Les Services IA à 3k€ minimum que les PME achètent vraiment (comment les trouver)

This video will demonstrate how to identify and sell AI services to businesses in 2026, focusing on a methodology to pinpoint tasks that incur significant costs for companies, which can then be replaced by AI solutions. These solutions can be sold for between €3,000 and €10,000. The presenter, Simon de Lima, has three years of experience in AI and will share a real-world case where a company saved over €16,000 using AI. This approach contrasts with the common, often misguided advice found on YouTube, which frequently focuses on buzzwords and selling "AI agents." The core principle is not to sell an AI agent, automation, or infrastructure, but rather to sell the *suppression of a cost line*. Businesses have fixed and variable costs. While variable costs are harder to influence, fixed costs, paid monthly, represent opportunities for AI intervention to drastically reduce them, thereby increasing margins and fostering growth. A cost line is any recurring expense, such as an assistant spending hours on copy-pasting, monthly penalties due to poor client follow-ups, or sales representatives losing time re-qualifying leads instead of selling. These are tasks essential for the business but can be done better or differently. The key distinction is that you are not selling an innovation or a "nice-to-have" cool new technology. Instead, you are replacing an existing expense. For example, replacing a €4,000 monthly expense with a €600 monthly AI solution directly impacts a company's expenditure sheet. French SMEs, facing increasing costs, administrative pressure, and fiscal burdens, are desperate to save money. In 2025, over 68,000 businesses went bankrupt. Therefore, any proposition that eliminates €40,000 in annual costs will be readily accepted. A common mistake made by those entering the AI field is believing they need to be highly technical, mastering APIs, code, models, and various tools. However, what truly matters is understanding a company's income statement—where money comes in and where it goes out. The ability to identify where money is being spent unnecessarily or where revenue could be multiplied with an AI system is paramount. This involves asking three specific questions to a business leader to pinpoint these wasteful expenditures. This is a business analysis job, not a developer's task. Business owners are not interested in the technology used (e.g., Cloud Code); they care about cost savings, increased margins, and business growth. The presenter, with over three years in AI and experience running two agencies, including Wolf, emphasizes that companies don't care about technical prowess. They want to discuss numbers, economics, and margins, not new prompts or technical details. This requires adopting a businessman's mindset. All businesses have "leaks"—areas of inefficiency where money is spent unnecessarily. Many leaders, accustomed to these leaks, no longer perceive them. Your role is to identify these hidden inefficiencies. Given that only 24% of French small and medium-sized businesses use ERP software, leaks are pervasive, contributing to the high bankruptcy rate. AI agencies are there to help, not to invent powerful chatbots with advanced models. There are three criteria for identifying these leaks: 1. **Repetitive tasks:** These occur daily, weekly, or with every new client. If a task is occasional, it's not a leak; if it's recurring, it's an ongoing expense and thus a leak. 2. **Expensive tasks:** This includes salaries for employees performing automatable tasks, where their salary represents a leak because they could be doing more valuable work. It also includes the time lost by the manager or team members on tasks they shouldn't be doing. 3. **Blocking tasks (opportunity cost):** This is the most differentiating criterion. It refers to what these tasks prevent the business from achieving. For example, a sales representative spending two hours daily on reporting instead of prospecting for new clients represents a significant lost opportunity for revenue growth. The cost of this unperformed, value-adding task must be calculated. To identify these leaks, you ask three key questions to the business owner: 1. "What is consuming your time right now?" This helps pinpoint where time is being lost. 2. "What causes these leaks?" This delves into the root causes of inefficiency. 3. "If you had 10 more hours a week, what would you do with them?" or "If you could eliminate/delegate this task, what would you do instead?" This question directly uncovers the opportunity cost, revealing what valuable activities are being sacrificed. Let's look at a real-world case involving Adrien, a member of Wolf who specializes in mortgage brokers. Adrien secured a deal for €5,185 in development and installation fees, plus €395 per month for 12 months for maintenance and updates, totaling €9,925 over a year. The client was an independent mortgage brokerage with three people: the manager, an administrative assistant (paid €2,400 net, costing the employer around €4,000 with charges), and a junior sales representative. The firm had an annual turnover of approximately €280,000, handling about ten cases per month, with each case generating around €2,800 in commission. The company was stable but had plateaued for two years, risking erosion of its earnings due to inflation and rising costs. Adrien identified a major leak: the administrative task of compiling client files. When