David Thomas, Chief Data Officer at London Stock Exchange Group, has spent 24 years working across a wide range of data roles in organisations with markedly different cultures. Each role has contributed to what he describes as a “library” of experience, a practical reference point he draws on when addressing new challenges, encompassing both what has worked and what has not.
Across that variety, one constant has shaped David’s approach: a sustained focus on how data creates value for internal stakeholders and external customers. This perspective was strongly influenced by his first mentor in the industry, who emphasised revenue generation and client relationships alongside technical delivery. That mindset continues to sit at the centre of his strategy, particularly in how he approaches AI implementation.
For David, data and AI initiatives must be grounded in clearly articulated benefits. Every strategic component and objective is expected to deliver tangible value, whether meeting policy and regulatory obligations, addressing customer needs, or enabling effective AI delivery.
David is committed to delivering durable, enterprise-scale solutions across data governance, as well as catalogue and metadata products, ensuring that foundational capabilities can support both current requirements and future innovation.
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?
“Communication. Increasingly, data leaders need the ability to articulate their strategy across a wide range of internal stakeholder and client communities. Communication skills are an essential part of this journey and landing key messages at all levels of organisations (board through to new joiners) is critical.
“Relationship-building. Over the last ten years, the number of stakeholders I speak to on a regular basis has grown exponentially. The success of our strategy, from development and syndication through to execution, is based on the ability to land this and make it relevant to our stakeholders. Building strong relationships that enable education (in both directions) and constructive challenge has enabled the team to ensure our strategy is meeting requirements or addressing stakeholder issues.
“Agile and change-focus. The data leader role has changed dramatically in the last 15 years, and AI promises to provide new challenges in the years to come. Leaders and their teams need to continuously evolve and challenge the status quo.
“Tech-aware. Many data leaders (me included) do not have a technical background and that is not an impediment to being a good leader in the current environment. However, it is essential to understand the relevance and power of evolving technology. Using technology to support a data governance strategy has been increasingly important and AI requirements are only going to accelerate this in the next few years.”
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?
“Put simply, networking with your ears open! Most of the data community is very happy to talk about our strategy and the complexities of the data governance journey but the real challenge and path to longer-term success is to ensure that what we deliver benefits the wider organisation and onward clients.
“To achieve this, we need to first listen to our stakeholders and to identify their requirements and how data can support these. The real skill is to allow the stakeholders to educate us on their requirements and to be able to focus in on the areas where a strong data strategy address some of the challenges they are facing. A business-first data strategy, aligned to the wider organisation objectives, is far more likely to succeed and key data teams relevant than one that is developed in isolation.”