In the early 2000s, the introduction of Amazon Web Services (AWS) marked a significant turning point for enterprise businesses, completely transforming their operations by providing instant access to scalable computing resources. Today, generative AI is poised to have a similarly significant impact, with projections indicating this technology will contribute between $2.6 and $4.4 trillion to the global economy each year.

According to Lee Chin Jian, Vice President at DAI Magister, generative AI’s influence is increasing because of its ability to handle large amounts of data, automate routine tasks, and predict outcomes reliably.

Jian said: “AI is transitioning from merely summarising information to synthesising insights from complex datasets, which involves far more than just organising information. This capability allows it to recognise patterns, trends, and hidden relationships that may elude human analysts due to data scale and complexity.

“By doing so, AI not only provides a comprehensive data perspective but also enables leaders to identify valuable insights and trends, thereby fostering growth and innovation. This transformative role of AI supports and enhances human intelligence and decision-making, rather than replacing it.

“The implications of AI’s enhancement of decision-making and creativity extend to complex areas like software development. AI can analyse expansive codebases, detecting potential bugs by recognising problematic code patterns.

“This shifts developers’ focus from monotonous tasks to more creative ones, like designing new features or enhancing user experiences. Furthermore, AI-assisted coding can lead to improved decision-making in code structuring, algorithm optimisation, and application performance.”

Jian also recognises how the deployment of generative AI will differ in the B2C and B2B spaces.

Jian commented: “In the consumer sphere, generative AI is predominantly used for personal and entertainment purposes, from AI-generated art or music to engagement with AI entities like ChatGPT. In these scenarios, the emphasis is often placed on the novelty and quantity of the output rather than its quality.

“In contrast, in a business context the key determinants are efficiency and quality. The aim is to leverage AI to make informed decisions and generate superior outcomes. For example, AI can transform software engineering across various stages of the development lifecycle, from designing, coding, and testing to maintaining software systems, making these businesses more efficient and competitive.”

Jian concluded: “Advances in AI technology over the next few years will pave the way for an abundance of diverse use cases. As these use cases proliferate and AI’s ability to amplify human decision-making becomes more apparent, we anticipate a significant upsurge in AI funding activity. This elevated level of funding will be multi-year and outperform the general tech funding market.”