AI Competency Assessment: How to Really Know What Your Team Can Do in 2026

Your company invested in AI tools. Your employees say they save them time. According to Adecco, an average of 171 minutes daily in Spain, three times more than the previous year. And yet, you're not seeing that impact in business results.

This is not a technology problem. It's a problem of unmeasured competencies.

When you don't know what your team can really do with the tools you've given them, and what they can't do, you cannot close the gaps that exist, orient training properly, or justify the investment to management. AI competency assessment changes this: it gives you a real picture of your workforce's capabilities, continuously, with less subjectivity, and directly connected to your training plan and your FUNDAE credit.

In this article we explain what changes when you use AI to assess competencies, how to get started practically, and why 2026 is the year when this decision stops being optional.

Competency assessment: a complete guide for HR →

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Why Competency Assessment Can No Longer Be an Annual Conversation

What is competency assessment?

Competency assessment is the systematic process of measuring, analyzing, and documenting the skills, knowledge, and capabilities that an organization's employees have relative to those it needs to achieve its goals. It is not the same as performance appraisal: performance appraisal measures results (what the employee has achieved), while competency assessment measures capabilities (what the employee knows and can do).

The "halo effect" problem and manager subjectivity

In many mid-sized companies in Spain, competencies are assessed the same way they were ten years ago: an annual conversation between the employee and their manager, perhaps accompanied by an Excel spreadsheet or a form in the HR system. The result is a document that gets filed, that nobody consults again, and that changes nothing day-to-day.

The problem is not just that it is inefficient. It's that this system doesn't tell you what you need to know.

When assessment depends almost entirely on the direct manager's perception, well-documented cognitive biases come into play that distort results. The most well-known is the halo effect: if someone performs well in one visible area, we tend to rate them positively in all others. The recency effect is equally common: what happened three weeks ago can weigh more than what occurred six months ago.

This is not a criticism of managers. It's the nature of human judgment without data to counter it. The practical result for HR is that traditional competency assessments can say more about the relationship between the employee and their manager than about the employee's actual capabilities.

The world where 39% of current competencies will be obsolete by 2030

The World Economic Forum published in its Future of Jobs Report 2025 a figure every HR Director should have in mind: 39% of workers' current competencies will be transformed or become obsolete between 2025 and 2030 (WEF, 2025). Not in twenty years. In five.

Furthermore, 63% of global employers identify the skills gap as the biggest obstacle to their business transformation during this period (WEF, 2025). Conducting an annual assessment in this context is like photographing a ship's position in the middle of a storm. When the storm shifts, the photo is no longer useful.

What the data says about Spain: 75% of companies can't find the profiles they need

According to ManpowerGroup Spain's 2024-2025 Talent Shortage Study, 75% of companies in Spain have difficulty finding the profiles they need (ManpowerGroup, 2024-2025). Among the main causes, companies point to the lack of technical skills and lack of experience as the most frequent factors.

The problem isn't always outside your company. In many cases, the profile you're looking for in the market may already exist within your workforce. You simply don't know it because you don't have a clear picture of what your employees can do.

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What Really Changes When AI Enters Competency Assessment

What is AI competency assessment?

AI competency assessment is a process in which automated systems analyze performance data from multiple sources: results of structured assessments, completed training, activity patterns, and self-assessments. The goal is to identify the real competencies of each employee and detect gaps relative to the profile required by their role or the company's strategy. Unlike traditional assessment, it doesn't depend on the manager's memory or judgment: it works with continuous and structured data.

An important clarification: AI doesn't measure competencies directly. It analyzes behavioral patterns and assessment results to infer underlying capabilities. The quality of that inference depends on the competency model it starts from, for example, a framework like the European DigComp 2.2 for digital competencies, and whether that model has been validated for your sector and roles. That's why it's essential that the tool you choose works with recognized reference frameworks, not invented categories.

The difference is not just technological. It's a different way of understanding what it means to assess someone.

From point-in-time to continuous assessment

The traditional model assesses once a year, or at most every six months. Tools that incorporate AI in competency assessment work with performance data collected continuously: activity in projects, training results, performance indicators. The result is an updated picture of each person's capabilities on your team.

This doesn't mean constant surveillance. It means that when you need to make a decision, assign someone to a new project, plan the year's training, detect who needs support, you have real data on the table. Not the memory of a conversation from nine months ago.

