"How much does it cost?" is the most honest question a business owner can ask. And it deserves an equally honest answer, not one that dodges the numbers and then arrives with a surprising quote.
In Italy in 2026, the AI consulting market is split into three bands with very different characteristics, prices and outcomes. This guide looks at them without filters, with the real numbers.
The price range on the Italian market (2026)
| Provider | Price band | ONP method |
|---|---|---|
| Big4 / Accenture | €80,000–€300,000+ per project | €5,000–€60,000 |
| Digital boutiques | €30,000–€100,000 | €5,000–€60,000 |
| AI freelancers | €5,000–€30,000 | €5,000–€60,000 |
| Initial assessment | €15,000–€80,000 (Big4) | From €5,000 |
But price is only half the story. The other half is: what are you actually buying?
What an SME buys from a large consulting firm
Large consulting firms, Big4, Accenture, high-end digital boutiques, have skilled teams, solid methodologies and established reputations. The issue isn't quality: it's the business model.
A Big4 works with enterprise clients worth hundreds of millions of euros. When it takes on a project with an SME, this is typically what happens:
- The operational team is made up of junior analysts (2–3 years of experience) supervised by a senior who shows up on calls but doesn't work on the project day to day.
- The main deliverable is a document, an assessment, roadmap or strategic framework. Often excellent on paper. The operational execution requires additional skills that aren't always included.
- The budget covers the analysis, not the implementation. To go from the roadmap to operational reality, the client has to engage again, at even higher costs.
- The frameworks are global, not calibrated for Italian SMEs. The SME often ends up with an action plan designed for an organisation ten times its size.
"I paid €120,000 for an assessment that restated things we already knew, in very formal language. The roadmap was complete, but internally we didn't have the skills to execute it."
This doesn't mean the Big4 are useless. For large companies with complex processes, international compliance and the right budget, they're often the right choice. For an SME of 50–200 people, they're often not the most efficient one.
The problem with AI freelancers
At the opposite end are freelancers and agencies that also offer AI services, often capable professionals individually, but with structural limitations that are hard to ignore for a serious business project:
- No structured methodology. Every project is different, often without a repeatable, validated process.
- Delivery isn't guaranteed. A freelancer can run into unexpected events, capacity issues, other clients. Without structure, the project risks stalling.
- The client ends up with a tool but no idea how to use it. The freelancer delivers the technical work, but training and knowledge transfer often fall outside the engagement.
- No continuity. If the freelancer is no longer available, the client has no one to turn to, and depends on a single person rather than a team.
The ONP model: accessible price, guaranteed delivery
ONP was created precisely to fill the space the Big4 don't reach and where freelancers can't hold up. The pricing structure is transparent:
- AI Readiness Assessment, from €5,000. Includes diagnosis, a prioritised roadmap and an action plan. Deliverables guaranteed in 2–3 weeks.
- Implementation track, from €15,000. Hands-on support to implement the identified processes. Team trained, tools working.
- Full track (Assessment + Implementation + Scale), from €25,000 to €60,000 depending on complexity. Includes team training (Officina AI).
What sets this apart from the other options isn't just the price, it's the structure of the contract. Every ONP project has defined, measurable, guaranteed deliverables before signing. If we don't deliver them, we keep working for free until we do.
Want an accurate quote for your situation?
A 30-minute call, free, no obligation, with a concrete output.How to calculate ROI before you start
Any AI investment should have an estimable ROI before you begin. The calculation isn't complicated, it just requires honesty about your current numbers.
Basic formula:
- Identify the current cost of the problem (hours/week × hourly cost × 52 weeks)
- Estimate a realistic reduction (typically 30–70% for the most automatable processes)
- Calculate the annual saving
- Compare it with the cost of the project
A concrete example: An orders office that uses 3 people for 2 hours a day on manual tasks. Average hourly cost €25. Annual cost of the problem: 3 × 2 × 250 × 25 = €37,500/year. With automation that cuts these tasks by 70%, the saving is €26,250/year. A €20,000 ONP project has a positive ROI in under 12 months.
This calculation should be done before signing any contract, not as an academic exercise, but as a real decision-making tool. If the ROI isn't clear, you don't start.
What to ask any provider before signing
Whoever you choose, these are the questions every serious AI provider should be able to answer:
- What exactly are the deliverables of this project? (Not "we'll improve your processes", but "we'll deliver X by Y date")
- Who actually works on the project day to day? (Not the name of the partner who signs the contract)
- How is success measured? (Specific metrics, not generic ones)
- What happens if you don't reach the results? (The right answer isn't "we'll do our best")
- At the end of the project, is my team autonomous or still dependent on you?
If a provider can't answer these questions clearly, it's a signal worth paying attention to.