Cloud & Infrastructure Sydney schedule

During this 5-minute networking session, the aim of the game is to go and meet three people you don't already know. Use the questions on the screen to guide your conversation. Have fun!  

Learn how the most successful technology leaders are redefining their role, influence, and value proposition as AI becomes central to competitive strategy.

• From technology steward to business strategist: Transition from managing IT services to architecting competitive advantage through strategic AI infrastructure
• New leadership competencies: Develop skills in AI business cases, stakeholder alignment, and risk assessment beyond technical expertise
• Organisational influence and governance: Establish new reporting relationships, decision authority, and board-level communication positioning technology leaders as core business strategists

Gain insight into holistic approaches to transform IT infrastructure to enable strategic agility and sustainable business growth.

• Engineering a balanced portfolio: Developing a diversified and future-proof IT portfolio by strategically integrating on-premise, public, and private cloud assets
• Operationalising intelligence with AIOps: Leveraging AI and machine learning to automate infrastructure management, predict system failures, and continuously optimise performance across the enterprise
• Extending infrastructure to the edge: Implementing robust edge infrastructure strategies to support low-latency applications, real-time data processing, and enhanced customer experiences

Architect foundations that support both current operations and future innovations without requiring wholesale replacement.

• AI-native architecture design: Accommodate AI workload demands through specialised hardware, distributed processing, and elastic scaling
• Emerging technology talent strategies: Evolve organisational capabilities blending traditional expertise with AI operations and cloud-native architectures
• Adaptive governance for innovation: Balance innovation enablement with operational stability, enabling rapid technology evaluation and integration

Speakers:

Suneetha Bodduluri, Chief Technology Officer, Service NSW

William Cross, Head of Technology, ColCap Financial Group

Moderator:

Kate Romanova, former Group Head of Technology, Strategy and Innovation, ex-Qantas

Defining, implementing and scaling AI strategy that is integrated with your core objectives, creating a foundation for sustained competitive advantage.

• The icare context: our view and usage of AI
• Translating AI potential to tangible outcomes: Define a value-driven roadmap that aligns AI investments with strategic goals
• Governance and the human element of AI: Implement governance frameworks, change management, and talent models to navigate AI's complexity
• Building the AI-ready organisation: Create foundational infrastructure and capabilities to support organisation-wide AI adoption

Discover practical, data-driven approaches to optimise infrastructure, reduce costs, and strengthen business resilience.

• Balancing strategic investments: Allocating capital across a mix of on-premise, public, and private cloud environments by analysing total cost of ownership
• Architecting for resilience: Designing hybrid infrastructures that balance cloud agility with the control and performance of dedicated infrastructure
• Driving a value-based FinOps culture: Operationalising financial discipline and continuous optimisation through advanced automation and governance across the IT portfolio 

A look into where the true, long-term business value lies.

• Is a complex cloud landscape required for faster innovation, or does it ultimately create operational friction, jeopardising control and efficiency?
• Does a best-of-breed approach deliver superior resilience, or does standardization offer a more secure, manageable foundation?
• What is the greater strategic risk: vendor lock-in or the hidden cost of juggling a diverse cloud ecosystem? 

Hear how organisations are designing strategic infrastructure to optimise AI capabilities across various deployment models.

• AI-first strategy: Design infrastructure and services optimised for AI workloads, ensuring scalability and flexibility
• Enterprise AI enablement: Create platforms and capabilities empowering business units to leverage AI effectively
• Digital infrastructure strategy: Align technology architecture with business goals, future-proofing infrastructure for market demands

Discover how to build infrastructure foundations for competitive advantage through strategic deployment, not technology ideology.

• Strategic deployment flexibility: Evaluate AI workload placement based on data sensitivity, performance, regulations, and costs
• Performance and cost optimisation: Balance predictable on-premise costs with scalable cloud services for different AI cases
• Integration and customisation strategies: Design infrastructure enabling deep integration and specialised development while leveraging cloud innovations 

Dive into architecture modernisation, scalability planning, and integration strategies for large-scale AI workloads.

• Architecture modernisation: Update cloud infrastructure supporting AI workloads with advanced technologies for performance and agility
• Scalability planning: Design cloud systems seamlessly expanding for growing AI demand while maintaining cost efficiency
• Data, AI, and automation integration: Leverage integrated platforms connecting data pipelines, AI workflows, and operations for faster innovation

Design intelligent cloud infrastructure to federate ecosystems, accelerate innovation, and enable strategic agility.

• Federating a multi-cloud ecosystem: Create a cohesive environment enabling interoperability and optimised workload placement
• Accelerating innovation: Build reusable platforms that empower safe, scalable developer and business innovation
• Enabling strategic agility: Embed automation and guardrails to balance freedom, risk, and ROI 

Transform infrastructure into a business value driver by aligning investments to growth and innovation outcomes.

