain to justify that price?

And above all: can an AI course built today still be useful tomorrow, when models, tools, interfaces and methods are all changing at speed?

That is the promise Le Recul is testing here.

What we are actually testing

We are not testing one specific course bought from a single vendor.

We are testing the general promise of AI courses sold at around €1,997:

  • learn to use generative AI;
  • become more productive;
  • automate tasks;
  • build AI assistants or agents;
  • use the right tools;
  • save time;
  • grow a business or an offer;
  • pay the course back quickly.

This is a documentary and comparative test: observed public prices, advertised content, free or cheaper alternatives, real market needs, obsolescence risk and the conditions under which the price is justified.

Verdict up front: the promise is partly kept.

An AI course can be useful. But at €1,997, it has to offer far more than “here is how to write a prompt in ChatGPT”.

Quick test result

Price tested: around €1,997.

Guaranteed income: none.

Guaranteed time saved: none.

Potential value: real, if the course is applied to concrete cases.

Main risk: paying a lot for content that will be partly out of date within a few months.

Conclusion: an AI course at €1,997 can be worth it if it sells a method, support and deliverables. It becomes too expensive if it only sells information.

Why the demand is real

The need for AI training is not invented.

In France, the APEC (the association for executive employment) reported in 2026 that 29% of managers said they had been trained in AI, against 24% in 2025. The study also points out that the training on offer often remains generalist, and not tailored enough to specific jobs.

That is an important signal: professionals are using AI more and more, but many still do not know how to integrate it properly into their work.

On the regulatory side, the European AI Act also imposes a logic of AI literacy: providers and professional users of AI systems must take measures to ensure a sufficient level of AI competence among the people concerned. That does not mean everyone has to buy a €1,997 course. But it confirms that AI training is becoming a genuine professional subject.

So the market is real.

But when a market becomes urgent, it also attracts mediocre offers, recycled courses, overly aggressive promises and inflated prices.

The €1,997 price: expensive, or normal?

€1,997 is not an absurd price in professional training.

But it is not a small price either.

It is an intermediate rate: more expensive than an online course, less expensive than a long bootcamp or a proper qualifying professional programme.

To understand it, you have to compare.

There are AI courses today that are free or almost free. DeepLearning.AI offers, for instance, a short course, “ChatGPT Prompt Engineering for Developers”, available free during the beta of its platform. Coursera Plus costs 59 dollars a month or 399 dollars a year. The Google AI Professional Certificate is advertised at 49 dollars a month in the United States and Canada. On Udemy, ChatGPT or prompt engineering courses regularly appear at around 14 to 20 dollars on promotion.

At the other extreme, full bootcamps cost far more. Le Wagon, for example, lists its Data Science & AI bootcamp in Paris at €7,900. Ironhack advertises AI bootcamps at several thousand euros depending on the session. These courses do not sell “ChatGPT” alone, but a wider path: data, machine learning, projects, code, support and careers.

Between the two sits a large professional offer:

  • short generative AI courses at around €650 to €1,490 excl. VAT;
  • ChatGPT or Claude courses at around €1,490 excl. VAT;
  • prompt engineering courses at around €899;
  • AI/no-code or productivity programmes at around €997, €1,497 or €1,997;
  • longer courses with coaching at around €2,000 or more.

So the €1,997 price sits inside the market. But it is only justified if the content goes well beyond beginner level.

What you should get for €1,997

At that price, an AI course should contain, at a minimum:

  • an initial assessment;
  • a structured path;
  • job-specific use cases;
  • corrected exercises;
  • practical projects;
  • real automations;
  • reusable templates;
  • a security and confidentiality module;
  • a module on GDPR and sensitive data;
  • a module on AI hallucinations;
  • regular updates;
  • human support;
  • an active community;
  • live sessions or workshops;
  • follow-up after the course;
  • deliverables the learner can genuinely use.

In other words, you are not only paying for videos.

You are normally paying for a shortcut, a method, correction and practice.

If the course contains only pre-recorded tutorials, a prompt library and a list of AI tools, the price is too high.

