The past decade has witnessed a remarkable transformation in technology, particularly in the realm of AI. Think of AI like a brain where technology mimics how a human would reason, learn, act, respond, and behave. Machine learning is a set of algorithms that allows the brain to learn new things from data, while generative AI, like ChatGPT, creates content – including text, images, and audio – based on the data it trains on. In this snapshot, we share takeaways from the AICM National Conference keynote, where Equifax Executive General Manager Data & Analytics, Kari Mastropasqua, shares her perspectives about the role of AI in business.


We're living through a period of major AI advances

AI adoption is on an unprecedented rise, with global spending on AI forecast to reach US$153b in 2023 and estimates that automation, including AI, could add up to $4 trillion to the Australian economy by the early 2030s. The widespread use of generative AI tools like ChatGPT, which has over one billion users, showcases the increasing accessibility of AI to those with limited tech ability. 

Data is becoming more democratised and accessible

The Internet of Things (IoT) is expanding, with loT devices set to double by 2030. This growth encourages hyperpersonalisation and generates a wealth of new data sources, with 90% of the world's data generated in the last two years. Approximately 80% of this data is unstructured, encompassing video, images, audio files, emails and social media. AI tools are leading the way in transforming unstructured data into actionable formats, enabling process automation at scale.

New business models are gaining traction

Consumer expectations for services are continually maturing, driven by new models like the metaverse and decentralised finance systems. Seamless digital experiences are here to stay, but the nature of customer journeys will continue to evolve. Technology doesn't stand still, so keeping abreast of these changing trends and consumer preferences will separate the leaders from the laggards.

Responsible AI is a key challenge

Trust, risk and security management (TRiSM) in AI applications are critical to its successful implementation.. AI's 'black box' nature, or lack of transparency, can result in unintended consequences like bias, inaccuracy and lack of explainability. At Equifax, we've developed a suite of Explainable AI (ExAI) techniques known as NeuroDecision® Technology, enabling machine learning benefits with transparent decision-making. This patented approach, unique in the Australian market, has been used for our award-winning consumer risk score, Equifax One Score.

AI is revolutionising credit scores

Credit scoring is an area where the integration of AI has been particularly beneficial. The combination of AI, traditional and non traditional data enables improved accuracy in decision making. Through ExAI we continue to make breakthroughs in both our consumer and commercial credit scores. 

Expect faster and more accurate decisions

Good decisions are made by weighing up multiple factors based on a broad range of data. Combining AI and machine learning can help businesses make data-driven decisions at scale that are fast, accurate and consistent. 

Customer service will enter a new era

New generative AI tools have the power to move customer service well beyond today’s capabilities, enabling instant and personalised responses to customers who expect the right information at the right time. Conversational AI will continue democratising data and enabling frictionless information delivery to help frontline teams enhance customer experience.

Bring the promise of AI to life with diversity of thought

  • AI implementation is a whole-of-business activity that benefits from a range of mindsets and perspectives. Here are some ways you can incorporate a collaborative approach into your AI journey:
  • Create cross functional teams to consider the opportunities for your business 
  • Take inspiration and learn from the conversations and work being done on AI globally
  • Do the research into AI regulation and develop a framework for what responsible AI looks like in your business
  • Experiment with new technology, take a test and learn an approach to prove out value and build up understanding in non tech areas.

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