From manager intuition to objective data

AI doesn't eliminate the manager's judgment. It complements it with something the manager cannot have: a cross-functional view, without the weight of the personal relationship, crossing data from different sources.

The real value of such a system isn't in an abstract retention figure. It's in two concrete things any SME HR Director immediately understands. First: detecting the misalignment between what the employee knows how to do and what the role requires before that misalignment becomes a resignation. Second: stopping spending the training budget on courses that don't address any real gap, and reducing the hours the HR team spends on an assessment process that in many cases is almost entirely manual.

The fundamental change is one of logic: you go from assessing what the manager perceives to assessing what the employee actually does and knows how to do.

From reactive to anticipating: detecting needs before they become a problem

Anticipatory capability is perhaps the most relevant change for the SME HR Director. Traditional assessment is reactive: it detects a gap once it has already become a problem, turnover, poor performance, operational errors. AI can identify early signals of emerging gaps, such as slow adoption of a new tool or low participation in specific training, before those gaps affect the business.

Calling it continuous diagnosis is more honest than talking about prediction. The platform identifies gaps in real time and, crossing that data with the expected evolution of the role, allows anticipating training needs 6-12 months ahead. It's not a statistical forecast model. It's an updated picture that helps you act before the problem becomes visible.

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Traditional Assessment vs. AI Assessment — Practical Comparison

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The Paradox Nobody in HR Is Talking About Enough

There's a data point that should concern any HR Director in Spain in 2026: according to Adecco's Global Workforce of the Future 2025 report, Spanish employees believe they save an average of 171 minutes daily thanks to AI, an increase of 3x compared to the 51 minutes reported in 2024 (Adecco Group Spain, 2025). It's a striking number.

The problem is that their companies are not detecting that improvement in results. Individual productivity perception and company-measured productivity don't coincide (Adecco Group Spain, 2025).

This paradox has a name: hidden competency gap. In many cases, employees perceive that they use AI, but use it superficially or without leveraging its potential. Nobody has assessed whether they really know how to use it well.

What does this mean in practice? Your company may have invested in AI, in licenses, in initial training, in process changes, and not be getting measurable return on that investment. Not because AI doesn't work. But because without knowing what each person on your team can do with those tools, you can't identify who is leveraging them well, who needs support, and where the gap is between the technology's potential and actual usage.

The McKinsey data puts it in perspective: 92% of companies plan to increase AI investments, but only 1% consider themselves mature in AI deployment (McKinsey, 2025). Mass adoption without competency measurement is, at best, poorly optimized investment.

92% of companies plan to invest more in AI. Only 1% consider they know how to deploy it well. That gap isn't closed with more licenses: it's closed by measuring what the team can do.

According to Microsoft & isEazy (2025), only 23% of HR and Training teams have achieved real AI integration in their processes. 85% use generic solutions like ChatGPT instead of tools specifically designed for HR. The early adopter advantage is still available for Spanish SMEs.

Want to see how AI competency assessment works? Try it yourself first: Skillia's free AI competency assessment takes less than 25 minutes and gives you your level in the most in-demand AI competencies plus a personalized development plan. It's exactly the type of diagnostic described in this article, applied to your own AI competencies. [Assess your AI competencies →]

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How AI Competency Assessment Works in Practice

Beyond the concept, what an HR Manager with a two-person team and a FUNDAE credit to manage needs to know is how this works day-to-day.

What an AI assessment platform actually does

A tool like Skillia isn't limited to analyzing passive data. It combines several sources of active assessment: adaptive tests that adjust difficulty in real time based on the employee's responses, situational scenarios where the employee demonstrates how they would solve a specific problem in their role, and competency questionnaires aligned with recognized reference frameworks like the European DigComp 2.2. The platform crosses the results of these assessments with completed training data and the employee's own self-assessments.

The result is a competency profile per employee that shows the gaps between what they know how to do and what their role requires, not based on a manager's perception, but on structured assessment evidence. For digital profiles (administration, customer service, coordination, management), the diagnosis is completed in 20-30 minutes per employee. For roles with less digital component (operators, field technicians), the scope of the assessment depends on the competencies defined in the role map, the tool is flexible, but its results are only as good as the competency model it works with.

Personalized development plan per employee

With that picture on the table, the tool can suggest an individual development plan: what competencies each person needs to develop, in what order, and with what type of training. This transforms the conversation with the manager. Instead of talking about "how did the year feel," you discuss "here are the gaps we've detected and this is what we're going to do."