a new client comes in, numerous documents are required (ID, pay slips, tax notices), and clients frequently forget to send documents, send incorrect ones, or provide blurry photos, leading to repeated follow-ups. This delays the process, causes stress for the client, and risks losing the client to competitors. The direct cost of this leak was significant: the assistant spent 60% of her time on this single task of chasing and compiling documents. This means roughly €2,400 of her salary (or €4,000 for the employer) was spent on collecting PDFs. Furthermore, two cases per month were delayed, leading to one lost commission of €2,800 every three months, totaling €40,000 per year in lost revenue. This calculation combines salary, lost commissions, and other associated costs. The opportunity cost was also substantial. When Adrien asked the manager what he would do with 10 extra hours a week, the manager stated he would engage in networking with notaries, real estate agents, and wealth management advisors to build a network of business providers and increase the firm's turnover. Instead, he was constantly chasing documents. This demonstrates that the client was missing out on significant growth opportunities. Adrien was not selling an AI innovation; he was selling the elimination of a costly leak. The client was paying €2,400 for this task and would now pay €395 per month for the AI solution. Once a problem is identified and quantified, the next step is to choose the right AI solution. There are several types of AI services, not just "AI agents" or "chatbots": 1. **Microsas:** A simple tool with a single function for a specific problem, ideal for companies wanting a proprietary tool. Costs range from €3,000 to €15,000, plus a monthly subscription. 2. **AI Agent:** A virtual collaborator for a precise mission, suitable for partially automating a single position. Costs range from €2,000 to €8,000, plus maintenance. 3. **AI Infrastructure:** Multiple AI agents working together, human-controlled via an interface. This is what Adrien chose. Ideal for SMEs or mid-sized companies with a complete process to transform. Costs range from €8,000 to €25,000. 4. **RAG Systems (Retrieval-Augmented Generation):** Interrogating an internal database for reliable, sourced answers. Costs €5,000 to €20,000. 5. **Audits:** A complete diagnosis before action, for leaders wanting to know where to start. Costs €100 to €8,000. 6. **Training:** Training client teams or managers to implement solutions themselves. Costs €100 to €5,000 per day. 7. **AI Automations:** Eliminating specific, highly repetitive, linear tasks with high volume. Costs €800 to €5,000. The choice of solution depends on the context, client needs, budget, data volume, and work habits, not on YouTube trends. The critical mistake is choosing the "vehicle" (the AI tool) before understanding the "problem." Instead, identify the client's problem first, then select the most appropriate solution. This approach is faster, more sensible, and more likely to result in a "yes" from the client. In Adrien's case, an **AI infrastructure with a dedicated interface** was chosen. A simple automation for reminders was too limited because client documents come in various formats, require judgment (e.g., blurry photos, incorrect dates). A standalone AI agent was too fragile due to multiple steps, interconnected tools, and various processes (reception, classification, verification, reminders, validation). A generic microsas was too standard, as it needed to adapt to the specific brokerage's workflow and financial products. The infrastructure was chosen because the problem was multi-step, the client wanted to retain control, and it offered long-term defensibility, being deeply integrated with client-specific data, making it resistant to being replaced by a generic LLM. Adrien developed this using Claude Code, a natural language tool, without requiring a team of developers or extensive experience. The implementation process spanned six weeks: 1. **Week 1: Audit.** Adrien visited the broker, asked the three key questions, mapped the company's processes, quantified the leak and opportunity cost, and gathered exact figures. 2. **Week 2: Sales Preparation.** He prepared a proposal comparing current costs with post-AI costs, highlighting the savings. The client, seeing the clear financial benefit, immediately signed. 3. **Week 3: Development Preparation.** He defined the technical solution: integrations, interface, database, all prepared with Claude Code. 4. **Week 4: Development.** He guided Claude Code using natural language, allowing the AI to develop, test, correct, and iterate until the solution took shape. 5. **Week 5: Client Iteration.** A first version was presented, tested with the client, adjustments were made, and then it moved to final validation. 6. **Week 6: Production.** The solution was deployed. Immediately, the client saw results: no more manual follow-ups by the assistant, documents automatically classified, and files completed in 4 days instead of two weeks. The client's previous cost was €3,300 per month, plus €14,000 per month in uncaptured revenue, totaling €17,000 in costs. After Adrien's solution, factoring in setup fees and solution costs, the client saved €16,000 instantly. Adrien, by securing just three such clients, could earn a significant recurring income. The moral of the story is to focus on solving problems and suppressing costs, not on inventing new technologies. The methodology is consistent: