#WomenInTech: Eva Aranda helps companies realise the potential of AI

June 17, 2026

What do you do, and what path led you there?

I work in data and Artificial Intelligence consulting, although my speciality, and the part of my job I enjoy most, is AI Governance. In other words, I help organisations realise the potential of Artificial Intelligence in a way that is responsible, secure and centred on people.

Ever since I was young, I have loved mathematics and solving logic problems. When the time came to choose a degree, I decided to turn that passion into my profession. I studied Mathematics and later completed a master's degree in business to complement the more theoretical side of my studies with a practical perspective that was closely aligned with the real needs of organisations.

Since then, my algebra problems and equations have been replaced by real customer challenges, and my job has become helping them tackle those challenges and reduce complexity in creative ways while delivering as much value as possible.

AI Governance makes it possible to realise AI's potential in a way that is responsible, secure and centred on people.

How would you define AI Governance, and why has it become a strategic priority for companies?

When we talk about AI Governance, we are talking about establishing the rules, processes and controls needed for an organisation to develop and use AI in a secure, ethical way that is aligned with its business objectives. It is not about slowing innovation down, but about enabling sustainable adoption that builds trust both inside and outside the organisation.

Over the last few years, we have seen AI evolve from a technology used by highly specialised teams into something that is within reach of virtually every employee. This multiplies the opportunities, but also the risks. A wrong decision made by an AI system can create regulatory issues, damage a company's reputation or even lead to significant financial losses.

Governing AI does not slow innovation down; it enables sustainable adoption that builds trust.

In addition, the AI Act, the European regulation governing the use of Artificial Intelligence, has been a clear driver of this need for governance, although it remains only part of the equation. More and more organisations understand that governing AI from the design stage onwards is also a competitive advantage. To achieve this, it is essential to know which AI systems exist within the organisation and to have clear processes in place to assess and monitor their risks throughout their lifecycle.

What is the main challenge facing a consultant specialising in AI Governance within a technology company such as Telefónica Tech?

One of the distinctive aspects of AI Governance is that it requires very different people to sit around the same table. Within a single project, you may be speaking with lawyers, business leaders, data scientists, developers or cybersecurity experts. Getting everyone to speak a common language and understand that Responsible AI is a shared responsibility is not always easy, but it is certainly one of the most interesting parts of the job.

In addition, through the Strategic Consulting CoE, we are helping to build and strengthen this area of expertise within Telefónica. This requires a great deal of awareness-raising, training and evangelisation, both internally and externally with our customers. Seeing more and more colleagues and customers understand the value of AI governance and start incorporating it into their initiatives is, without doubt, one of the most rewarding parts of my work.

Responsible AI is a shared responsibility that requires a common language across very different disciplines.

What are the key factors for a company to become a benchmark in AI Governance?

For me, a leading organisation is not necessarily the one with the greatest number of AI use cases or the highest level of technological maturity. It is the one that has successfully integrated AI across the organisation in a controlled and sustainable way.

Compliance with regulation is important. Staying ahead of the AI Act implementation timeline, establishing assessment and monitoring processes for AI systems, and adopting standards such as ISO 42001 are all fundamental steps. However, the real challenge emerges when AI stops being something occasional and becomes embedded across multiple processes and areas of the organisation.

AI Governance maturity is demonstrated by scaling oversight and control consistently.

The most advanced organisations are those capable of maintaining the same level of traceability, oversight and risk management regardless of how many systems they use. In this context, AI Governance tools are becoming a key enabler for scaling these processes efficiently. Governing three systems is relatively straightforward; governing hundreds or thousands of them while maintaining consistency and the same level of control is where true AI Governance maturity is demonstrated.

When you assess an AI system, which risks tend to concern companies the most, and why?

One of the most common risks is related to data. Many organisations fully understand the value that generative AI can deliver, but they are concerned about what information they are sharing, where it is stored and who can access it. In reality, this is often not a new problem, but rather a classic privacy and data protection challenge that AI has amplified because of the speed and ease with which it is used.

Another risk I frequently see among customers is a loss of visibility over the AI being used within the organisation. Adoption is happening so quickly that AI use cases sometimes emerge without clear processes in place to assess or monitor them, which, as we discussed earlier, is essential for effective governance.

When a company does not know which AI it is using or what data it relies on, managing any other risk becomes extremely difficult.

In this context, having a centralised inventory of AI systems is essential, as it makes it possible to understand which solutions exist, where their risks have been assessed and what measures have been adopted to mitigate them. When an organisation does not know which AI it is using, what it is being used for or what data it relies on, managing any other risk becomes extremely difficult.

What changes will companies need to make in order to achieve AI that is responsible, trustworthy and aligned with their corporate values?

First and foremost, organisations will need to define clear Responsible AI principles for the development and use of AI, and ensure that they are applied throughout the entire lifecycle of their systems. Aspects such as fairness, traceability, transparency and human oversight will become increasingly important.

It will also be essential to strengthen data protection measures. The GDPR (General Data Protection Regulation) remains fully in force and, whether in generative or agentic solutions, organisations must understand what information they are sharing, with which providers and under what safeguards, in order to avoid losing control of their data.

Finally, the responsible adoption of AI will require a sustained effort in training and awareness. It is essential to have an AI literacy programme tailored to different roles and levels of knowledge, helping to promote appropriate use and reduce the risks associated with the misuse of AI.

The responsible adoption of AI requires clear principles, data protection and a shared culture.

In this regard, internal communication also plays a key role through initiatives such as blogs, newsletters and educational content, helping to reinforce a culture of Responsible AI as a shared responsibility across the entire organisation.

What does diversity of backgrounds bring to a strong AI Governance strategy?

AI Governance is probably one of the most multidisciplinary fields within the technology sector. No single person has all the knowledge required to assess the full impact of an AI system. In practice, this becomes very clear within teams.

A technical specialist understands how the model or system works, a legal professional identifies regulatory implications, ethics experts help challenge potential societal impacts, and business teams provide the real-world context in which the technology will be used. It is the combination of all these perspectives that makes it possible to design systems that are safer, more responsible and more closely aligned with their intended purpose.

That is precisely why I believe diversity is not only desirable, but necessary. The more perspectives we bring together, the greater our ability to identify risks early, anticipate impacts and build solutions that take into account the people who will use or be affected by the technology.

Diverse perspectives make it possible to identify risks, anticipate impacts and build more responsible solutions.

What advice would you give to girls and young women who would like to pursue a career in this field?

If they genuinely enjoy technology and are curious about it, I would encourage them to be brave and go for it. They should not see being a woman as a limitation. Talent, innovation and leadership are not defined by gender, and technology needs people who are eager to learn, contribute and build.

I would also tell them that we are living through a unique moment. AI is evolving at an incredible pace and that requires us to keep learning constantly, but it is also creating opportunities that did not even exist a few years ago. If they enjoy solving problems and stepping outside their comfort zone, they will be hard pressed to find a more stimulating field.

I am not going to say it is always easy; there will be moments of uncertainty and challenges that seem enormous. But there is also something incredibly rewarding about looking back and realising how much you have learned and how much you have grown in such a short period of time. At least for me, that feeling more than makes up for any effort involved.

Technology needs people who are curious, eager to learn and brave enough to take on new challenges.

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