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APAC to gain $4.5tn in economic value from GenAI

The region’s largest economies could see a 0.7 percentage point increase in their annual GDP by leveraging generative AI responsibly at scale with a focus on people

Generative artificial intelligence (GenAI) could deliver $4.5tn more in economic value in Asia-Pacific’s largest economies – equivalent to a 0.7 percentage point increase in their annual GDP growth – over the next 15 years, research by Accenture has found.

As part of the research, the consulting firm performed economic modelling for Australia, China, India and Japan, which involved assessing the potential for job automation with human verification; identifying GenAI adoption scenarios; and modelling GDP growth, among other factors.

It also conducted a survey in the four countries, as well as in Singapore, a beacon economy, stressing the importance of leveraging GenAI responsibly at scale and focusing on people to realise the economic potential of the technology.

Citing the findings from its research, Accenture noted that 33% of working hours would either be automated or augmented by GenAI, leading to a productivity boost. Working hours will be most impacted in Australia (45%) and Japan (44%), followed by China (33%).

In Australia, this could lead to a 0.75 percentage point increase in GDP growth per year and an additional $269bn in economic value by 2038.

Nearly all (96%) business leaders in the study acknowledged the significant impact of GenAI, while 91% of workers were keen to acquire new skills to work with it. However, only 4% of business leaders have rolled out GenAI training at scale. 

Similarly, 89% of businesses planned to increase their spending on GenAI this year, but only 35% prioritised investments in workforce development.

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The most impacted industries included capital markets where GenAI would transform nearly three-quarters of working hours (71%), as well as software and platforms, where two-thirds (66%) of working hours would be automated or augmented. This was followed by banking (64%), insurance (62%) and retail (49%).

Leo Framil, CEO of growth markets at Accenture, urged leaders to see GenAI as a “value creation opportunity” for businesses, people and society, and more than just a tool for redesigning processes and driving cost efficiencies.

“The scaled implementation of GenAI could reinvent almost all functions across industries,” he said. “The key to unlocking its real value lies in skilling. For businesses to maximise GenAI benefits and drive growth, leaders must extend their focus beyond the immediate tasks and roles and embrace a long term, people-centric approach.”

Steps to take

To fully leverage the potential of GenAI, Accenture recommends that businesses take the following steps:

Lead and learn in new ways: To be effective and build trust in the GenAI-enabled future, leaders need to engage, lead differently and challenge old mindsets to learn new things. It is important that leaders immerse themselves in the technology, effectively changing how they learn by embedding learning into the flow of work.

Reinvent work: By rethinking entire workflows, leaders can gain a clear view of where GenAI can be most impactful, aligning it with business goals for better efficiency and innovation across the enterprise and collapsing silos in a lasting, meaningful way. From there, it’s possible to re-focus on how the work needs to change to better serve customers, support people and achieve business outcomes.

Reshape the workforce: The shift in how work is done demands a dynamic and adaptable workforce. Organisations need to prioritise continuous talent reinvention. As use of this technology grows, organisations should further leverage tools and technologies, such as skills mapping, that can help facilitate smoother transitions from declining to emerging roles. And as work and roles shift, increased capacity can free up time and talent for higher value activities.

Prepare workers: As organisations invest in helping workers acquire market-relevant technical skills and the capability to collaborate with machines, they will also need to focus on soft skills. A teach-to-learn model is emerging to equip workers to teach the machines. Along this journey, leaders also need to listen and involve their people at every step of the way to strengthen trust.

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