• Strategic infrastructure financial governance: Implement predictive cost models and metrics to guide growth-focused investments
• Unified hybrid portfolio visibility: Gain cost transparency across cloud, private infrastructure, SaaS, and AI workloads
• Shared financial responsibility and accountability: Establish cost allocation and cross-functional accountability to drive smarter adoption

Speaker:

Arvind Shastry, FinOps Manager, Transport for NSW

Moderator:

Jayden Le, Global Head of IT and Security, Zoomo  

Align infrastructure with regulations, embed risk management, and build governance for control and accountability

• Regulatory alignment: Understand and operationalise evolving regulations to ensure compliance and reduce exposure
• Risk mitigation: Identify and manage operational, security, and financial risks across hybrid and legacy systems
• Compliance strategy: Build governance frameworks integrating compliance into daily operations for security and accountability 

Cloud FinOps is often misunderstood as a purely cost-cutting/controlling exercise—but that’s far from the truth. In this session, we’ll debunk common myths and explore how FinOps can become a strategic enabler for innovation and growth. You’ll learn how to move beyond reactive cost management toward proactive financial governance that drives measurable business outcomes.

• Myth-busting: Why FinOps isn’t just about reducing spend—and how focusing solely on cost can limit scalability and innovation.
• Strategic alignment: Position FinOps as a value driver by linking cloud investments to organizational goals and growth strategies.
• Governance frameworks: Implement guardrails and accountability models that balance agility with financial discipline.
• Financial transparency: Achieve unified visibility across multi-cloud, SaaS, and AI workloads to eliminate waste and optimize ROI.
• Shared responsibility: Foster cross-functional collaboration between engineering, finance, and operations for sustainable success.

Harness AI's transformative potential while maintaining the reliability and security that business demands.

• Reactive to predictive transformation: Anticipate and prevent issues, shifting from firefighting to strategic value creation
• Collaborative human-AI workforce strategy: Reimagine roles focusing talent on strategic work while AI handles routine tasks
• AI-driven governance and risk management: Build adaptive resilience ensuring automated decisions align with business requirements 

Drive adoption and business value by embedding change management across AI-enabled cloud transformation.

• Cross-functional alignment: Align business units, IT teams, and decision-makers around shared AI and cloud objectives.
• Strategic stakeholder engagement: Engage stakeholders early and continuously to champion AI-driven cloud capabilities.
• Bridging technology and strategy: Establish governance, communication, and metrics linking AI initiatives to measurable business impact

Speakers:

Tom Gao, Chief Technology and Digital Services Officer, City of Sydney

Eriza San Miguel, Global Technology Portfolio Director, BlueScope

Moderator:

Aman Dayal, GM - Data, AI, Architecture, Coates

Evolve operating models, processes, and talent to accelerate digital business transformation.

• Reinventing talent and processes: Reinvent teams for rapid delivery, continuous improvement, and modern tech talent
• Redefining IT governance: Redefine governance to enable speed, empowerment, and agile experimentation
• Scaling innovation: Create a culture that rewards experimentation and scales new applications quickly

Speakers

Stan Belikoff, Chief Technology Officer, C2O Group

Prakhar Rawat, Chief Technology Officer, Tokio Marine Management Australasia

Chaitanya Kuber, Chief Technology Officer, Airtasker

Speakers:

Stevie-Ann Dovico, Chief Information Officer, Beyond Bank Australia  

In the highly competitive age of digital transformation financial service organizations are facing accelerated urgency to improve their customer and employee experience while simultaneously reducing operating costs, and managing risk and compliance.

To meet these competing demands on their business, these organizations are racing to deploy deep learning to achieve a new competitive edge by optimizing their back office operations with intelligent document processing, personalizing their customer experience with cutting edge NLP models, and reducing fraud and risk using state-of-the-art deep learning.

AI is here and delivering new capabilities to help businesses solve large and complicated challenges. Join Bob Gaines to learn what that means for your business and how deep learning is helping organizations:

• Achieve higher compliance, faster and with lower costs • Dramatically improve Customer Experience • Reduce time to value from years to weeks

Sergio Rego is a customer engineer at SambaNova Systems where he helps clients deploy purpose-built, deep learning solutions in weeks rather than years. Sergio started his career in financial services, where he worked in strategy; active and index management; and product design and management. Sergio also served as a senior data scientist and team manager for a system integrator where he helped federal government agencies deploy ML and AI solutions.

In the highly competitive age of digital transformation financial service organizations are facing accelerated urgency to improve their customer and employee experience while simultaneously reducing operating costs, and managing risk and compliance.

To meet these competing demands on their business, these organizations are racing to deploy deep learning to achieve a new competitive edge by optimizing their back office operations with intelligent document processing, personalizing their customer experience with cutting edge NLP models, and reducing fraud and risk using state-of-the-art deep learning.

AI is here and delivering new capabilities to help businesses solve large and complicated challenges. Join Bob Gaines to learn what that means for your business and how deep learning is helping organizations:

• Achieve higher compliance, faster and with lower costs • Dramatically improve Customer Experience • Reduce time to value from years to weeks

Sergio Rego is a customer engineer at SambaNova Systems where he helps clients deploy purpose-built, deep learning solutions in weeks rather than years. Sergio started his career in financial services, where he worked in strategy; active and index management; and product design and management. Sergio also served as a senior data scientist and team manager for a system integrator where he helped federal government agencies deploy ML and AI solutions.