What is not worth €1,997

An AI course is not worth €1,997 if it amounts to:

  • learning to create a ChatGPT account;
  • explaining what generative AI is;
  • handing over 100 prompts to copy and paste;
  • showing how to write an email with ChatGPT;
  • presenting Midjourney, Canva, Notion AI or Perplexity on the surface;
  • selling a list of tools;
  • showing automations without having you build them;
  • promising you will “make money with AI” with no real case;
  • recycling old videos;
  • giving “lifetime” access with no real updates.

That kind of content already exists for free, or for a few tens of euros.

At €1,997, the value must not be in the raw information. It has to be in the application.

The big weakness of AI courses: obsolescence

This is the point many vendors play down.

An AI course ages fast.

Very fast.

An Excel course can stay useful for years. An accounting course keeps a stable base. A management course evolves, but its principles do not change every three months.

AI moves far more quickly.

Models change. Interfaces change. Prices change. Usage limits change. Tools disappear. AI agents evolve. Prompting methods change. No-code workflows break. APIs get updated. Old screenshots become wrong.

Google indicates, for example, in its Gemini API notes that some Gemini 2.0 models were retired in June 2026, with a recommendation to use more recent ones. Anthropic regularly publishes new generations of Claude. OpenAI updates its models and its prompting recommendations. Even the way you talk to a model evolves: OpenAI now recommends avoiding certain older, overly rigid prompt styles when they add noise or make answers mechanical.

So a frozen AI course is dangerous.

A course that was very good in 2024 can be average in 2026. A course that is decent today can become partly obsolete tomorrow.

The problem is not that everything becomes useless. The principles hold: frame a task, give context, verify, test, iterate, measure. But the precise recipes age fast.

A course selling “the best ChatGPT prompts” is fragile.

A course teaching how to think, test, build and update an AI workflow is far more durable.

And verification is not an optional extra. We saw what an unverified model does to ordinary office documents when Microsoft measured how AI silently damages files.

The real subject: prompt engineering, or a way of working?

In 2023, many courses sold prompt engineering as a magic skill.

In 2026, that is not enough.

Knowing how to write a good prompt is still useful. But the real value has moved.

Today, what you mainly need to know is how to:

  • choose the right use case;
  • supply the right context;
  • verify the answers;
  • organise your documents;
  • build a knowledge base;
  • connect tools;
  • automate a process;
  • create a specialised assistant;
  • measure the time saved;
  • protect data;
  • keep a human in the loop.

This is no longer just “talking to ChatGPT”.

It is integrating AI into a real working system.

So a serious AI course has to go beyond the prompt. It has to teach you how to turn a real task into a reliable workflow.

Generalist AI courses: useful, but quickly limited

A generalist course can be useful for a complete beginner.

It can help you understand:

  • what generative AI is;
  • what a model can and cannot do;
  • how to structure a request;
  • how to verify an answer;
  • which tools exist;
  • how to save time on simple tasks.

But at €1,997, a course that stays too generalist becomes hard to defend.

Why?

Because the basics are already available free or nearly free. Google, OpenAI, DeepLearning.AI, Coursera, YouTube, official blogs and public documentation already let you acquire a lot of the fundamentals.

So a beginner can learn the basics for €0 to €100.

What justifies €1,997 is personalisation.

If the course does not adapt to the learner’s job, level and goals, the price is fragile.

Job-specific AI courses: far more interesting

The most solid courses are the ones targeting a precise use.

Examples:

  • AI for owners of very small and mid-sized companies;
  • AI for sales people;
  • AI for HR;
  • AI for lawyers;
  • AI for restaurant owners;
  • AI for content creators;
  • AI for freelancers;
  • AI for customer support;
  • AI for marketing;
  • AI for document analysis;
  • AI for automating admin;
  • AI for developers;
  • AI for agencies or e-commerce.

Why is that more interesting?

Because the value comes from the context.

A restaurant owner does not need to “master AI”. They need to handle their product sheets, their customer replies, their schedules, their reviews, their social posts, their menus, their hiring or their internal procedures better.

A sales person does not need 200 prompts. They need a workflow to qualify prospects, prepare follow-ups, summarise calls and personalise their messages.

A company director does not need to become a Claude, ChatGPT or Gemini expert. They need to identify the expensive, repetitive or badly executed tasks in their company, then see where AI can genuinely help.

A good AI course does not start from the tool. It starts from the problem.

We put exactly that reasoning to the test on one of the most heavily sold AI promises: how many real leads automated AI prospecting actually produces.

