The question that operations directors and CFOs of mid-sized companies repeat most often when they sit down with us is always the same: «How much is this artificial intelligence thing going to cost me?». The honest answer is that it depends on many variables, but market-oriented ranges do exist that allow you to compare proposals and avoid surprises. This article breaks down those ranges, explains the factors that push the price up or down, and describes the typical phases of an AI adoption project for a Spanish SME or mid-sized company in 2026.
What an AI Consultancy for Business Actually Is
An artificial intelligence consultancy for business is not the same as buying a ChatGPT subscription or hiring a developer to install a chatbot. It is a structured process that starts with an honest diagnosis of business processes, identifies the use cases with the greatest return, defines the technical architecture, manages organisational change, and accompanies the organisation until the solution produces measurable results.
Projects purchased as a «black box» without that consultancy layer fail at a far higher rate than projects where an interlocutor exists who understands both the business and the technology. According to data published by McKinsey in its AI Survey 2024, 72% of organisations already use AI in at least one business function, yet most fail to generalise its use beyond the initial pilot without a solid methodological framework in place.
Indicative Price Ranges in the Spanish Market in 2026
The prices below are market ranges based on industry publications, public procurement data and benchmarks from associations such as AMETIC and data from the consultancy firm IDC for the Iberian market. They are not the rates of any specific provider; they serve to orient the budget and detect proposals that fall outside the reasonable range.
| Project type | Company profile | Indicative range (consultancy fees) | Typical duration |
|---|---|---|---|
| AI diagnosis and roadmap | 10-50 employees | €3,000 – €8,000 | 3-6 weeks |
| AI diagnosis and roadmap | 50-250 employees | €8,000 – €18,000 | 6-10 weeks |
| Pilot with one use case (automation, RAG, classification) | 10-50 employees | €6,000 – €20,000 | 2-4 months |
| Pilot with one use case | 50-250 employees | €18,000 – €50,000 | 3-6 months |
| Full implementation (multiple use cases + ERP integration) | 50-250 employees | €40,000 – €120,000 | 6-18 months |
| Corporate adoption programme + training + governance | 100-250 employees | €60,000 – €150,000 | 12-24 months |
Important: these ranges correspond to the consultancy team's fees. On top of these, you must add software licences (language model APIs, automation platforms, cloud infrastructure) and the internal time of the client's team. In automation projects using n8n or low-code platforms, licence costs can be modest; in projects with proprietary models such as GPT-4o or Claude 3 Opus, the monthly token invoice can range from €200 to €3,000 depending on query volume.
Factors That Drive the Price Up
Complexity and Number of Integrations
A project that needs to connect the AI agent with the ERP, CRM, and document management system multiplies integration hours. Each connector that does not exist out of the box adds between 15 and 40 hours of development, depending on the quality of the source system's API. Companies with legacy or custom-built management software pay noticeably more than those using standard ERPs such as Odoo, Sage, or Dynamics 365.
Need for Clean, Labelled Data
Artificial intelligence does not work with dirty data. If the company does not have its documents digitised, its processes recorded, or its historical data in an accessible format, the first phase of the project will be data cleansing, which adds between 20% and 40% to the original budget. A thorough prior diagnosis identifies this before signing.
Data Sovereignty Requirements
Companies that process sensitive data (medical, legal, financial) or that operate under regulations such as the GDPR with special categories of data cannot send that information to third-party APIs. In those cases, the project requires deployment of models on proprietary infrastructure (on-premise or private cloud), which raises infrastructure costs and configuration time. The additional range can be €10,000 to €40,000 above the base consultancy cost.
Regulatory Compliance (AI Act)
The European Artificial Intelligence Regulation (AI Act, in force since August 2024 with progressive application until 2027) imposes different obligations depending on the system's risk level. Companies deploying AI in human resources, credit, health, or critical infrastructure processes fall under high-risk categories and require technical documentation, conformity assessments, and in some cases the involvement of a notified body. Adding this governance layer to the project adds between €5,000 and €20,000 depending on complexity.
Provider Profile
The Spanish market has a wide range: from specialist freelancers charging between €60 and €120 per hour, to large consultancies billing €180 – €350 per hour for senior profiles. In the specialised mid-sized consultancy segment (the most suitable niche for companies of 20-200 employees), the typical range is €85 to €160 per hour. The hourly rate is not the only criterion: speed of execution, sector experience, and the ability to accompany organisational change are the key determinants of real return.
Factors That Can Reduce Cost
Starting With a Well-Scoped Use Case
Companies that try to «do AI» across all their departments at once spend more and get less. The right approach is to identify a repetitive, high-volume process with relatively organised data and a measurable economic impact, and run a pilot over 8-12 weeks. If it works, it scales; if not, the cost of the learning has been controlled.
