Estimated reading time: 11 minutes
An SME gets the most out of artificial intelligence when it applies it to specific, measurable, and repetitive processes—not when it hands out ChatGPT licenses. That’s the difference between “using AI” and making money from it, and it’s exactly what a well-designed AI consulting project addresses.
In Spain, more and more companies are testing AI tools, but few see the impact on their bottom line. In this guide, we explain where the real return lies, why most projects fail, and how we at Inprofit work to help AI evolve from an experiment into a business tool.
30-Second Summary
- Using AI is not the same as making it profitable: most pilot projects do not generate a measurable return.
- The greatest return is usually found in internal processes (administration, customer service, sales, documentation), not in the flashiest applications.
- The formula that works: process diagnosis, prioritization by impact, a short pilot with KPIs in euros, and scaling.
- AI really delivers when combined with automation (n8n, Make) and integration with your systems (CRM, ERP, e-commerce).
- An AI consulting firm should also tell you what NOT to automate.
What is an AI consulting service for small and medium-sized businesses?
An AI consulting service for SMEs is a service that analyzes a company’s processes, identifies where artificial intelligence and automation generate a measurable return, and implements those solutions integrated with the tools the company already uses.
It’s not about recommending “the best AI on the market.” It’s about answering three business questions:
- Which tasks consume the most time, cause the most errors, or cost the most money in my company?
- Which of these can an AI or an automated workflow handle with sufficient quality?
- How much will I save or earn, and how long will it take to recoup my investment?
It is important to distinguish between two concepts that are often confused. Automation executes fixed rules (if an order comes in, it creates an invoice). AI applies judgment to unstructured information (understanding an email, classifying a document, drafting a response). The most profitable projects combine both: AI interprets, and automation executes.
Using AI Doesn’t Mean Making It Profitable: What the Data Says
Adoption is growing rapidly, but returns aren’t keeping pace. According to the INE’s ICT survey, 21.1% of Spanish companies with 10 or more employees used AI in the first quarter of 2025, 8.7 percentage points more than a year earlier (INE via Europa Press). Among industrial SMEs, the figure is much lower: the IndesIA 2025 Barometer puts it at 2.9% (Forbes).
The issue isn’t just how many companies use AI, but what they achieve with it. The MIT report *The GenAI Divide: State of AI in Business 2025* concluded that only about 5% of generative AI pilots achieve a measurable impact on revenue (Xataka). The same study identified two patterns that are particularly useful for small and medium-sized enterprises:
- More than half of the budget goes toward sales and marketing, but the greatest return comes from automating internal and back-office processes (Exame).
- Solutions implemented with specialized vendors are successful in about two out of every three cases, compared with approximately one-third of purely in-house developments (same source).
Translated to a Spanish SME: The opportunity isn’t in “having AI,” but in choosing wisely where to apply it and relying on those who have already done so.
Why AI Projects Fail in SMEs
The technology almost never fails; it’s the approach that fails. These are the five mistakes we see most often when auditing companies:
- Start with the tool, not the process. You purchase a license and then figure out what to use it for.
- Don’t measure in euros. “Saves time” isn’t a KPI. Without a baseline (hours, errors, cost per task), it’s impossible to demonstrate a return on investment.
- AI isolated from systems. A chatbot that can’t access your CRM, ERP, or online store forces you to copy and paste. The savings evaporate.
- Disorganized data. If information is scattered across Excel spreadsheets, emails, and folders with no structure, the AI inherits that chaos.
- No one is held accountable. Without an internal owner for the process and without training for the team, the pilot dies within a few weeks.
Added to this is “shadow AI”: employees using personal tools with customer data without oversight. This poses a privacy risk and is also a sign that there is internal demand that should be channeled.
How SMEs Make Money with AI: 8 Processes with Real Returns
The fastest return on investment comes from repetitive, high-volume tasks with clear rules—tasks where people are currently copying, sorting, or responding to the same thing over and over again.
| Area | What AI + Automation Does | Common Tools | What to Measure |
|---|---|---|---|
| Administration and Invoices | Reads invoices and delivery notes, extracts data, and records it in the ERP or accounting system | n8n or Make + AI model + Odoo/Holded/A3 | Recording hours, errors, cost per invoice |
| Customer Service | Answers frequently asked questions via the website, email, or WhatsApp, and escalates complex issues to a representative | AI agent + knowledge base + CRM | % of inquiries resolved without human intervention, response time |
| Sales and CRM | Qualifies leads, enriches contact records, drafts follow-ups, and schedules meetings | CRM + n8n/Make + AI | Time to first contact, conversion rate |
| Quotes | Generate proposals using a template and customer data | AI + documents + CRM | Quotes/week, time per quote |
| E-commerce | Create and optimize product listings, manage order issues, and recover abandoned carts | WooCommerce/Shopify + AI + automation | Product listings published per month, average order value, resolved issues |
| Marketing and Content | Produces drafts, adapts content by channel, and generates campaign reports | AI + Google/Meta Ads connectors | Cost per piece, reporting time |
| Internal documentation | Assistant that provides access to company manuals, procedures, and policies | AI with access to internal documents (RAG) | Consultations with the veteran team, onboarding time |
| Human Resources | Screens resumes based on defined criteria and automates onboarding | AI + forms + workflows | Hours spent screening, days until onboarding |
Not everything is worth automating. A task that occurs twice a month or requires a delicate touch (a negotiation, a sensitive complaint) usually causes more problems than it saves. Part of a good consulting firm’s job is to tell you what to leave out.