For a small HR team, this makes an enormous difference in the time you spend preparing development meetings.

Integration with the training plan and FUNDAE credit

Here is the most practical point for a Spanish SME: if competency assessment tells you exactly what each person on your team needs to learn, you already have your Training Needs Analysis (TNA) done. And the TNA is the foundation on which you should build your FUNDAE-subsidized training plan.

Instead of falling back on last year's courses or choosing by intuition, you have data that tells you where to invest the credit so the impact is real.

Practical example: how it works in a services company

This is a representative and illustrative case, not an actual Skillia client.

A logistics services company with 120 employees had the same training plan since 2022 — three Excel courses and one health & safety course — and their previous year's FUNDAE credit had partially expired unused. The TNA was drafted by the HR manager based on department requests and their own judgment.

After a data-based competency assessment, real gaps were detected in four role families (customer service, logistics coordination, warehouse supervision, administration). The following year's TNA was built around those gaps. Indicative result: approximately 85% of available FUNDAE credit applied to specific training, compared to 40% the previous year. The TNA drafting process went from three weeks to two days.

The difference wasn't technological. It was having data before deciding what training to buy.

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FUNDAE and Competency Assessment: The Training Money You Already Have

What is FUNDAE and why is it relevant for competency assessment?

FUNDAE (State Foundation for Employment Training) manages the subsidy system for continuous employee training in Spain. Every company that contributes to Social Security has an annual training credit assigned that it can use to subsidize its employees' training costs. In many Spanish SMEs, a significant portion of that credit is not fully utilized, or is spent on standard courses that don't address the workforce's real gaps.

AI competency assessment solves exactly that problem.

If you have employees in Spain, you have a training credit. It's yours by law, generated automatically based on your payroll. The process is straightforward: you assess what your employees know how to do and where the gaps are relative to what the business needs. Those gaps become the year's training plan. And that training plan is subsidized with the FUNDAE credit you already have available.

A frequent objection HR directors hear when talking about investing in assessment is "we don't have budget." In Spain, that objection doesn't hold. Your company already has a training budget. What it lacks is knowing where to invest it so the impact is real.

How much credit you have: bands by company size

The subsidized training credit is generated from the Vocational Training contribution your company makes to Social Security. The exact amount depends on your wage bill and what was contributed in the previous year, but the recovery bands by size are as follows (FUNDAE, 2025):

Indicative example: A company of 80 employees with an average wage bill of around €30,000 gross per employee can have an annual credit of between €8,000 and €12,000, depending on their actual contribution. If that credit is not applied before December 31, it expires as a general rule. Companies with fewer than 50 employees can apply to accumulate unused credit for up to two additional years, but must formally request this before June 30.

With a TNA based on assessment data, that amount is invested in training that addresses real gaps. Without prior diagnosis, it's money you technically have but spend without criteria, or don't end up using.

Important: The company applies the subsidy as a deduction on the TC1 social security form for the month the training action ends (or the following month). In practice, the vast majority of SMEs delegate this management to their accounting firm or an accredited training organization. Skillia generates the TNA with data; the accounting firm handles the subsidy processing.

In Spain, the training credit is already paid. The problem isn't the budget: it's that without knowing what gaps the team has, it gets spent on the same courses as always or expires unused.

How to connect assessment results with the TNA — and what role the platform plays

The Training Needs Analysis (TNA) is the process that justifies and guides the use of FUNDAE credit. It's normally done manually and intuitively: the HR manager asks managers what courses they want for their teams, or directly drafts the document based on intuition and the scattered requests that come in from departments. In practice, the TNA is usually an Excel with manual assessment templates, a Google Forms survey, or a document that nobody has reviewed since the previous year.

What a platform like Skillia does is generate that TNA with real data from continuous assessment: the gaps detected between what employees know how to do and what their roles require. The company or its accounting firm then uses that data to justify the training plan to FUNDAE. Skillia doesn't act as an accredited training organization. It's the data infrastructure that converts an intuitive TNA into an evidence-based TNA.

Processing the subsidy has administrative steps that require attention: prior communication to the legal representatives of workers (if any), accreditation of the training provider with SEPE, TC1 tracking after completion, and document retention for four years for possible audits. For most SMEs, this is managed by the accounting firm or accredited training organization. What Skillia contributes is that the TNA data is based on evidence, not intuition — the administrative processing remains the responsibility of the company or its manager.

