Hywel Jon Benbow is Senior Vice President, Global Data, AI and Analytics at GEMS Education, where he leads the organisation’s data and analytics agenda with a strong focus on alignment, adoption, and decision-making impact.
His career in data has been shaped by collaboration, context, and organisational understanding. Early in his career, Hywel recognised that analytics only delivers value when it reflects how teams actually operate (their pressures, incentives and definitions of success) rather than abstract technical ideals.
As his responsibilities have grown, Hywel’s focus has centred on aligning three core elements: data assets, data products, and data insights. He has consistently found that tackling these in isolation limits impact. Instead, the greatest value is created when trusted data assets, well-designed products and contextualised insights are developed together and clearly linked to organisational goals.
Working across education, operations, customer experience and commercial functions has reinforced his belief that there is no single version of the business. Each function views decisions through a different lens, and effective data leadership must respect those perspectives. When data is trusted, products are designed around real decisions and insights are delivered with context, the impact is significantly amplified.
Hywel’s role has evolved from building reports to enabling leaders to better understand their own remits. He now focuses on embedding insight into everyday workflows, helping teams move from retrospective reporting towards earlier, more informed action. His approach positions data as a strategic partner, supporting clarity, prioritisation, and confident decision-making rather than a purely technical function.
As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?
“The most important trait for data and AI leaders is the ability to understand what drives different parts of the organisation.
“Empathy is central to this. Leaders must recognise the pressures, incentives, and constraints that teams operate under. Without this understanding, even accurate insight will struggle to influence behaviour.
“Translation is equally important. Data must be shaped so it answers the questions people genuinely need to answer. Effective leaders frame decisions rather than simply presenting information.
“Trust underpins everything. Data teams must earn trust through consistency, transparency, and reliability. Issues with data quality, even when limited in scope, can quickly undermine confidence. Once trust is lost, it takes sustained effort and time to rebuild.
“Credibility follows when stakeholders see data as a key support for professional judgement rather than a replacement for it. When these traits are present, data shifts from being a central reporting function to an enabler of better understanding and better decision-making across the organisation.
Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?
“If you want to succeed as a data leader at senior levels, focus less on being right and more on being useful.
“Invest time in understanding how others define success in their role and where decisions feel most challenging. When you can articulate someone else’s priorities clearly, you earn trust and influence.
“My advice is to lead with context rather than data. Data becomes powerful when it helps people understand their responsibilities more clearly and act with confidence.
“The most influential data leaders are not those with the most advanced tools. They are the ones invited into conversations early because they help others think more clearly and make better decisions.”