I have spent my career at the intersection of business and technology, translating complex technical decisions into clear commercial choices, and commercial ambition into systems that hold up under load.
That has meant carrier-grade networks and satellite programs at national scale, enterprise data platforms and AI-enabled automation, turnarounds where the numbers had to move in months rather than years, and cyber and governance uplift that had to satisfy a board as well as an engineer. Across all of it, the constant has been the operating model: clear accountabilities, disciplined delivery cadence, and benefits tracked to a number.
The part I care most about is the people. I build multi-disciplinary teams across product, engineering, security and operations, and coach leaders to make their own calls, so capability stays in the business after the program closes. I am approachable by design and steady when things are not going to plan; that combination is usually what makes transformation survive contact with reality.
AI only creates value when it is wired into the operating model, not bolted onto it.
I build enterprise AI strategy the same way I build any transformation: a clear view of where the margin and the risk actually sit, a governed data foundation that can be trusted, a small number of use cases sequenced by value and feasibility, and benefits tracked to a number the CFO recognises. Guardrails go in first: data lineage, access control, human-in-the-loop review and auditability.
In practice that has meant agentic AI across onboarding, compliance and training; predictive demand forecasting and AI-enabled rostering that reduced rostered hours; and executive analytics that replaced manual reporting cycles. Just as important is the capability side: bringing leaders and frontline teams with you, so AI becomes something the organisation uses with confidence rather than something it is subjected to.
AI strategy & roadmap
Use-case discovery, value cases, sequencing, target operating model and the investment story for the board.
Data foundation & governance
Cloud data architecture, quality and lineage, definitions and audit controls, the prerequisite everyone skips.
Adoption & responsible AI
Human-in-the-loop design, risk and compliance alignment, capability uplift and change that actually lands.
Enterprise & digital transformation
Roadmaps, target operating models, benefits tracking and the governance to keep multi-stream programs honest.
Data, analytics & AI enablement
Unified data ecosystems, predictive forecasting, agentic automation and self-serve executive reporting, governed and responsible.
Cloud & platform modernisation
Azure and AWS migration, hybrid architecture, legacy rationalisation and measurable cost-to-serve reduction.
Cyber resilience & governance
Security frameworks, Essential Eight alignment, identity and access, risk and compliance uplift for regulated environments.
Engineering & delivery operating model
Agile ways of working, CI/CD and DevOps, quality discipline and release cadence measured in weeks, not quarters.
Commercial, contract & vendor leadership
Major enterprise negotiation, partner ecosystems, vendor turnaround and P&L accountability up to $20M+ budgets.
Open to board, advisory and executive conversations.
Based in Melbourne, working globally. If you are weighing an AI strategy, a transformation, a turnaround, or the chief technology voice on your board, I am glad to talk it through.
And if your team needs mentoring, whether that is emerging technology leaders or engineers stepping into their first management role, feel free to reach out. I make time for it.