Leveraging Public Funding
In 2025-2026, several instruments exist to partially fund AI projects in Spanish mid-sized companies:
- Kit Digital (programme for companies with 0-49 employees): up to €12,000 per company in the 10-49 employee segment for digitalisation, including AI and automation.
- Kit Consulting (companies with 10-250 employees): up to €24,000 for strategic consultancy services, which can include an AI roadmap.
- CDTI – Cervera and Missions: R&D projects with an AI component can apply for grants or soft loans from the Centre for Industrial Technological Development.
- FUNDAE: AI training for teams is subsidisable through the State Foundation for Employment Training, reducing the net cost of staff upskilling.
Using Already-Established Low-Code Platforms
Not all projects require custom development. Platforms such as n8n, Make, or Power Automate make it possible to build AI-powered automations at a fraction of the cost of proprietary development, provided the use case does not require highly specialised models or very deep integrations.
What a Serious AI Consultancy Proposal Should Include
A proposal worth evaluating must break down, at minimum, the following elements:
- Initial diagnosis: process analysis, inventory of available data, and a map of use cases prioritised by return and technical feasibility.
- Proposed technical architecture: which models will be used (proprietary vs. open-source), where they will run (public, private, or hybrid cloud), and how they integrate with existing systems.
- Governance and compliance plan: how risk is managed in line with the AI Act, who is responsible for automated decisions, how results are audited.
- Success KPIs: concrete metrics agreed before starting (hours saved, error rate reduced, customer response time) with a baseline and target.
- Training and change plan: how the team that will use or supervise the tool is upskilled.
- Exit conditions: what happens to the code, trained models, and documentation if the company decides to change providers.
If a proposal does not include a prior diagnosis, an explicit architecture, or agreed KPIs, that is a warning sign regardless of the price.
The Difference Between Strategic AI Consultancy and AI Software Development
It is common for companies to confuse two distinct services. Strategic AI consultancy — what an AI advisory service offers — focuses on deciding what to do, in what order, with what technology, and under what governance framework. It is provider-independent and business-oriented.
AI software development executes the decision already made: it builds the agent, integrates the model, and programmes the connectors. These are complementary but distinct services, with different professional profiles. A company that goes straight to development without going through the strategic layer typically ends up building something technically functional but poorly aligned with the real business problem.
Expected Return: When Does a Mid-Sized Company Recoup the Investment?
The return on an AI consultancy varies enormously depending on the use case. Some documented examples in the Spanish market:
- Automated supplier invoice extraction: companies handling 500-2,000 monthly invoices recoup the investment in 6-12 months by eliminating manual review.
- Customer service agent with automated FAQ: a 40-60% reduction in repetitive queries handled by the human team, with a typical ROI of 8-14 months.
- RAG on internal technical documentation: reduced information search time for engineering or legal teams; ROI is harder to measure but very perceptible in productivity terms.
- AI-powered demand forecasting: reduced excess stock and stockouts; the margin impact can exceed the project cost in the first year in sectors with high seasonal variability.
In all cases, the return depends more on the quality of the initial diagnosis and the commitment of the internal team than on the price paid to the consultant.
Frequently Asked Questions
Is there a minimum price below which AI consultancy makes no sense?
A rigorous diagnosis for a company of 15-30 employees cannot be done properly for less than €3,000-€4,000, because it requires at least 20-30 hours of analytical work from a senior professional. Cheaper proposals tend to be superficial audits that do not identify the real use cases or evaluate data quality. That said, public bodies (CDTI, Chambers of Commerce, CEEI) offer subsidised lower-cost diagnoses as a first step.
Is it better to pay by the hour or for a fixed-price project?
For the diagnosis and roadmap phase, an hourly rate with an agreed cap gives more flexibility. For implementation phases, a fixed price per deliverable is safer for the client company, provided the scope is well defined before signing. Fixed-price contracts with an ambiguous scope are the main source of conflicts in technology projects.
What is the difference between hiring a large consultancy and a specialised AI consultancy for SMEs?
Large consultancies (Big Four, global technology consultancies) have excellent methodological capabilities but inflate the project with high cost structures and often assign junior profiles to mid-sized company projects. Specialised mid-sized consultancies, such as those that have been accompanying digital transformations in companies in Castile and León and the Canary Islands since 2007, better understand the budget and operational constraints of SMEs and can offer more direct support at more competitive costs.
Is the cost of language model APIs predictable?
Yes, with a volume estimate. Model providers (OpenAI, Anthropic, Google, Meta through cloud providers) publish rates per million tokens processed. A project generating 10 million tokens per month with a mid-range model can cost between €50 and €300 per month in API costs, depending on the model chosen. A serious consultancy makes this estimate before the pilot and includes it in the return analysis.