# Governance & risk — AI Engineer Sydney 2026

> 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.

Canonical page: https://webdirections.org/ai-engineer/topics/governance-risk/
Program status: The speaker lineup and talk descriptions are public. Session days, times, rooms and the full timetable have not yet been published.

## Published talks

- [Building AI for students who can't tell you when it's wrong](https://webdirections.org/ai-engineer/speakers/ez-herrmann/) — Ez Herrmann
  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, inconsistent and potentially harmful. We built IRIS with the Alannah & Madeline Foundation, a Trusted…
- [How we introduced LLMs into credit decisioning](https://webdirections.org/ai-engineer/speakers/kevin-nguyen/) — Kevin Nguyen
  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. Starting from a simple assumption, the same application should receive the same outcome regardless of who…
- [Sovereignty Is an Inference Problem](https://webdirections.org/ai-engineer/speakers/leo-borges/) — Leo Borges
  **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 dependency. Owning the building isn’t owning the model. Enterprises have the same blind spot. Running one…
- [From Documents to Defensible Evidence: Rethinking RAG for Audits](https://webdirections.org/ai-engineer/speakers/sharat-madanapalli/) — Sharat Madanapalli
  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 follows defined guidelines and requires precise citations. A plausible answer has little value if an…
- [Regulated Doesn't Mean On Rails: what compliance actually asks of your engineers](https://webdirections.org/ai-engineer/speakers/stephen-sennett/) — Stephen Sennett
  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 ISO 27001, the same four obligations recur: traceability, change management, testing proportionate…
- [Where Should the Dice Roll? Placing Non-Determinism Deliberately in Enterprise AI](https://webdirections.org/ai-engineer/speakers/vighnesh-deshpande/) — Vighnesh Deshpande
  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. The engineering problem flips: how do you make variance useful, keep it safe, and convince a…
- [Lessons from Economics for the Human / Agent Software Workforce](https://webdirections.org/ai-engineer/speakers/daniel-nadasi/) — Daniel Nadasi
  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 how technical innovation has transformed work in other industries and provides useful ways to think…
- [Token usage is the new lines of code (and it's just as useless)](https://webdirections.org/ai-engineer/speakers/fawaz-ahmad/) — Fawaz Ahmad
  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 43% of PRs, PR volume was up 44% year over year (and growing week-over-week), but none of us could…

The timetable is not public. This page does not imply a day, time, room or track.

- [Explore the whole programme](https://webdirections.org/ai-engineer/program/)
- [Conference overview](https://webdirections.org/ai-engineer/index.md)