Australia’s AI workforce revolution: automation paves the way for a four-day work week.

In Short

UiPath’s report highlights the rapid shift towards “agentic automation,” where AI makes autonomous decisions, encouraging businesses to reassess roles and harness automation for productivity. This evolution may enable a four-day work week and necessitates the retraining of staff while ensuring regulations are in place for trust and compliance with AI integration.

The trend towards work reallocation is rapidly advancing, with UiPath’s new report identifying significant shifts in AI and automation.

Key insights from the report suggest a move towards “agentic automation,” where AI begins to make autonomous decisions. Yelena Galstian, Head of Solutions and Customer Advisory at UiPath shares her key insights.

Organisations are encouraged to reassess existing roles and identify areas where automation can enhance productivity.

A critical aspect will be the orchestration of collaboration between human employees, AI agents, and software robots to ensure effective teamwork.

Looking ahead, the motto for businesses is to “redesign and reassign” processes while considering how AI can handle repetitive tasks, allowing human employees to focus on more complex responsibilities.

As organisations embrace these changes, we could see a potential transition to a four-day work week, made feasible through increased efficiency and productivity from AI.

For further insights into the research and methodologies for implementing AI in business, interested parties can connect with the UiPath team through their website.

The rise of AI is pushing data centres to their limits, with increasing demands for high-resolution telemetry and greater power capacity. As AI applications grow more complex, managing these challenges efficiently has become a critical focus for industry leaders. The quest for smarter solutions is reshaping the infrastructure landscape. Luke Dalske, COO of Radix IoT, joins the program to discuss.

AI is transforming supply chains: enhancing efficiency, demand forecasting, delivery optimisation through advanced technologies.

Supply chain issues continue to challenge industries worldwide.

AI is increasingly seen as a solution to enhance efficiency and resilience within this sector.

To understand its impact, Jyot Singh, CEO of RTS Labs, joined to share his insights.

By utilising historical data, algorithms can predict future demand, facilitating better inventory management.

Additionally, advances in generative AI further enhance these forecasts by incorporating sentiment analysis and other factors.

AI also optimises delivery routes by analysing real-time data on traffic and weather conditions, thus reducing costs.

Companies, such as UPS, utilise technologies to streamline last-mile delivery, which is the most expensive portion of the supply chain.

AI’s role extends to improving vendor management and procurement efficiency through smart contracts and data-driven decision-making.

This helps businesses assess vendor reliability and make informed choices about allocating resources effectively.

Moreover, the digital twin technology allows businesses to simulate their supply chains virtually, testing various scenarios to identify potential disruptions.

American technological research and consulting firm Gartner predicts that by 2026, 60% of global supply chains will adopt digital twin applications, enhancing their ability to manage complex logistics.