SEPE data confirms this: its 2025 Prospecting and Training Needs Analysis Report places digital competencies among the most in-demand by Spanish companies (SEPE, 2025). A TNA backed by objective assessment data is also the strongest argument in any review that subsidized training responded to a real need.

Complete guide to FUNDAE subsidized training →

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What You Need to Know About the AI Act — Without Alarming, Without Ignoring

Most articles about AI in HR don't mention regulation. This one does, because it's practical information that affects the decision of which tool to choose.

The AI Act classifies competency assessment systems as "high risk"

The European AI Regulation, the AI Act (Regulation EU 2024/1689), entered into force in August 2024, with full application from August 2026. It classifies AI systems used in human resources and personnel selection as high-risk systems, the category requiring the greatest compliance obligations: algorithm documentation, anti-discrimination guarantees, human oversight, and assessment traceability.

What this means in practice for a Spanish SME

The most common reaction from HR Directors when the AI Act comes up is clear: "that can wait." For most SMEs, it's something on the radar but not on the immediate agenda. And that's understandable: day-to-day, there are more urgent problems.

Still, there's a practical reason to consider it right now: if you choose a platform that already works with transparent and auditable criteria, because it's designed to comply with the AI Act, you'll be in a much better position when the regulation becomes urgent. Not as a competitive advantage, but as simple risk management.

If you're evaluating AI assessment tools, include in your list of questions to the provider: Can you document how the algorithm works? What mechanisms does it have to detect bias? Is it planned that a human professional can review and reverse any recommendation? If the answers are evasive, that already tells you something.

Prior labor obligations before implementation

In addition to the AI Act, there are three legal obligations in the Spanish context you need to know before deploying any algorithmic assessment system:

1. Information to the works council (Art. 64.4.d of the Workers' Statute). If your company has a works council or employee representatives, they must be informed before implementing an AI assessment system about the algorithm's parameters and rules. This is not a recommendation: it's a legal obligation.

2. Algorithmic transparency (Law 12/2021, "Rider Law"). The company is obligated to inform employee representatives about the parameters, rules, and instructions of the algorithm used to make or support decisions that affect working conditions.

3. Data Protection Impact Assessment (GDPR, Art. 35) and LOPDGDD. Continuous collection of employee performance data to generate competency profiles requires a DPIA before deployment. The employer, not the platform provider, is the data controller. The LOPDGDD (Organic Law 3/2018) adds specific guarantees about digital privacy in the workplace.

Practical recommendation: Consult an employment lawyer before signing the contract with the provider, not just before deployment. The contract must include data processing clauses (Art. 28 GDPR). The cost of that consultation is insignificant compared to the risk of a collective dispute or a penalty.

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How to Get Started with AI Competency Assessment in Your Company

If you run an SME of 50 to 200 people and your HR team is you and one other person, or just you, this is what makes sense to do, in order. You don't need a dedicated L&D team or a consulting budget.

1Define which competencies are critical for your business

Before measuring anything, you need to know what you want to measure. Don't talk about generic competencies. Talk about the specific skills and behaviors you need from people in the roles that most impact your business.

What are the three competencies without which your company cannot grow in the next two years? Start there. An initial competency map can have five or six key competencies per role family. You don't need a catalog of forty to get started.

If your company is betting on AI as a productivity lever, assessing digital competencies and AI tool usage should be a priority. According to Microsoft & isEazy (2025), 56% of surveyed professionals cite prompting as the most in-demand AI competency for 2025-2026: knowing how to formulate instructions to get useful results from a generative AI tool.

Competency map: a step-by-step practical guide for HR →

2Choose a tool suited to your company's size

Not all AI competency assessment platforms are designed for SMEs. Before tools like Skillia, the norm was an Excel spreadsheet with manual assessment templates, a Google Forms survey, or simply nothing structured: the manager "knew" who needed what training, and HR drafted the TNA manually based on intuition and the requests coming in from departments. That's the real starting point, and what a specialized platform replaces.

Some platforms require months-long implementation, a dedicated technical team, and budgets designed for companies of 500 or more people. Look for a tool you can get running in weeks, not months. One that doesn't require hours of configuration for each assessment. One that complies with the AI Act.