Example: Automated B2B Orders with n8n, AI, WooCommerce, and Odoo
A typical scenario for the type of project we implement; figures are for illustrative purposes only.
Starting point: An industrial supplies distributor sells to professionals through a WooCommerce B2B store and manages inventory and invoicing in Odoo. Many customers do not place orders on the website; instead, they send their orders via email, either as a PDF or in the body of the message. Two administrative staff members would manually enter these orders into Odoo—about 900 orders per month, taking an average of 8 minutes each (120 hours per month).
The solution: An n8n workflow monitors the order inbox. An AI model reads each email or PDF and extracts the customer, SKUs, quantities, and delivery date. n8n validates each line against the Odoo catalog and inventory and creates the sales order. The updated inventory is synchronized with WooCommerce, and the customer automatically receives a confirmation. If an SKU does not exist or the AI is unsure, the order is moved to a queue for human review.
Indicator Before After Orders processed without intervention 0% 85% Hours of administration per month 120 h 22 h Transcription errors 3.1% of orders 0,4% Time to Confirm the Order Up to 1 business day 15 minutes The Return on Investment. Freeing up 98 hours per month, at a cost of €24 per hour, amounts to approximately €2,350 per month. With an investment of €9,500 and €220 per month for server costs, AI usage, and support, the investment pays for itself in about 4.5 months. The administration team now dedicates that time to tracking collections and serving key clients.
How We Work at Inprofit: A 5-Phase Method
Our method is designed so that you see measurable results in weeks, not years, and so that every euro invested has a clear purpose.
- Process diagnosis (1–2 weeks). We interview the managers of each area and map out tasks, volumes, tools, and costs. Result: an inventory of opportunities with their baseline.
- Prioritization by impact and effort. We score each opportunity based on potential savings, technical complexity, data quality, and risk. We select one or two “quick wins” to get started.
- Pilot with KPIs in euros (4–6 weeks). We implement the solution in a real-world process, integrated with your systems, and measure performance against the baseline. If it doesn’t meet the target, we adjust or discard it.
- Scaling and integration. What works is rolled out to other teams or processes, with robust workflows in n8n or Make, error handling, and monitoring.
- Training and governance. We train the team, define who is responsible for each workflow, and establish a policy for AI use and data protection.
This approach isn’t just theoretical. At Inprofit, we develop our own AI-powered products, such as OpenClient, an AI marketing agent platform for small and medium-sized businesses, and eCosecha, an AI assistant on WhatsApp for farmers. We apply to our clients what we’ve already tested in-house. In addition, we hold certifications in Google, WordPress, Shopify, n8n, and Make.
How Much Does It Cost, and How to Calculate the ROI of AI for Your Business
The cost of an AI project depends on the number of processes, the necessary integrations, and the condition of your data. That’s why the useful question isn’t “how much does it cost,” but “how much return will I get, and how long will it take?” To answer that, simply use this formula:
\text{ROI} = \frac{\text{Ahorro anual} - \text{Coste total anual}}{\text{Coste total anual}} \times 100And the payback period:
\text{Meses de recuperación} = \frac{\text{Inversión inicial}}{\text{Ahorro mensual} - \text{Coste mensual de mantenimiento}}Illustrative example: automating the entry of supplier invoices
| Concept | Amount |
|---|---|
| Monthly Invoices | 400 |
| Manual time per invoice | 6 min (40 h/month) |
| Hourly cost of the position (including overhead) | 25 € |
| Current cost of the process | €1,000/month |
| Automation percentage | 75% |
| Savings | 750 €/month (9,000 €/year) |
| Initial investment (example) | 6,000 € |
| AI maintenance and usage (example) | 150 €/month |
| Return on investment | 10 months |
In the first year, the ROI is 15% (€9,000 in savings versus €7,800 in total cost). Starting in the second year, without the initial investment, the net savings rise to €7,200 annually. And that’s not even counting benefits that are hard to quantify: fewer errors, faster financial closings, and employees focused on higher-value tasks.
