The AI evolution: Where are we heading?

2023 could be billed as the year that AI went mainstream. Over the past few years, AI has become increasingly prevalent in everyday life, used in voice assistants such as Amazon’s Alexa and Apple’s Siri; customer service chatbots; personalised online recommendations for shopping or viewing choices, and much more. However, this year, there has been a dramatic surge in interest in AI and its capabilities thanks largely to ChatGPT.

OpenAI’s large-language model (LLM) chatbot, ChatGPT, was made freely available in November 2022 and became one of the fastest-growing applications ever, reaching 100 million users in just two months¹. LLMs are advanced AI programmes that are trained on large amounts of text data to understand human language and produce meaningful, natural responses. The technology is designed to make communication between humans and computers more like human-to-human conversations.

ChatGPT sparked a wave of excitement around AI because it enabled anyone with access to the internet to experience generative AI’s enormous potential. In its response to simple prompts and questions, it has been a powerful demonstration of how generative AI can enable computers to ‘think more like humans’ and create original text, images, video, music and code.

“Generative AI can enable computers to ‘think more like humans’ and create original text, images, video, music and code.”
 

Tech companies have been working on AI projects for years, but OpenAI opened the floodgates with the release of ChatGPT. It has been swiftly followed by a host of other open-source generative AI tools, including Google’s Bard, Meta’s Llama and Baidu’s Ernie Bot, as large tech companies seek to capture a core share of the market.

The hunger for data

LLMs rely on vast amounts of data to be able to produce new content, which is leading to growing competition for datasets. “Data has already been hailed as the new oil,” notes Jasmeet Chadha, Global Technology Analyst. “Generative AI might as well be the internal combustion engine of our age that helps unleash its value.”

Businesses that own proprietary datasets will become increasingly valuable, especially since those datasets are required to create the generative models. For example, Adobe, a creative software company, has used its database of hundreds of millions of photos to create Firefly, a product that generates AI-powered content with a simple prompt. Sources of news and images are also being approached by AI companies to incorporate datasets into their models.

In the future, we are likely to see a growing number of businesses training models on their own proprietary data to create bespoke AI applications. Given that many firms’ datasets are located across different systems and may not necessarily be in the best format, this could require the help of IT services companies who can advise firms how best to implement AI effectively, and achieve efficiencies in their operations while ensuring data security.

A disruptive technology

We believe AI is now entering the next phase of its evolution driven by generative AI and LLMs. In our view, the capabilities and applications that AI now offers has huge potential to transform businesses, disrupt entire industries and even alter human lives.

Using computers to enhance human decision-making and perform repetitive tasks could help businesses improve efficiency and productivity. Indeed, research by consultants McKinsey estimates productivity improvements from generative AI and automation could add between US$2.6 trillion – US$4.4 trillion annually to the global economy².

Read the full article in the inaugural edition of Ampersand, our bi-annual thought leadership magazine.

¹ Reuters, “Chat GPT sets record for fastest-growing user base – analyst note”, Reuters.com, February 2023. 
² McKinsey, “The economic potential of generative AI: The next productivity frontier”, mckinsey.com, June 2023.

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