C-Suite Synergy: Breaking Silos to Deliver on Data & AI Ambitions
Speakers: Abbi Agana (Leathermarket JMB), Louise Herring (Brambles), Matt Webb (UK Power Networks), Sarah Barron (Domino’s Pizza UK & Ireland)
This first leadership panel explored how data success depends on C-suite alignment that drives measurable value, not just structural coordination.
Key insights:
- Strategic integration beats functional excellence. Merging digital, strategy and data leadership eliminates “vanity innovation,” ensuring every project maps to defined business outcomes.
- Shift from enablement to accountability. Data teams must no longer act as service providers but as joint owners of KPIs alongside business units.
- Continuous reprioritisation is now a leadership discipline. The panel agreed that agility, not architecture, determines impact and strategies must evolve as market conditions shift.
- Collaboration as currency. The new measure of success for data leaders is how effectively they create connection and shared language across the executive team.
Establishing a Robust, Scalable Framework for Managing Data Governance in the Age of Generative AI
Speakers: Elizabeth Osta (DataIQ), Jonathan Davis (Zurich Insurance UK), Oleg Kravets (The Travel Corporation), Pete Edmonds (Aviva), Shahina Khan (SMBC Group), Sian McHenry (Nationwide Building Society)
Generative AI has changed the calculus of data governance. The conversation moved beyond compliance to how leaders can operationalise trust at scale while enabling rapid innovation.
Key insights:
- Dynamic governance models are emerging. Organisations are moving toward modular governance frameworks that evolve in parallel with new AI use cases rather than lag behind them.
- Accountability must extend into the algorithm. Panellists highlighted the need for data governance to explicitly cover AI-generated content and decision outputs.
- Governance as a growth enabler. Examples of governance frameworks designed to accelerate model deployment were shared which included treating auditability and explainability as accelerators of stakeholder confidence.
- Investment in literacy. Speakers underscored that the biggest barrier is cultural readiness, even more than regulation: leaders must invest in board-level understanding of data risk.
Enhancing Clinical Workflows with Generative AI
Speaker: Ming Tang, Chief Data and Analytics Offer & Chief Digital and Information Officer (interim), NHS England.
Healthcare provided perhaps the day’s most vivid example of purpose-driven transformation.
The NHS showcased its ongoing digital overhaul, moving from disjointed systems to intelligent, interoperable workflows powered by data and AI.
Key insights:
- NHS app is one of the largest public sector apps in use, with potential to integrate data from 240 NHS organisations.
- Small-scale pilots, systemic vision. Rather than broad digital mandates, NHS teams are pursuing targeted interventions that reduce friction in existing clinical tasks while building evidence for scale.
- Adoption of voice-assisted technology frees time for clinicians, improving employee wellbeing and enabling them to focus on patient outcomes. This underscores that the future of AI in healthcare is augmentation, not automation.
Progressing AI Pilots to Successful Deployment
Mastercard’s Vice President for Agentic Experience Strategy, Mara Pometti, explored the “pilot trap” where innovation labs thrive, but enterprise adoption lags.
Key insights:
- 90% of pilots fail for cultural, not technical, reasons. Adoption falters when AI lacks emotional usability, such as when people don’t see its relevance to their work.
- Design for adoption from day one. Integrate behavioural science into AI design that make tools intuitive, explainable and visibly beneficial to end users.
- Agentic AI is the next organisational design challenge. Focus on systems that can act autonomously yet remain accountable. This signals a new era where AI becomes a co-worker, not just a computational engine.
- Value creation requires storytelling. Leadership must narrate how AI success links to business ambition and reframe technical wins as cultural progress.
Raising Visibility, Shaping the Profession: What Recognition in the DataIQ 100 Really Means for Leaders
Speakers: Amy Lenander (Capital One), Caroline Bellamy (Ministry of Defence), Johanna Hutchinson (BAE Systems), David Reed (DataIQ)
The closing session reframed professional recognition as a strategic lever for diversity, visibility and cultural change across the data and AI community. Far from being symbolic, inclusion in the DataIQ 100 plays a tangible role in elevating underrepresented voices and showcasing the breadth of leadership shaping the profession.
Key insights:
- Visibility drives representation. Public recognition has a multiplier effect, inspiring emerging leaders and validating the work of teams that often operate behind the scenes. Recognition turns invisible impact into visible influence.
- Recognition as a leadership platform. Visibility comes with responsibility and should be used to mentor, advocate and model the values of openness and accessibility within technical leadership.
- Diversity through design. Professional recognition has a unique value within the public sector where hierarchies and traditional pathways can obscure digital and data talent. Recognition programmes help surface and legitimise new kinds of leadership.
- The DataIQ 100 encourages for collective accountability, ensuring that the data profession continues to broaden its definition of leadership, celebrate diverse expertise, and promote role models who reflect the communities they serve.
