Change Adoption Lead
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About the role
QBE Europe is recruiting a Change Adoption Lead to join the EO Data & AI function and help embed the Data & AI strategy into everyday ways of working across the organisation. The role focuses on data‑related change that sits outside funded transformation - including BAU process improvements, non‑funded initiatives, and the ongoing onboarding and effective use of existing data and analytics platforms. The Change Adoption Lead would work closely with the Business Change practice, which leads on change adoption for data initiatives funded through the central transformation portfolio. Sitting within the Data Strategy & Operations capability, the Data Adoption Lead plays a critical role in sustaining momentum between data change initiatives and BAU initiatives over time. You will connect change activity across EO into a clear, coherent narrative that shows how the data strategy is being implemented in practice, reinforces consistent data ways of working, and supports lasting adoption beyond individual project lifecycles. Having the right to work in the UK is a requirement for this role. QBE may consider sponsorship at its discretion. About QBE At QBE, we get to the heart of what matters for our customers. And we do it all with a human touch. We're an international insurer with more than 13,000 people working across 26 countries - which means we're big enough for your ambitions, yet small enough for you to make a real impact. It's an exciting time. We're building momentum towards our vision to become the most consistent and innovative risk partner. What if you could have a positive impact - at work and in the world? As part of the QBE team, you'll get to spend every day working with people who are passionate, talented and kind. Your New Role Lead and coordinate adoption activity for the EO Data & AI estate outside of funded transformation programmes, ensuring continued uptake, effective use and long‑term value from existing data platforms and products. Own and maintain a clear, joined‑up adoption narrative that connects BAU change, platform evolution and transformation initiatives, reinforcing how they collectively deliver the Data & AI strategy. Create and deliver clear, compelling communications (updates, showcases and success stories) aligned to the Data & AI strategy, value-stream priorities and key milestones. Partner closely with Business Change Managers (BCMs) on funded initiatives to align messaging, timing and adoption approaches, ensuring a seamless transition from project delivery into BAU adoption. Work closely with Data Delivery Managers and key stakeholders to anticipate change impacts and align adoption activity across the data landscape. Translate complex, technical data concepts into practical, audience-specific messages that enable confident decisions and day-to-day use. Design and coordinate enablement approaches for data and analytics capabilities, including onboarding to platforms, reinforcement of data quality practices and adoption of data‑led ways of working. Build and maintain stakeholder networks across EO, including leaders, subject-matter experts and change champions, to increase reach, improve feedback loops and accelerate adoption. Define and track adoption measures and insights (engagement, usage, feedback) to evidence outcomes and continuously improve adoption approaches. Identify adoption risks across BAU and non‑funded change and recommend pragmatic mitigation actions. About You Experience in change, communications, adoption or engagement roles, ideally within data, analytics, technology or complex transformation environments. Strong written and verbal communication skills, with the ability to tailor messages and influence action across different audiences. Basic understanding of change management principles, models (e.g., Prosci, ADKAR, Kotter), and tools Experience supporting the adoption of data platforms, analytics tools, reporting or AI‑enabled capabilities. Proven stakeholder management and influencing skills, with credibility at all levels of the organisation. Ability to work collaboratively across business, technology and data teams. A structured and proactive approach to planning and delivery. A pragmatic, people-centered mindset focused on enabling outcomes rather than process for its own sake. Comfortable with a degree of ambiguity