However, there is no one-size-fits-all approach to using generative AI. The nascent nature of generative AI requires enterprises to train their AI models on massive volumes of diverse data before these models can perform tasks efficiently or provide actionable insights. In essence, these AI models must go to “school” before they can be put to work.
ChatGPT has put artificial intelligence at the forefront of public consciousness with its accessibility and relative ease of use. Once perceived to be accessible only to experts and large enterprises, it has democratised access to AI, making it available to consumers and smaller businesses.
As a result, businesses are looking to incorporate artificial intelligence (AI) technology across their organisations to benefit from increased productivity and efficiency. Super-app, Grab, for example, has augmented its search engine with AI to offer the closest matches and relevant suggestions to queries while taking into account local languages and nuances. The International Data Corp predicts that spending on AI in Asia-Pacific (excluding Japan) including software, services, and hardware for AI-centric systems, will grow to US$49.2 billion in 2026.
