
ASP AI & Data is led by Andrew Prosia, a data and delivery specialist with a decade of experience turning complex, fragmented enterprise data into trusted foundations for reporting, analytics, and AI.
Andrew currently leads data delivery as Head of Delivery, Data & AI Enablement at a large health insurer, where he runs a team of ten engineers and analysts building the trusted, production-grade datasets that enable AI and advanced analytics across the organisation. In that role he owns the end-to-end delivery of a single source of truth — reconciling data and competing definitions across Actuarial, Finance, and Claims Intelligence — and manages senior executive stakeholders across those functions to agree, govern, and prioritise what "the truth" actually is. It's exactly the problem most large organisations face, and exactly what ASP AI & Data was built to solve.
Before that, Andrew delivered enterprise data and analytics programs through EY's AI & Data practice and Accenture's Strategy & Consulting pillar, across private health insurance, medical indemnity, one of Australia's Big 4 banks, and a large government telco transformation. His work spans customer-360 data products, legacy-to-cloud claims migrations, enterprise reporting modernisation, master data management, and executive-grade BI in regulated environments.
He is hands-on across Azure Databricks, Power BI, SQL, and SAS, fluent in medallion architecture, Delta Lake, and SCD patterns, and delivers in Scaled Agile as a certified SAFe Scrum Master. He holds a Bachelor of Science (Data Science) from the University of Melbourne.
We own outcomes end to end — discovery through production and handover — in Scaled Agile environments, managing cross-functional teams of engineers and analysts.
Every dataset we build is engineered for quality, lineage, and governance from day one, so it can safely feed AI, models, and executive reporting.
We routinely align Actuarial, Finance, Claims, and Operations stakeholders on a single agreed definition of the truth — the hardest part of most data programs.