Industrial AI Program

What is Industrial AI?

At AIML, Industrial AI is the use of AI to improve efficiency or create value for industry. Examples of Industrial AI include chat bots, advanced analytics, management tools, supply chain management, and automation and robotics in manufacturing.

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AIML’s Industrial AI program 

Launched in 2024, AIML’s Industrial AI program supports the development of core capability in industrial AI, driving economic growth and job creation in South Australia (SA) and across the nation in a range of sectors. The primary focus of AIML’s Industrial AI program is to:

  • increase the development and adoption of AI to create jobs and boost productivity.
  • grow and attract world-class talent and expertise to SA.
  • harness AIML’s world-leading AI capabilities to solve national challenges and benefit all Australians.
  • ensure Industrial AI technologies are responsible, inclusive, and reflect Australian values.

The Industrial AI program will achieve this through the delivery of the following programs:

Program 1: Recruit leadership in industrial AI 

AIML will attract research leaders in industrial AI to Adelaide to contribute to the growth and development of students, early career researchers, and industry collaborations at AIML.

Program 2: Upskill for business growth and social mobility – building domestic talent for South Australia in Industrial AI 

AIML is offering competitive scholarships for high achieving domestic and international students. AIML will also provide scholarships that support students to complete honours or master’s by research degrees.

The current list of AIML Industrial AI scholarships include:

  • - supports two exceptional students engaging in advanced research in Artificial Intelligence and Machine Learning in an Honours program of study at the ³ÉÈË´óƬ. Applications open 9am, Monday 2 December 2024; close 5pm, Friday 28 February 2025.
  • - these full-time scholarships support students undertaking their PhDs in AI and machine learning.
  • - these scholarships support students undertaking their master’s degrees in AI and machine learning.
Industrial AI PhD Scholarship Key Points

Program 3: Supporting Government and Business to Adopt AI 

AIML will provide machine learning expertise for state government departments and South Australian small and medium enterprises (SMEs) to scope opportunities, as well as develop and adopt new machine learning tools. 

At the conclusion of the program in December 2028, AIML is confident that we will have contributed significantly to the advancement of Industrial AI in Australia and the global Industrial AI field as well. We look forward to working with our collaborators and stakeholders in this space and creating the frameworks for a practical and sustainable Industrial AI initiative that will provide value to all Australian businesses, no matter the industry.

Organisations are turning to digitalisation and Industrial AI to develop autonomous and semi-autonomous processes and tools that enable new levels of safety, sustainability, and profitability.  Some of the most difficult challenges for local industries include maximising throughput while minimising changeover costs and ensuring on-time delivery of products to customers. AI can help through its ability to consider a multitude of variables at once to identify the optimal solution.  

At AIML, Industrial AI is about pushing the frontiers of what can be done with AI and machine learning, by making new discoveries that will ultimately benefit industry. By working with local industries and using AI to help increase safety, enhance supply chain management, improve performance, and cut downtime, our goal is to help businesses reach the highest levels of operational efficiency.

The Industrial AI program is supported by the South Australian Government through the Department of State Development’s Research and Innovation Fund. 

Pivotal needs in Industrial AI 

According to a 2021 article in the MIT Technology Review, there are three pivotal needs driving capital-intensive industries to digitise and implement purpose-built AI systems: 1 

Generational shifts in the workforce are creating a loss of operational expertise. Veteran workers with years of institutional knowledge are retiring, replaced by younger workers taught on technologies and concepts that don’t match the reality of many organisations’ workflows and systems. This dilemma is fuelling the need for automated knowledge sharing and intelligence-rich applications that can close the skills gap. 

Industrial organisations are accumulating massive volumes of data but deriving business value from only a small slice of it. Organisations are switching their focus from mass data accumulation to strategic industrial data management, homing in on data integration, mobility, and accessibility—with the goal of using AI-enabled technologies to unlock value hidden in these unoptimised and underutilised sets of industrial data.

Adopting new technologies unlocks new business models that are integral to sustainability, market competitiveness, and new corporate strategies. The more that competitors digitally transform to reap these advantages, the more organisations that don’t transform will be left behind.

Some of the use cases for industrial AI include:

  • Self-aware, that can independently measure performance to generate alerts when degradation reaches a critical point or performance is reduced for any reason. 
  • Creating for regulatory compliance monitoring in banks and financial institutions.  
  • Robotics and that can replace human involvement, thereby increasing efficiency and boosting production while improving human safety.
  • Complex supply chain management that increases visibility into every step of the process, including tracking raw materials, inventory, warehouse management, logistics, and last-mile distribution.

Relevant AIML news pieces

For more information on AIML’s Industrial AI program please contact IndustrialAI@adelaide.edu.au.

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