What’s driving investment in generative AI?

For financial advisers and professional investors only – not for distribution to retail investors.

09 August 2024

Rapid development in generative AI technology could transform the global economy.

Key points

  • Advances in generative AI (GenAI) are capturing investor imagination
  • New technologies have the potential to transform whole sectors
  • Global spending on AI is estimated to reach $US300b annually by 20261

What’s driving investment in generative artificial intelligence?

AI has long been part of our everyday lives – Siri and Alexa voice assistants use AI to understand what you are saying, your mobile phone uses AI when you take a photo, and Netflix and Amazon use AI to recommend you shows to watch and products to buy. These are examples of discriminative AI, which analyses patterns to make predictions.

AI-based systems have long played an important role in many industrial processes like drug discovery, disease detection, logistics, and finance.  But it is recent advances in AI technology that are capturing the imagination of investors.

Fundamentally, it is due to a new and distinct category of AI systems which can create text, computer code, images, and videos on demand.

Termed ‘generative AI’ or ‘GenAI’, the new technology marks a pivotal evolution that is already unlocking new ways to work across the world, from rapidly creating emails, summarising documents, researching and answering questions, and coding software.

 

 

What is generative AI?

At its core, generative AI is a type of artificial intelligence that can generate new content like a human.

The models that underpin this technology are effectively an enormous amount of data processed through neural networks that attempt to mimic the construct of a human brain.

These neural networks are made up of nodes (like our neurons) organised in layers and are connected by billions of parameters (like our synapses) that have weights which are optimised through training.

GenAI models can be trained on various forms of data including text, images, software code, sound, and video depending on the desired specialisation. Once created, a model is then able to utilise probabilities to predict each next part of a response to generate a unique output to a given prompt.

Primary factors that influence the capabilities of a model include the scale and quality of data available for training, employee talent, accessible computing power, and financial resources.

This technology is not new. However, the development of transformer architecture, improvements in training methods, GPU (graphics processing unit) advancements, and the availability of big data have all recently combined to enable the creation of far more powerful models.

Businesses are already finding new ways to use GenAI tools to automate routine tasks, research and explain complex information, transcribe and summarise meetings, capture action items, generate new ideas, and to design.

Automating work tasks with GenAI is predicted to result in a measurable boost to global GDP and faster labour productivity growth, with McKinsey estimating a potential saving of $US2.6-4.4 trillion from productivity gains alone2.

Ultimately, that requires widespread adoption of GenAI systems and continued development of the technology.

That is what is driving the investment interest: developing and running GenAI requires vast amounts of resources from investment to electricity and infrastructure – and the race is on to be the leader in developing the next generation of AI systems.

As rapid development continues, we believe the GenAI revolution could be as big a transformation for the global economy as the advent of mobile phones, the internet – and even the industrial revolution. 


1 IDC, 2023

2 McKinsey, “The economic potential of generative AI: The next productivity frontier.” 2023

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