^{Originally published in the AFR on 11 March 2024. See the original article.}

Taylor Swift, US President Joe Biden and British cook Nigella Lawson have all been the target of so-called deepfake videos posted online. Created by generative artificial intelligence, the imagery is so lifelike that only a computer can detect whether they are real or not.

Generative AI was a term generally relegated to coders in specialised technology firms until a little over a year ago when research company Open AI, in partnership with Microsoft, released ChatGPT to the public. Almost instantly, it became a social media sensation, breaking out of its niche tech circles.

Then came the release of Nvidia’s semiconductor chips that process vast volumes of data and computations at high speed, accelerating generative AI’s broader enterprise adoption. Since then, references to generative AI in company transcripts across industries around the world have exploded.

Recognised as one of the fastest and most impactful innovations of the so-called fourth industrial revolution, generative AI was prominently featured at the World Economic Forum in Davos. Consequently, developed countries are scrambling to establish regulatory frameworks to govern its usage.

Companies have been incorporating various forms of AI into their operations for years, such as text-based chatbots replacing human call centres. But unlike traditional AI, which is based on text and often used for classifying or grouping data, generative AI produces images, music, code and text. It goes beyond processing words; it also understands context, nuance and even humour.

Just as billionaire Bill Gates in the early 1990s when computers started to take off envisaged a future of “information at your fingertips”, Microsoft chief executive Satya Nadella refers to generative AI as having “a world of expertise at your fingertips”.

It is early days as to how it will unfold for each industry, but it is clear that generative AI will have a meaningful impact. The International Monetary Fund expects it to impact 40 per cent of global employment, including high-skilled jobs.

Company examples

The first and most direct beneficiaries have been chip maker Nvidia and predominantly US-based providers of infrastructure for generative AI. However, over the longer term, companies in many other industries can benefit from embracing the technology.

Healthcare company Sanofi advocates using AI as a way of driving better data-driven decision-making regarding clinical trial execution, as well as accelerating drug molecule design and optimisation. Similarly, Walmart recognises generative AI as a step change in search technology, integrating the technology it into its app and website to produce more intuitive and personalised search results.

Colgate Palmolive has built tools to help predict consumer behaviour and trends to aid in new product innovation. Gaming company Light and Wonder uses generative AI as coding assistants to get more productivity for new features and products. The list of potential uses is long and vast.

But there are also ethical implications of generative AI to contemplate.

Generative AI is clearly a powerful tool with many benefits, but an important challenge that the world will have to grapple with is not only the best way to incorporate it into workflows but ensuring that its use is ethical.

Training generative AI models often requires large amounts of personal data, which can create issues around privacy if the data is leaked or misused, such as the creation of deepfakes that can manipulate the public and damage reputations.

Misinformation and disinformation is ranked as the No.1 threat that the world faces in the next two years, according to the World Economic Forum’s Global Risks Report 2024. The European Union and the US are drafting regulations around its use.

Ultimately, generative AI should improve efficiency, make jobs more interesting by automating repetitive tasks, boost creativity and accelerate innovation. However, it is still in the very early days of adoption and just like other disruptive technologies there tends to be big initial hype surrounding its potential.

Nvidia’s share price has skyrocketed and closer to home, the share prices of ASX-listed companies involved in data centres such as Next DC and Goodman Group have benefited because generative AI also drives an enormous step change in data requirements.

While there are fewer ASX companies that are directly exposed, the landscape will evolve with potential to provide big opportunities over time for companies that are nimble and can incorporate the technology effectively to optimise productivity and innovation.