The most important criteria for a company of 50 to 200 employees: ease of implementation without a technical team, integration with the tools you already use (HRIS, training platform), AI Act compliance, and the ability to connect results with FUNDAE planning.

3Connect results with your training plan and FUNDAE

This is the step most people skip, and it's the most important. Competency assessment only has value if what you detect becomes action: a concrete training plan, with dates, with responsible parties, and with FUNDAE credit assigned.

If assessment results don't reach the training plan, you've done the diagnosis but not the treatment.

4Establish a continuous assessment cycle

Annual assessment makes sense as a formal review moment. But if you only assess once a year, you're making decisions about people with data that may be twelve months old.

Establish a rhythm: quarterly reviews of the tool's data, and a formal biannual or annual assessment connected to each person's development cycle. You don't have to hold more meetings. You have to hold better meetings, with data on the table.

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Frequently Asked Questions About AI Competency Assessment

What exactly is AI competency assessment?

AI competency assessment is an automated process that analyzes performance data from multiple sources to identify the real skills of each employee and detect gaps relative to the competencies required by their role or the company's strategy. Unlike traditional assessment, it doesn't depend on the direct manager's judgment but on objective and continuous data, reducing bias and providing a more reliable view of organizational capabilities.

Can AI replace the manager in competency assessment?

No, and no serious tool should claim otherwise. AI provides objective data and a cross-functional view the manager cannot have. But the manager provides context, knowledge of the person, and responsibility for the decision. The European AI Act (Regulation EU 2024/1689, Article 14), in fact, explicitly requires human oversight in any decision affecting employees. AI is a tool to support the manager's judgment, not a replacement.

Is it legal to use AI to assess employees in Spain?

Yes, it is legal, but subject to several layers of regulation worth knowing before implementation.

AI Act (Regulation EU 2024/1689): Full application from August 2026. Classifies AI systems in HR as "high risk" and requires algorithm documentation, anti-discrimination guarantees, human oversight, and traceability. AESIA (Spanish AI Supervision Agency) is the supervisory body in Spain.

Workers' Statute (Art. 64.4.d): If the company has a works council or employee representatives, they must be informed before implementing any algorithmic assessment system about its parameters and rules.

Law 12/2021 ("Rider Law"): Requires informing employee representatives about algorithm parameters used in decisions affecting working conditions.

GDPR (Arts. 35 and 22) and LOPDGDD (Organic Law 3/2018): Continuous collection of employee performance data to generate competency profiles requires a DPIA before deployment. The Art. 22 GDPR establishes that no decision can be based exclusively on automated processing if it produces legal or significant effects on the employee — human intervention must be real and decisive, not cosmetic. The employer is the data controller, not the platform provider. The LOPDGDD adds specific guarantees about the right to privacy in the use of digital devices in the workplace (Arts. 87-91).

Practical recommendation: Consult an employment lawyer before signing the contract with any algorithmic assessment provider — not just before deployment, but before contracting, as the contract must include data processing clauses (Art. 28 GDPR). It's not unnecessary bureaucracy: it's basic legal risk management.

What is the difference between performance appraisal and competency assessment?

Performance appraisal measures results: what a person has achieved in a given period (goals met, KPIs reached, projects completed). Competency assessment measures capabilities: what the employee knows how to do, what skills they have, and which they lack to perform better in their current or future roles. They are complementary, not alternatives. Performance measures the what; competencies measure the how. AI competency assessment is especially useful for anticipating gaps before they impact performance, and for connecting them directly to FUNDAE credit.

How can I start assessing competencies with AI in my company?

The most practical starting point is to try it yourself first. Skillia's free AI competency assessment takes less than 25 minutes and gives you your level in the most in-demand AI competencies plus a personalized development plan. This gives you a clear picture of how the process works and what kind of data it generates before rolling it out to your team. Before assessing, be clear on one thing: what three competencies are critical for your business in the next 12 months. [Assess your AI competencies →]

Can I subsidize training derived from competency assessment with FUNDAE?

Yes, but with an important clarification: what is subsidizable is the training derived from the assessment, not the assessment platform itself. A subscription to an assessment tool is not eligible for FUNDAE; the courses designed from the assessment results are.

The correct process: competency assessment → Training Needs Analysis (TNA) → annual training plan → FUNDAE subsidy processing through an accredited training organization or with own SEPE accreditation.

