In an increasingly complex landscape, strategic advantage hinges on intelligent decision making. This briefing examines how Google Cloud's advanced AI capabilities offer Australian State and Federal Government leaders unprecedented opportunities to extract actionable insights from vast datasets, predict emerging trends, and proactively address societal challenges. Learn how AI can enhance policy development, streamline operations, and bolster national resilience, ensuring Australia remains at the forefront of innovation and effective governance.

SAP’s data and analytics solutions serve as the foundation for this data fabric; delivering an integrated, semantically-rich data layer that ensures seamless and scalable access to data without duplication.

Join this session to learn how Endeavour Energy is leveraging SAP’s data and analytic capabilities to build a flexible, business-ready data foundation critical for delivering analytical insights. We’ll explore the journey they took to get here, and the future they are building, including a look into SAP Business Data Cloud and, with Databricks, can facilitate a unified data platform to thrive in the AI economy.

AI agents are emerging as an important trend since they enable levels of business adaptability, flexibility and agility that traditional AI systems can’t achieve. This flexibility is valuable in unpredictable environments where real-time monitoring and control aren’t practical. Autonomous behaviors, despite significant societal, legal and ethical implications, are the answer to the increasing complexity in our enterprise systems.

Most metadata in 2024 will remain passive in approaches with stats, reports, schema and business-developed glossary terms. Most organizations must grow their maturity in metadata management. We start with traditional metadata techniques — passive. With AI undergoing confidence issues and the demand to reduce risk, grow AI confidence, and provide data assurance, active metadata becomes key.

With growing focus on AI in organisations, deliveringAI-ready data has become the number one investment priority of data management leaders. This session will define AI-ready data, how it differs from traditional data management and discuss AI-ready data practices and technologies.

Legacy data tools weren’t built for the AI era. Agentic Data Management replaces static rules and siloed platforms with intelligent agents that monitor, reason, and act—automating quality, governance, and lineage at scale. Discover how data leaders are shifting from manual firefighting to autonomous control, powering faster, trusted, and scalable data for AI and analytics.
See a live demo of an agentic system in action


Learn how probabilistic and deterministic approaches work in concert


Explore how to build intelligent data products using the MCP protocol

Data observability helps to detect and diagnose unknown unknowns in data quality and pipeline performance—but it doesn't fix them. Learn how Bigeye is leveraging AI to enable data teams to resolve data quality and pipeline issues, and even prevent them occurring in the first place.

Struggling to balance AI-driven innovation with security and compliance? Organisations are racing to leverage AI, advanced analytics, and the cloud for a competitive edge—but growing regulations and data protection requirements create significant challenges.
This session will provide practical strategies to maximise AI potential while safeguarding sensitive data, ensuring compliance, and mitigating risk.
Learn how to harness innovation without compromise and position your organisation for success in a rapidly evolving digital landscape.

Relying on a single model for AI solutions due to the hype of powerful GenAI models in the market is a common pitfall in AI adoption for enterprises. D&A leaders and the teams should avoid this pitfall by using systems thinking and clarifying the limitations with stakeholders. This session will introduce practices that go beyond a single model for more powerful, reliable and efficient AI solutions.

Artificial Intelligence (AI) provides enormous potential for Defence. AI will support military functions and capabilities, enhance the analysis of intelligence data, and improve the decision-making and functions of the Defence enterprise.
The Defence AI Centre has been established to accelerate the responsible adoption of AI across Defence. Dr Paul Robards, Chief Data Integration Officer in Defence, will talk about the establishment of the Defence AI Centre, the operating model that Defence has adopted, and the challenges and opportunities.

Implementing AI governance can be challenging, navigating this in the public sector is particularly so with risk focus often overshadowing value and benefits. This roundtable will explore practices in overcoming challenges to achieve success in AI Governance with specific focus on public sector aspects including data, regulations and workforce.

GenAI may excelling in some areas but fail in others, complicating the business case. CIOs often underestimate costs, which can scale by 500%-1000%. Productivity is a key benefit but hard to prove to CFOs. Should you invest in chat-style GenAI for 100K employees or near-custom AI for 50 R&D staff? Join our session to master cost scaling, value harvesting beyond productivity, and creating a portfolio of GenAI investment options.

Heads of analytics & AI face many challenges such as keeping afloat, staying the course or racing ahead in the race for AI superiority. This session will focus on the top fears, risks, objections and hurdles leaders of Analytics & AI face and most importantly, how to handle them.

