Programme topic
Governance & risk
Governance becomes an engineering concern when AI affects credit, education, audit or regulated decisions. These talks connect sovereignty, compliance and auditability to concrete system choices teams can test and defend.
8 published talks
Talks about governance & risk
Building AI for students who can't tell you when it's wrong
Ez HerrmannTechnical Solution Architect, Sitback Solutions
Teachers in Australian specialist schools spend two hours or more preparing a single lesson, then adapt it again for every ability group in the room. Many are already pasting student details into consumer chatbots to keep up. That shadow AI is ungoverned,…
How we introduced LLMs into credit decisioning
Kevin NguyenSenior Product Engineer, Skip
Over the past nine months we've built and deployed an AI-assisted credit assessment system that's now used in production to help credit assessors process home loan applications. More importantly, it was signed off by our founders and risk underwriters.…
Sovereignty Is an Inference Problem
Leo BorgesChief Engineer - GenAI, Commbank
**AI sovereignty isn’t about where the GPUs sit. It’s about who can switch the intelligence off.** Australia is spending billions on sovereign AI infrastructure. But onshore compute running models subject to another country’s export controls is still a…
From Documents to Defensible Evidence: Rethinking RAG for Audits
Sharat MadanapalliFounder, InTune AI
Audits impose strict requirements for evidence, traceability and expert judgement. Each entity being audited supplies a new body of evidence, made up of manuals, records, tables, diagrams, scans and multilingual documents. Assessment against an audit standard…
Regulated Doesn't Mean On Rails: what compliance actually asks of your engineers
Stephen SennettPrincipal Forward-Deployed Engineer - Applied AI, V2 AI
We spent three months rebuilding a regulated enterprise's development lifecycle around agents, then worked out how much of the governance we had added was doing real compliance work. Less than we assumed. Across APRA's prudential standards, the ISM, SOC 2 and…
Where Should the Dice Roll? Placing Non-Determinism Deliberately in Enterprise AI
Vighnesh DeshpandeAI Engineer, Vivanti Consulting
Most production AI guidance assumes you want consistency: pin the prompt, lower the temperature, eval for drift. But a whole class of enterprise use cases - idea generation, recommendation, exploration, synthesis - is worthless if the output is predictable.…
Lessons from Economics for the Human / Agent Software Workforce
Daniel NadasiPrincipal Engineer, Google
AI is reshaping software engineering, creating uncertainty about how engineering roles will change as increasingly capable systems take on work that was once performed by people. While no one can predict the future with certainty, history offers examples of…
Token usage is the new lines of code (and it's just as useless)
Fawaz AhmadSenior Engineering Director, Canva
Canva hit mid-2026 with every AI metric a vendor could hand us and no answer to the only question the business actually cared about: is this working? Adoption flattened at around 85% of ~3,000 engineers, and the number stopped telling us anything. AI touched…