Adam Cresser is Data and AI Director at Notting Hill Genesis, where he leads the organisation’s data and AI agenda with a clear focus on outcomes, impact, and value.
He began his career on the frontline of social housing, where the direct impact on people’s lives mattered more than metrics. That experience shaped his values and continues to inform his approach to data leadership: technology is only useful when it delivers meaningful outcomes. Over more than 12 years in senior leadership roles, Adam led operational housing services, compliance and business improvement through mergers, periods of change and organisational crises. These roles developed the core skills that underpin his data leadership today, including influence, communication, strategic clarity, and delivery at pace.
Five years ago, Adam pivoted formally into data leadership, bringing with him a strong business-first mindset. Rather than approaching data as a technical discipline in isolation, he focused on solving real organisational problems and surrounded himself with deep technical expertise. Building an understanding of data and AI enabled him to amplify his transferable leadership experience and accelerate impact.
Since then, Adam has developed and delivered one of the housing sector’s first comprehensive data strategies. His work has been recognised by organisations including DAMA, Housing Technology and DataIQ, reflecting both innovation and practical impact.
Adam views data leadership as leadership full stop: setting a clear direction, building capability and creating the conditions for people to do their best work.
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 and influence come first. In a traditional sector, stakeholders rarely arrive with well-formed asks. You need curiosity, empathy, and credibility to surface the right problems, build trust, and tell compelling value stories. It’s the difference between being seen as a cost and being recognised as a strategic enabler.
“Strategic and critical thinking matters: joining the dots across regulatory, commercial and political contexts; aligning data and AI to what’s topical and material; and choosing the right idea, at the right time, with the right sponsor. You obviously bring your technical knowledge on capabilities to that. Strong networks ensure you’re in the right conversations.
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?
“Don’t let perfect be the enemy of progress; balance theory with pragmatism and pace. A mentor once reminded me, pretty sure it was copied from Keynes, that ‘we’re all dead in the long run.’ In practice: long term architectures and best practice models matter, but if people don’t feel impact soon, you’ll lose trust and momentum, and not last.
“Design every initiative with a 90-day outcome and a North Star. Deliver something tangible early (reduce a risk, save time, improve a decision) while building the foundations that avoid technical debt. Earn the right to do the hard stuff by solving real pain, quickly. Measure it. Tell the story. Then iterate.
“This approach sustains sponsorship, motivates teams, and keeps strategy grounded in value.”