Conference Day Two: Thursday 11th March, 2021

Many enterprises are building out Centres of Excellence as part of their digital capability uplift in new technologies. They are experimenting with more intelligent automation to introduce business efficiencies, uplift the employee and customer experience as well as drive further insights into the business. In the knowledge that implementation of COEs needing to be carefully planned in order for new initiatives to be successful, questions remain around the best approach to aligning all aspects of the business for this.

•        Creating Centres of Excellence with the right COE model according to business need

•        The challenges of aligning people, capability, processes, technology and systems

•        Starting off – Tech and business Diagnosis, Re-engineering for the fastest ROI and long term strategic intelligent automation

•        Ensuring an end to end journey through the implementation of integrated technology tool sets and platforms

•        Internal structural and cultural backing to attempt to build intelligent automation into your organisation

Scott Delaney

Head of Innovation & Insight
MyState Bank

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Kelly Smith

General Manager, Enterprise Portfolio, Delivery & Intelligent Automation
AIA Australia & NZ

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Izak Van Niekerk

Manager, Business Transformation Architecture & RPA Centre of Excellence Lead
University of Auckland

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Transport for NSW are undergoing huge digital advancement to their systems, introducing real-time continuous signalling and decision support as part of intelligence initiatives. This session will see Pascal outline the data strategy built to support these advancements as well as the changes internally which must be introduced to combat change aversion.

·        Digital advancement to support Transport for NSW’s future vision

-         Next generation Sydney systems for real-time and continuous signalling

-         Application of machine learning for proactive decision support in an intelligent congestion management system

·        Defining a fit for purpose data strategy capable of supporting digital transformation in line with business need

-         Approaches to data ingestion, storage, visualization, BI and analytics

-         Negotiating touch and immigration points across multiple systems

·        Understanding cultural change needed to combat change aversion: value demonstration & clarity on future vision

Pascal Labouze

Executive Director of Operational Systems
Transport for NSW

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Many argue that a business strategy should be innately digital and support the overarching goals of the business. However, as many enterprises are starting from a legacy environment, they must now consider how to facilitate this change. People and culture determine the success of much transformation work and when it comes to digital disruption and innovation, a significant amount of reluctance is often palpable amongst internal teams. This panel discussion will explore steps to embedding digital as norm and approaching change management to ensure disruption is viewed as ‘innovation’ rather than ‘obsolescence’.

·        Challenges with rapid change, removing potential barriers and embedding continuous improvement practices

·        Upskilling and permeating a culture of learning agility and outcome focus

·        What does sustainable change management look like?

·        Confronting risk aversion to drive AI beyond low level complexity applications

·        Digital workforce – preparing the organization for transformation and shaping the future of work

Stuart Robertson

Head of IT Business Partnering Customer & Digital
Toll Group

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Catherine Payne

Executive Director of Digital & Customer Communications
Department of Environment, Land, Water and Planning

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Dan Bridgman

Senior Data Scientist
86 400

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The Institute for Applied Artificial Intelligence at Deakin University is a world leader in IA exploration and innovation. Their team of highly skilled data scientists and engineers form part of the research of 1st generation development of AI projects which demonstrate what is possible in the AI space. In this session, they will share their ground breaking work, giving you an insight into what is possible in the AI world and what the critical steps to reaching true AI capability are.

·        Case studies of artificial intelligence projects

-         AI in emergency surgery

-         Humanoid simulation for training of dementia

·        Simulation systems in defense

·        What are the 5 most critical foundations needed for a robust AI strategy?

·        The future for the digital space: AR/VR/Quantum Computing/Block Chain

Rajesh Vasa

Head of Translational Research & Development
Deakin University

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The idea that artificial intelligence would ultimately succeed was long thought of as science fiction. However, thanks to recent breakthroughs, many AI milestones, which experts viewed as decades away merely five years ago, have now been reached. This excitement has seen many companies invest in AI initiatives without the proper infrastructure in place. For this reason, multiple initiatives have failed and a hesitancy around such investment has emerged.

What’s more, CSIRO’s Data61 recently completed their national consultation for an Australian Ethics Framework for artificial intelligence, establishing industry feedback for the proposed framework. This highlighted the growing need for consensus around ethical use of AI and its governance. However, what does practical application of this framework look like? This panel will break down realistic expectations around AI as well as its ethical usage.

·        Is AI a fallacy? What we have been sold and what is the realistic capability?

·        Setting realistic expectations when building your data and digital strategy

·        What does ethical use of AI mean?: Key takeaways from the framework for AI development

·        How can regulators and organisations increase collaboration to create clear structures for AI accountability?

Scott Wall

CIO
BankVic

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Agustinus Nalwan

Head of AI and Machine Learning
Carsales

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Sandeep Reddy

Associate Professor, AI in Healthcare
Deakin University

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