AI automation: the most interesting promise, and also the riskiest

Many €1,997 courses put automation front and centre.

That makes sense. This is where the value can be real.

Automating monitoring, reporting, an email reply, an information extraction, a document creation or a sales preparation can save time.

But AI automation is also the ground where promises become dangerous.

A badly designed automation can:

  • send out wrong information;
  • use sensitive data;
  • produce false answers;
  • break when an interface changes;
  • create dependency on one tool;
  • give an illusion of reliability;
  • cost more time than it saves.

So a course promising “automate your business with AI” absolutely has to teach:

  • the limits;
  • the errors;
  • the tests;
  • the logs;
  • human validation;
  • maintenance;
  • confidentiality;
  • hidden costs;
  • failure scenarios.

If it only shows Make or Zapier workflows that shine in a demo, that is not enough.

AI agents: beware the magic word

In 2026, “AI agent” has become a selling phrase.

Many courses use the term because it carries an impression of modernity: sales agent, support agent, HR agent, monitoring agent, prospecting agent, the agent that works while you sleep.

The subject is real.

But it is often oversold.

A reliable AI agent is not just a chatbot with a name.

You have to define:

  • its role;
  • its sources;
  • its tools;
  • its limits;
  • its permissions;
  • its success criteria;
  • its guardrails;
  • its logs;
  • its validations;
  • its failure cases.

A course that explains this can have value.

A course selling “build your AI agent team in a few clicks”, with nothing on errors, hallucinations, access rights and maintenance, is too light.

The gap between what these tools promise and what they complete on their own is exactly what we followed when AI tools stopped answering and started acting, and what our AI assistant ranking keeps measuring.

The payback calculation

At €1,997, the course has to be paid back one way or another.

The simple calculation:

If your time is worth €25 an hour, you need to save roughly 80 hours to pay back €1,997.

If your time is worth €50 an hour, you need to save roughly 40 hours.

If your time is worth €100 an hour, you need to save roughly 20 hours.

So the course becomes profitable if it genuinely lets you gain:

  • 2 hours a week for 20 weeks at €50/h;
  • or 4 hours a week for 10 weeks at €50/h;
  • or an automation that removes an expensive repetitive task;
  • or a new billable offer;
  • or better sales execution;
  • or fewer errors;
  • or faster production of content, quotes, analyses or documents.

But if you watch the videos without implementing anything, the return is zero.

AI can save time, but only if it is built into a real task.

A study by the Federal Reserve Bank of St. Louis reports that generative AI users said they saved on average 5.4% of their working time, which is about 2.2 hours a week for a 40-hour week. That is useful. But it is not magic.

At that rate, a €1,997 course has to be applied seriously over several months to pay for itself.

The prices you can find on the market

Here is a realistic reading of observed prices.

€0 to €100: introduction, short courses, prompt basics, discovering ChatGPT, free resources, official documentation, YouTube, DeepLearning.AI, small Udemy courses.

Good for: starting out, understanding the basics, testing at no risk.

Limit: little or no support, not necessarily fitted to your job.

€100 to €500: mini-courses, short workshops, introductory training, replays, prompt packs, entry-level programmes.

Good for: learning the basics and a few practical cases quickly.

Limit: watch out for products that are too superficial.

€500 to €1,000: structured courses, several modules, sometimes a community, guided projects, lifetime access, announced updates.

Good for: professionals who want to go further without paying for a large programme.

Limit: quality depends heavily on the trainer and on the updates.

€1,000 to €2,500: professional courses, CPF/OPCO funding (the French individual training account and sector training funds), support, workshops, job-specific cases, automations, certification, coaching.

Good for: freelancers, directors, employees and teams who want to apply AI to their own activity.

Limit: the price is hard to justify if the content stays generalist.

€4,000 to €8,000 and above: AI/data bootcamps, development, machine learning, data science, heavy projects, career support.

Good for: retraining or a serious technical step up.

Limit: this is no longer a simple “use ChatGPT” course, it is a full professional path.

So in which cases is €1,997 acceptable?

€1,997 is acceptable if the course includes:

  • genuine support;
  • live sessions;
  • project correction;
  • job-specific cases;
  • automations built during the course;
  • frequent updates;
  • human support;
  • usable templates;
  • an active community;
  • concrete examples;
  • an adaptable method;
  • help with implementation.

