How Much to Budget for AI in 2027: Real Line Items and Ranges

How much to budget for AI for 2027 depends on size and ambition, but the honest ranges are these: a Spanish SME starting seriously should set aside between €20,000 and €60,000 for the first year; a medium-sized company with several processes in its sights, between €60,000 and €250,000. More important than the total figure is the structure: a serious AI budget has five items—diagnosis, implementation, operating cost, training, and maintenance—and most who fail only budgeted for the second one.

This guide is written for those preparing the 2027 budget during the fall of 2026: executives and operations or technology managers who need to put a number in a box before December and defend it later. Let’s go item by item, with indicative ranges, the most expensive conceptual error made when budgeting for AI, and the questions you should ask any provider before committing a single Euro.

What items should an AI budget include?

Five, and it is advisable to budget them separately because they behave differently: two are one-off, two are recurring, and one is mixed.

1. Diagnosis (one-off: €3,000-€15,000). Inventorying processes, measuring how much they cost today in hours and errors, and prioritizing by return. This is 2-4 weeks of work and is the item that prevents wasting the rest: automating the wrong process is much more expensive than diagnosing.
2. Development and implementation (one-off, per process: €15,000-€60,000 per agent). Design of the redesigned process, building the agent, connecting with your systems using native connectors, testing with real cases, and going live. The range depends on the complexity of the process and the number of systems to integrate, not the "model size".
3. Operating cost per model usage (recurring: €100-€2,000/month per agent). AI models are paid by consumption, like electricity. A moderate-volume agent in an SME usually stays in the hundreds of euros per month; one that processes tens of thousands of operations, in the thousands. This is the item most people forget and the easiest to estimate poorly: always ask for a projection based on your real volume.
4. Team training (mixed: 5-10% of the total budget). The people who will work with the agents—supervising them, correcting them, making the most of them—need practical training, not an inspirational talk. Without this item, the technical system works but adoption doesn't; we have a specific guide on AI training for employees.
5. Maintenance and evolution (recurring: 15-25% annually of the implementation cost). Processes change, systems update, models improve. An agent without maintenance degrades silently; this item covers supervision, adjustments, and incremental improvements.

With that structure, the typical budget for an SME deploying its first agent looks like this: about €5,000-€10,000 for diagnosis, €20,000-€40,000 for implementation, €200-€500/month for operation, training included in the project, and an annual maintenance of €4,000-€8,000 starting from the second year. The fine breakdown, with examples by project type, is in our guide on how much a custom AI agent costs.

Indicative ranges by company size

The following ranges assume a full first year—diagnosis, one or several deployments, and operation—and are deliberately wide: the real number is fixed by how many processes you automate, not how many employees you have.

• Small business (10-50 employees): €20,000-€60,000 the first year. A narrow diagnosis and 1-2 truly automated processes, typically customer service, administration, or the sales funnel. Less than €15,000 rarely allows for moving beyond a decorative pilot.
• Medium-sized (50-250 employees): €60,000-€250,000 the first year. Full diagnosis, 3-6 processes in 2-3 phases, and an internal lead with real part-time dedication. In this bracket, the annual savings from well-chosen processes usually exceed the investment even within the first year.
• Large (250+): from €250,000, budgeted by divisions. At this scale, a single "corporate AI" budget works worse than providing each division with its own budget against specific cases, with a common standard of security and traceability.

A warning about these ranges: they are for automation with agents connected to your systems, which is where the structural return lies. If your 2027 budget only contemplates licenses for general-purpose tools (office assistants, generic copilots), you are buying diffuse individual productivity—useful, but hard to measure—rather than process transformation.

The most expensive error: budgeting "a platform" instead of automated processes

The classic mistake is setting aside a figure to "implement an AI platform"—a corporate subscription, so many euros per seat per month—and considering the budget done. It’s easy to approve and almost always disappointing because it buys access to technology, not results in processes.

The question that should structure the budget is not "which platform do we buy?" but "which processes are we going to automate, how many hours and errors do they cost us today, and how much will it cost to automate them?". The first question produces a recurring expense line that no one knows how to justify in 2028; the second produces a prioritized list where each item has its return calculated before being approved.

