AI consulting identifies in which processes of your company artificial intelligence generates a real return, prioritises them by impact, ease and risk, and turns them into a roadmap with measurable pilots. We work with management and with the teams, and afterwards we can build what we recommend.
By Oliver Guirado · Updated on October 28, 2026 · 6 min read
Who AI consulting is for
It is for companies that know AI can help them but do not know where to start, what to prioritise or how much to invest: growing small and mid-sized businesses, executives under pressure to "do something with AI" and teams that have already tried isolated tools without measurable impact.
The signs that it suits you: your teams use AI on their own without common criteria, there are processes with a lot of text to read or repetitive manual work, your data is scattered across several systems or you have already received technology proposals you cannot compare. The guide on how to implement AI in a small business summarises the path; consulting walks it with you.
What is included and what you receive
Opportunity map
A list of candidate processes with their current cost, volume and data maturity.
Prioritisation with criteria
Each case scored by impact, technical ease, risk and time to return.
12-month roadmap
What to do first, with what budget, who takes part and what is measured.
Business cases
Estimate of savings or revenue, investment and timeline for the 3-5 main cases.
Architecture and providers
Technical recommendation: build, buy or integrate, and which models to use.
AI usage policy
Clear rules for employees: permitted data, approved tools and human review.
Ways of working
Format
What we do
Duration
Opportunities workshop
A session with management and area heads to detect cases and discard those that do not pay off.
1 – 2 days
Diagnostic and roadmap
Interviews, analysis of systems and data, prioritisation and a plan with business cases.
3 – 5 weeks
Guided pilot
We build and measure the priority case with a bounded version.
4 – 8 weeks
Ongoing support
Part-time AI technical leadership: review of providers, quality and new cases.
Value: hours freed up, revenue captured or errors avoided, with a prudent and defensible estimate.
Ease: quality and accessibility of the data, integrations needed and complexity of the process.
Risk: impact of an error, personal data, regulatory requirements and need for human oversight.
Adoption: who will use it, how much it changes their work and how success will be measured.
The result is a clear table: what to do now, what to prepare (data or integrations) and what to discard, with reasons. We avoid the most expensive mistake: starting with the most eye-catching case instead of the most profitable. If you want a catalogue for inspiration, see AI use cases by department.
Sample AI consulting projects
Sample project · Logistics
AI diagnostic and roadmap for a logistics group
Problem
Management was receiving AI proposals from several providers, all different and hard to compare, and the operations, customer service and administration teams were trying out tools on their own without common criteria.
Solution
A four-week diagnostic with interviews across the areas, analysis of systems and data, a catalogue of scored cases and a roadmap with three pilots, their budget and their metrics.
Steps
Workshop with management to set goals and constraints.
Interviews by area and a process map with volume and current cost.
Review of data and systems (TMS, ERP, email, documents).
Prioritisation by value, ease and risk, and business cases for the main ones.
Presentation to management, AI usage policy and pilot plan.
Target outcome
Comparable investment decisions, three pilots with clear metrics and a common policy for the whole workforce. More in logistics software.
Technology
Deliverables: report, prioritisation matrix, business cases, recommended architecture and usage policy.
Sample project · Hospitality and restaurants
AI strategy for a restaurant chain
Problem
Many venues, a lot of customer service across different channels and demand forecasting done by hand. It was not clear whether AI would pay off or in what order.
Solution
A bounded workshop and diagnostic that prioritise three lines: conversational service and bookings, review analysis and demand forecasting for purchasing and shifts, with a pilot in a group of venues.
Steps
Workshop with operations, marketing and customer service.
Analysis of available data (bookings, sales, reviews, staff).
Prioritisation and design of the pilot with success metrics.
Phased roll-out plan by venue.
Target outcome
A phased plan with estimated return and a first pilot under way. More in apps for restaurants.
Technology
Deliverables: opportunity map, business cases and pilot specification.
The projects on this page are illustrative, anonymised examples of how we approach this kind of work. Every real project is defined with your information, your systems and your goals.
Data, governance and regulation
The strategy includes what tends to be forgotten: data quality and ownership, what information can be sent to external models, GDPR, and the obligations of the EU AI Act depending on the use (transparency to users, classification by risk level and human oversight). We deliver a usage policy for employees and an inventory of AI systems, with the legal review appropriate to your case.
Reference prices for AI consulting
Service
Indicative investment
Opportunities workshop (1 – 2 days)
€1,500 – €3,500
Diagnostic and roadmap (3 – 5 weeks)
€4,000 – €12,000
Guided pilot of a priority case
€8,000 – €25,000
Monthly support (part-time AI technical leadership)
€2,000 – €6,000 / month
Indicative reference prices in euros, excluding VAT, for projects in Spain and Europe in 2026. The final amount depends on scope, integrations and data quality; we confirm it with a fixed quote after a first meeting.
The investment in the diagnostic is deducted, in full or in part, if you commission the development of the prioritised cases with us.
Frequently asked questions
What is artificial intelligence consulting?
It is analysis and planning work that identifies in which processes of your company AI generates a return, prioritises them by impact, ease and risk, and delivers a roadmap with measurable pilots, a budget and a usage policy.
How much does AI consulting cost?
An opportunities workshop costs between €1,500 and €3,500; a diagnostic with roadmap, between €4,000 and €12,000; and monthly support, between €2,000 and €6,000 a month. These are reference prices excluding VAT.
How long does an AI diagnostic take?
Between three and five weeks depending on the size of the company and the number of areas involved. The initial workshop takes one or two days.
Do I need my data in order before starting?
No. Part of the diagnostic is assessing the state of the data and defining what needs to be prepared. Some cases work with imperfect data and others require tidying it first.
Does consulting include developing the solutions?
Not necessarily. You receive a plan that your team or a third party can carry out. If you want us to build it, we deduct the diagnostic investment from the project.
How is European AI regulation handled?
We review which uses you have or plan, their risk level, the transparency and human oversight obligations, and deliver a usage policy. For specific legal advice we recommend review by your lawyer.
Shall we talk about your project?
Tell us about your case and we will reply within 24-48 hours with a proposed scope and an indicative quote.