In that case, you are not just paying for content. You are paying for acceleration.

But €1,997 is too expensive if the course rests mainly on:

  • pre-recorded videos;
  • generic prompts;
  • tool tutorials;
  • old screenshots;
  • income promises;
  • artificially inflated bonuses;
  • an inactive community;
  • no correction;
  • no updates;
  • no real deliverable.

The good signs before you buy

Before paying, you should check:

  • the date of the last update;
  • the detailed syllabus;
  • the real number of hours;
  • the share of practice;
  • the presence of job-specific cases;
  • the number of live sessions;
  • support after the course;
  • examples of deliverables;
  • the refund policy;
  • verifiable reviews;
  • the trainer’s identity;
  • the trainer’s actual skills;
  • the tools used;
  • the planned updates;
  • the limits, clearly stated.

A good AI course vendor should also explain what the course will not do.

If they only promise “save time and make money thanks to AI”, be wary.

Red flags

Very bad signs:

  • “Become an AI expert in 7 days”
  • “Make money with ChatGPT”
  • “Launch your AI business with no skills”
  • “1000 ready-to-copy prompts”
  • “Automate your company without lifting a finger”
  • “Replace an employee with AI”
  • “Lifetime access” with no evidence of updates
  • “Eligible for CPF funding” used as the main argument
  • a high price with no clear syllabus
  • vague testimonials
  • no demonstration of a deliverable
  • no mention of limits
  • no mention of GDPR or confidentiality
  • no mention of hallucinations
  • no mention of maintenance

CPF, Qualiopi (the French training-quality label) or OPCO funding do not guarantee that the content is worth its price. What they mainly indicate is an administrative and funding framework.

A course can be eligible for funding and still be mediocre.

The real content to insist on

A good AI course has to leave you with something concrete.

Not just “I understood ChatGPT”.

But:

  • a prompt library fitted to your job;
  • a structured knowledge base;
  • a configured AI assistant;
  • a production workflow;
  • a monitoring system;
  • a verification process;
  • a tested automation;
  • a reporting template;
  • security rules;
  • a method for keeping it up to date;
  • a 30-day application plan.

Without a deliverable, an AI course stays theoretical.

And theory alone is not worth €1,997.

AI courses and income: beware the promise

Some courses imply that learning AI will let you create an income quickly.

It is possible, but not automatic.

You can sell AI-related services:

  • automation;
  • content creation;
  • chatbots;
  • internal training;
  • AI audits;
  • tool integration;
  • document analysis;
  • monitoring;
  • customer support;
  • visual generation;
  • process optimisation.

But learning a few prompts is not enough to sell those services.

To get paid, you also need to:

  • understand the client’s need;
  • deliver a reliable result;
  • handle the data;
  • know how to maintain the system;
  • prove a gain;
  • price it correctly;
  • provide support.

So an AI course that talks about income has to show real cases, deliverables, limits and a commercial method. Otherwise it is mostly marketing.

Our Le Recul verdict

The promise is partly kept.

Yes, an AI course can be worth money.

Yes, €1,997 can be justified in some cases.

Yes, AI can save time.

Yes, automation can improve a business or a job.

But no, €1,997 is not justified just to learn how to use ChatGPT.

No, a prompt library is not enough.

No, a frozen AI course does not keep its value for long.

No, a certification or CPF funding does not prove the real quality of the content.

The real value of an AI course in 2026 comes down to four things:

  1. application to the job;
  2. corrected practice;
  3. updates;
  4. concrete deliverables.

Without those four, the price is fragile.

Conclusion — at €1,997, you should not be buying prompts

The right instinct is simple: at €1,997, you should not be buying information.

The information is already available everywhere.

You should be buying an operational transformation.

A good AI course has to help you move from “I try ChatGPT now and then” to “I have a reliable system that saves me time on specific tasks”.

It has to teach you to think of AI as a working tool, not as a magic wand.

It also has to teach you to stay up to date, because AI changes too fast for frozen content to be enough.

Our final verdict: an AI course at €1,997 can be a good investment if it is practical, job-specific, supported and updated. But if it mainly sells tutorials, prompts and a promise of quick income, the price is overstated.