In just two years, our conversations about AI will be radically different. We'll stop talking about the labels—GenAI, Agents, AI—and start focusing on what truly matters: measurable business transformation. Today's exciting GenAI technology will fade into the background, becoming a very important, but seamless, integrated part of the modern tech stack that powers our companies.

In this session we will explore how the convergence of AI technologies will fuel a new era of hyper-personalization and intelligent automation, delivering tangible value across every industry and department.

Join University of Auckland (UoA) and IBM to examine how you can move from experimentation to execution and ensure your GenAI programs deliver meaningful, measurable impact. We’ll guide you through a case study of UoA’s GenAI assistant, from PoC to full-scale production. It explores the foundations needed for GenAI success, applicable across any industry: an enterprise-ready technology platform, a mature AI operations lifecycle, and strong regulatory guardrails. Learn how these solutions safeguard a GenAI assistant serving over 50,000 users to deliver a more efficient business, at scale.

In this session, learn how Qlik and Village Roadshow are leveraging data authenticity and applied AI value to shape the future of Agentic AI. Discover real-world examples and a roadmap for implementing multi-agent architectures.

Generative AI is revolutionizing businesses, but the secret behind its success is your data – sensitive, unstructured, and exposed. Companies are racing to deploy AI yet often overlook the risks of data compromise, exfiltration and compliance. As organizations adopt new data tools, they must rethink their approach to data security or risk disastrous consequences.
If you’re struggling with balancing innovation and security, this session will give you the blueprint to securely scale data & AI applications.

With rates of fraud, scams and identity theft continuing to rise in Australia, there has never been a greater focus on keeping customers’ information safe. Commonwealth Bank is at the forefront of fraud prevention in Australia, implementing a suite of data and AI-driven innovations in partnership with SAS. This is all part of efforts to detect, respond and ultimately prevent the efforts of scammers across the world. During this session, you will hear how one of Australia's largest organisations is working tirelessly to protect its customers.

How does a lean data science team at Lottery Corporation manage to avoid the common pitfall of AI/ML being stuck in the lab, have 90% of their models in production and drive substantial business outcomes? Join Dr. Chris Hillman and Stewart Campbell to learn how the current programmes of models are built for success, driving risk reduction, anomaly detection and better customer retention at scale. Then, hear about their plans to use LLM, RAG and agentic AI to drive hyper personalisation, business productivity and better investment decisions.

In this session, we will explore cost transformative vendors such as DeepSeek and MistralAI’s impact on AI development, highlighting the potential to enhance enterprise innovation at a price/performance that is unprecedented. Data, analytics & AI leaders can bring their questions on how they can capitalize on new training and inferencing paradigms in AI, the future of AI model development and the impact of reasoning models on a more autonomous future in AI.

Moving AI projects from pilot to production requires substantial effort for most enterprises. AI Engineering provides the foundation for enterprise delivery of AI and generative AI solutions at scale unifying DataOps, MLOps and DevOps practices. This session will highlight AI engineering best practices across these dimensions covering people, processes and technology.

Analytics is experiencing another monumental change. Just as visual drag and drop BI tools and augmented insights led to changes in analytics delivery, we now experience conversational interfaces, automated workflows and AI agents that cause us to rethink how analytics will be done. Join this session to learn the new technologies that are making an impact and how this will affect plans for future investment in analytics tools, platforms and solutions.

This presentation of Gartner's top D&A predictions for 2024 guides data and analytics leaders as they plan for the impact of AI on all aspects of data and analytics, including leadership, governance, talent, market, and the need for AI-ready data and a FinAI competency for value realization.

D&A leaders and teams are at an AI-driven inflection point. They are crucial to enable business value through AI-readiness but must evolve their strategy and operating model to meet their organization’s AI ambitions. Reporting from the Gartner 2025 CDAO Agenda Survey, this session reveals actions successful D&A leaders have taken to deliver business outcomes from AI, data, and analytics, and what they need to do next year.

As privacy regulations tighten, organisations must go beyond check-the-box compliance to stay ahead. Join BigID and David Mesman for a practical discussion on how to build a future-proof, privacy-aware data strategy. Learn how to:

• Unify discovery, classification and governance across structured, unstructured and AI-generated data
• Automate privacy workflows and enforce policies in real time
• Strengthen customer trust through responsible data use
• Ensure compliance with current and future Australian privacy laws
• Align privacy, security and AI risk under one integrated framework