Key points before planning:

• The credit expires on December 31 as a general rule. Companies with fewer than 50 employees can apply to accumulate unused credit for up to two additional years (application before June 30).
• Companies with more than 5 employees have co-financing obligations: 5% for 6-9 employees, 10% for 10-49, 20% for 50-249, 40% for 250+ (Law 30/2015, RD 694/2017). FUNDAE does not cover 100% of training costs.
• The subsidy is applied as a deduction on the TC1 form for the month the training action ends (or the following month).
• The vast majority of SMEs process the subsidy through their accounting firm or an accredited training organization. You don't have to handle the bureaucracy alone.
• FUNDAE administrative management has real complexity: prior communication, follow-up documentation, record retention for possible audits. A TNA backed by data reduces risk in reviews, but doesn't eliminate the need for administrative management.

A TNA based on objective assessment data is the strongest argument in any external review.

What are the main risks of using AI in competency assessment?

The main risks are algorithmic bias, lack of transparency, and regulatory non-compliance. Algorithmic bias occurs when systems are trained on historical data that reflects existing biases. To mitigate them: require your provider to provide algorithm documentation, anti-discrimination guarantees, and AI Act compliance. Always maintain human oversight over relevant decisions.

Why do 63% of employers consider the skills gap their main barrier?

According to the World Economic Forum, Future of Jobs Report 2025, 63% of employers identify the skills gap as the biggest obstacle to their business transformation. The pace of technological change, especially AI adoption, is creating new skill needs faster than traditional training systems can fill them. Without rigorous competency assessment, it's impossible to design an effective development strategy.

Which AI competencies should I assess first in my team?

The most in-demand AI competencies for companies in 2025-2026 are, according to Microsoft & isEazy (2025): effective prompting (knowing how to formulate instructions to get useful results from generative AI tools), change management, and ethical AI governance. The practical starting point: first assess the competencies directly related to the tools you've already invested in, to identify whether the perception/reality productivity gap highlighted by Adecco also exists in your organization.

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Conclusion: Competency Assessment Isn't the Destination — It's the Starting Point

Artificial intelligence hasn't made it easier to ignore your team's competencies. It's made ignoring them more expensive.

If your employees are using AI tools but you're not seeing the impact in results, the problem isn't the technology. It's that you don't know what competencies they actually have to leverage it. If you have a FUNDAE credit that renews each year and you keep choosing the same courses, the problem isn't the budget. It's that you don't have the data to decide better.

AI competency assessment gives you that data. And when you have it, things that were previously intuition start to make sense: who to promote, where to invest in training, how to prepare the team for what's coming.

The good news for the HR Director of a Spanish SME: you have a training credit assigned by law that you can invest exactly where competency assessment demonstrates there's a real gap. Not in the usual course catalog, but in the real needs of your team, detected with data.

AI competency assessment isn't a surveillance tool. It's the diagnosis that turns training from an administrative expense into a data-driven decision.

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Ready to assess your team's AI competencies? Tell us about your case and we'll show you how it works in practice. Request a demo →

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References

1. [1] World Economic Forum (2025). The Future of Jobs Report 2025. ↗ Fuente
2. [2] World Economic Forum (2025). Future of Jobs Report 2025: 78 Million New Job Opportunities by 2030. ↗ Fuente
3. [3] ManpowerGroup España (2024-2025). Talent Shortage Study. ↗ Fuente
4. [4] Adecco Group España (2025). Global Workforce of the Future Report 2025. ↗ Fuente
5. [5] Deloitte (2025). 2025 Global Human Capital Trends Report. ↗ Fuente
6. [6] Microsoft & isEazy (2025). AI Use in HR and Training. ↗ Fuente
7. [7] McKinsey & Company (2025). AI in the Workplace / Superagency in the Workplace 2025. ↗ Fuente
8. [8] Regulation (EU) 2024/1689 of the European Parliament and of the Council (AI Act). ↗ Fuente
9. [9] MBIT School (2025). European AI Regulation: How to comply with the AI Act in Spain 2025. ↗ Fuente
10. [10] SEPE (2025). Prospecting and Training Needs Analysis Report 2025.
11. [11] FUNDAE (2025). Subsidized training credits, bands by company size. ↗ Fuente
12. [12] Law 12/2021, of 28 September, amending the consolidated text of the Workers' Statute Law ("Rider Law").