The acid test for any proposal: if the provider can tell you "this process costs you X hours per month, we’ll bring it down to Y, it pays for itself in Z months and is measured like this," you are budgeting for processes. If the proposal talks about users, seats, and modules, you are budgeting for a platform. Our methodology for calculating that return process by process is in the guide on the ROI of artificial intelligence in business.

How to sequence investment: self-financing phases

The safest way to budget for AI is not to commit the entire annual amount on January 1st, but to approve it in phases where each phase is paid for with the savings from the previous one. It’s better for cash flow, better for risk, and—not least—much easier to defend before a skeptical board or CFO.

1. Phase 0 — Diagnosis (fall 2026 or January 2027). Small commitment: €3,000-€15,000. You come out with an inventory of processes prioritized by return and with measured baselines.
2. Phase 1 — Minimum profitable (first quarter). The process with the best savings/difficulty ratio, in production in 4-8 weeks. This is the phase that converts internal skepticism into internal demand.
3. Phase 2 — Financed expansion (from the second quarter). Verified savings from phase 1—against baseline, not against estimates—finance the next 2-3 processes. The budget stops being an act of faith.
4. Phase 3 — Ordinary budget (2028). AI stops being an extraordinary item and becomes part of the operating budget of each area, like the ERP or the cloud.

This scheme has a practical implication for anyone budgeting now: you don't need to get the full annual figure right. You need to confidently approve phase 0 and phase 1—say €25,000-€50,000 for an SME—and condition the rest on measured results. A well-designed conditional budget is more ambitious, not less: it removes the artificial ceiling of "what we dared to ask for in October."

What to ask a provider before committing budget

Six questions, and the answers will tell you more than any sales proposal:

1. "Show me a system of yours in production that is still working six months later." Separates those who build from those who pitch.
2. "Break down the proposal into the five items: diagnosis, implementation, operation, training, and maintenance." Anyone hiding the operating cost or maintenance is shifting the surprise to 2028.
3. "How much will the monthly operation cost with our real volume?" Demand a projection with your numbers, not a generic flat rate.
4. "Who owns the code, the prompts, and the data when the project ends?" The only acceptable answer is "you," with documented clean exit.
5. "Which of our processes would you NOT automate?" Anyone who answers "all are automatable" is selling, not consulting. Sometimes the correct answer is a simple rule without AI.
6. "What about traceability and compliance?" GDPR, AI Act—with obligations already in force and a calendar that continues to unfold in 2026-2027—and, if you touch billing in Spain, VeriFactu. Logging of every agent action included, not as an extra.

If you want to cross-check your budget draft before taking it for approval, that is exactly the type of work we do in the diagnosis phase of our artificial intelligence consultancy: process inventory, baselines, and a phased plan with defensible numbers.

Frequently Asked Questions

Is AI budgeted as CAPEX or OPEX?

In practice, it's mixed: diagnosis and implementation are usually treated as an investment (and custom development can be capitalized), while the use of models, licenses, and maintenance are recurring operating expenses. What matters for planning is not just budgeting the single-payment part: the recurring part determines the real three-year cost.

What do I do if my budget is less than €15,000?

Start smaller in scope, not cheaper in quality: a narrow diagnosis plus the automation of a single well-chosen flow, or directly serious team training with existing tools while you prepare for the jump. What you shouldn't do with a small budget is a "cheap agent" without connection to your systems: it's the fast track to a pilot project that gets abandoned.

How much does it cost to maintain an agent per year?

Between 15% and 25% of its implementation cost, plus model consumption. For a typical €30,000 agent, that's €4,500-€7,500 annually for maintenance and evolution plus €100-€500/month for operation. If a provider tells you maintenance is zero, they haven't operated systems in production.

Are there public subsidies for this in Spain?

There have been public digitization and AI advisory programs for SMEs, and it is reasonable to expect active calls for 2027, both at the state and regional levels. Practical advice: treat them as an accelerator, not a condition—a project that only makes sense with a subsidy is likely not well-chosen—and check the active calls when you close the budget.

What if model prices drop in 2027?

They probably will: the cost per unit of work for models has been falling for years with each generation. Budget the operating item with current prices and treat the drop as a safety margin, not as an assumption. The dominant cost of these projects is not the model, but the implementation and the process change; that is where money is won or lost.