These figures are approximate. During the assessment, we’ll calculate this exact number using your actual data before you invest a single euro in implementation.
External consulting, standalone tools, or an in-house specialist: what’s right for you
For most small and medium-sized businesses, the most efficient option is to start by hiring a consulting firm to implement the first projects and train the team, and then decide whether to bring the work in-house.
| Criteria | Individual licenses (ChatGPT, Copilot, etc.) | Hire an in-house AI specialist | AI and automation consulting |
|---|---|---|---|
| Initial cost | Low | High (salary + recruitment time) | Medium, tied to goals |
| Time to Results | Immediate, but superficial | Months | Weeks (4–6-week pilot) |
| Integration with CRM/ERP/e-commerce | No | Depends on the profile | Yes, that’s the core of the work |
| ROI Measurement | Rarely | It depends | From the assessment |
| Data risk and compliance | High if there is no policy | Medium | Low, with a usage policy in place |
| Knowledge retained within the company | Individual | Concentrated in one person | Documented and transferred to the team |
Individual licenses are a good first step, but they rarely transform a process. An internal solution makes sense when there are already several workflows in place that need to be maintained and improved.
Checklist: Is your company ready to capitalize on AI?
If you check five or more boxes, you have clear potential to see a return on investment from AI and automation in the coming months.
- Some people spend several hours a week copying data between programs.
- You often find yourself answering the same questions from customers or suppliers.
- Quotes or proposals take more than a day to produce.
- It takes hours or days to make initial contact with leads.
- Key information is scattered across Excel spreadsheets, emails, and folders.
- Your team is already using ChatGPT or other AI tools on their own, without a common policy.
- You use a CRM, ERP, or online store that aren’t connected to each other.
- Monthly reports are put together manually.
- You’ve tried an AI tool but haven’t seen any impact on your results.
- You want to grow without increasing your administrative staff.
AI, Data Protection, and the European AI Regulation
Getting the most out of AI also means doing so without legal risks. Every implementation must comply with the GDPR: you must know what personal data each tool processes, where it is stored, and on what legal basis.
The European Artificial Intelligence Regulation (AI Act) will phase in its requirements gradually. Starting in February 2025, companies that use AI systems must ensure that their staff have a sufficient level of AI literacy. In addition, there are transparency obligations, such as informing a user that they are speaking with a chatbot rather than a person.
In practice, for an SME, this translates into three simple steps:
- An internal policy on the use of AI (which tools, with what data, and for what purposes).
- Basic training for the team, which in many cases can be subsidized through FUNDAE.
- Choose providers and configurations that do not use your data to train models.
This article does not constitute legal advice; if you have specific questions, consult a data protection specialist.
Frequently Asked Questions About AI Consulting for Small and Medium-Sized Businesses
Analyze your processes, identify where AI and automation can generate savings or revenue, implement solutions that integrate with your tools, and train your team to use them. The deliverable isn’t a report—it’s processes that are up and running, with measurable results.
A well-chosen pilot program typically yields measurable results within 4 to 6 weeks. The time to recoup the investment depends on the process, but for high-volume administrative tasks, it is typically less than one year.
No. It is sufficient for the chosen process to provide accessible and reasonably consistent data. Organizing the information is part of the project itself and is often a benefit in and of itself.
In an SME, AI typically frees up time spent on repetitive tasks so that employees can focus on customers, sales, or quality. The usual goal is to grow without adding to the administrative burden, not to reduce the workforce.
Both are platforms for automating processes by connecting applications. Make is more visual and faster for simple workflows. n8n offers more control, allows for self-hosting, and is more cost-effective at high volumes. We choose one or the other depending on the situation.
Yes, if it’s set up correctly: vendors that don’t process your data, hosting within the EU whenever possible, restricted access, and an internal usage policy that complies with the GDPR.
Conclusion: Profitable AI Starts with a Process, Not a Tool
SMEs that make money with AI aren’t the ones that try out the most tools, but rather the ones that choose the right process from the start, measure its impact in euros, and scale it up. The technology is already mature and affordable; what makes the difference is the method.
At Inprofit, we help you take that step: we assess your processes, calculate the return on investment using your actual data, and implement AI and automation solutions integrated with your CRM, ERP, or e-commerce platform.
Want to know how much your company could save? Request a free diagnostic session, and we’ll tell you which two or three processes AI can deliver a return on first—and which ones aren’t worth touching.
Marketing tecnológico en vena. Fanático de las tecnologías Martech que rompen moldes: IA generativa, blockchain, no-code, metaverso, automatización extrema… Convencido de que el futuro no se espera, se construye (y se vende muy bien).
Responsable del marketing más disruptivo y tecnológico.
