Agenda

Data is in the spotlight more than ever in 2024, bringing new opportunities as well as challenges.

The aspiration is to lead peers with superior digital products, unified customer data, customised experiences, accurate dashboards, an integrated data strategy, data culture, and mastery of emerging AI.
But with limited resources, how can we ensure Australian organisations don’t fall behind on critical goals?

This makes 2024 a pivotal year for Data leadership.
To optimise architecture, AI, access, and governance – we must ensure that data leadership and culture comes from the top down.
With less than 50% of Data leaders confident of executing on their data strategy, how can we increase their impact, value, and influence?

Join the community at ADAPT Data & AI Edge, bringing together our regional enterprise and government data and AI heroes to connect, learn and inspire in these challenging times.

ADAPT’s research and advisory team reveal the latest local fact-based insights, based upon over 1,000 detailed surveys of our region’s executive leaders. Showing the core findings distilled from your aggregated pre-event surveys and those of your executive CFO, Digital and CIO peers on their drivers, aims and opinions on data strategy. Also comparing the investment priorities, resource allocation and unique challenges of the Australian Chief Data Officer for you to benchmark and validate your thinking.

GenAI is a breakthrough, but often human misunderstanding means we feel there’s too much hype about its capability. Adoption of AI is tough, mainly because companies face big gaps:

• They don’t fully understand AI’s potential
• They struggle to execute AI projects well
• Their teams aren’t ready to use AI effectively
• They overestimate it’s potential and are disappointed

The question also emerges as to who should own AI capabilities and adoption? Should it go to the Head of Data or CIO, or elsewhere?

Reality is businesses who harness the AI capability for operational efficiency and new business models will excel in the next 5 years. So, one thing is for sure: the CEO and Board want to know how to get past the hurdles and truly benefit from AI, no matter what stage of the adoption cycle.

• What are the proven use cases to make operations more efficient?
• How can you make AI projects succeed and align with strategic business goals?
• How can you identify, understand, and adopt the right AI tools to propel growth?

With an impressive career and capabilities in quantitative finance, the impact of automation, and the future of work, Michael is focused on solving the problems of industry AI adoption.

Michael is an experienced business leader with a strong technical foundation in statistical AI systems. He began his career with a PhD in Finance from the London School of Economics, eventually moving into institutional asset management and quantitative research (Blackrock, Fidelity, AXA). Later, transitioning to the development of AI systems for institutional investment programmes, while continuing to teach Masters courses in quantitative techniques and analysis at LSE and Imperial College.

In this session, join Snowflake’s Principal Architect and Global Field CTO for AI/ML Chase Ginther for a deep dive into AI/ML on the world’s most capable Data Platform. Chase will discuss how organisations are driving data strategy as the foundation to succeeding in today’s rapidly evolving AI landscape. Specifically, Chase will highlight how Snowflake uses an innovative maturity model to collaborate with customers’ on addressing their maturity in their data foundation and AI use cases.

One such customer who has reaped the reward from Snowflakes enablement is the BuyNow PayLater payment solution “Scalapay”. Scalapay is a Unicorn transforming the way more than 5 million customers buy online and in-store, empowering 8,000+ merchants (online and in-store) to give their customers magical shopping experiences. Join Zachary Damcevski & Arlo Stewart, in a fireside chat outlining how Scalapay is pioneering groundbreaking solutions at the intersection of machine learning and data engineering to drive innovation and create value for our customers.

2024 is a watershed year for AI, as businesses shift from exploring AI’s potential to implementing these technologies at scale. To leverage the significant benefits of AI, companies must make strategic choices around AI’s impact on talent, operating models, data infrastructure, use case delivery, change management, and regulatory compliance.

Richard explores this crucial transition, outlining how companies can move from experimentation phase to full-scale production.

Importantly, beyond optimising productivity and CX, organisations are beginning to use AI to reinvent their business models and spawn new ventures. This approach signals a deeper recognition of AI’s transformative power in creating competitive advantage and driving business growth.

In his presentation, Richard will cover:

– The transition of AI projects from experimentation to scalable solutions in 2024.

– Key considerations for businesses scaling AI, such as talent, technology, regulatory engagement, and use case execution.

– The role of AI in pioneering business model innovations and new enterprises.

Leveraging his deep expertise in analytics and AI, Richard offers a roadmap for businesses to navigate the AI adoption landscape, highlighting proven ways to align AI initiatives with overarching business objectives that deliver sustained success.

Discussing the topical trends in data and AI as we navigate this inflection point.  Covering the generative AI opportunity, the Databricks vision and showing how your company can democratise data to take advantage of AI and benefit from large language models (LLMs), while maintaining data privacy and data quality

Covering:

• Today’s GenAI opportunity
• Real use cases
• Current Inhibitors
• Paths to success

According to a recent report, 83% of tech leaders see AI as becoming mandatory, and every company’s AI strategy will become a key differentiating factor. So, what are the criteria that make companies succeed and what makes them fail? Why will some projects be market differentiators while others will lead to high costs, low user satisfaction and missed business goals?

Alois was a key driver behind the development of Dynatrace’s Hypermodal AI which revolutionises the observability industry. He will walk through the strategic decisions that led to Dynatrace’s AI strategy. Then he will deep dive into why choosing the right AI techniques was not only crucial for technical but also business success. Alois will share how a business-first and innovation-centric approach helped to transform an entire industry.

The talk will cover:

• How to start to define an AI strategy and business case
• How to measure the success of an AI project and steer it in the right direction
• Why the AI architecture matters and what business leaders need to know about AI (without getting too technical)
• How to develop sustainable AI products in a fast moving market.

Alois also leads Dynatrace’s strategic open source initiatives for projects, co-chair and founding member of CNCF TAG App Delivery, as well as developing industry wide standards, most recently co-founding the W3C distributed tracing working group.