By Dora Tse, CEO of Explora.
The AI boom is currently the major tech transformation hype that every investor, industry, and person is talking about. According to analysts at PricewaterhouseCoopers, AI could add up to $15.7 trillion USD to the global GDP by 2030. We know that Microsoft invests heavily in OpenAI and Github, which develop many solutions and initiatives that can be used for developing AI. Furthermore, we also know that Google, AWS, and Meta are playing major roles in their tooling and R&D labs to bring basic innovation in AI algorithms to market, including their powered search features and AI functions to help accelerate the transformation and bring value to the industry in many ways.
There is no doubt that companies focusing on AI and machine learning have strong growth potential, which would develop many more projects, investments, and job opportunities in that area. However, most importantly, Open AI, ChatGPT, and many AI innovations indeed need a large volume of quality data that the AI explosion will heavily rely on. Explora sees the need for enterprises to integrate their data into a centralized data warehouse to develop and improve their AI models. In our point of view as data experts, we cannot skip steps to jump straight to machine learning and any kind of AI innovation. We have to start from data integration, follow the structure and best practices by centralizing their data in a quality structure so that we can then get data ready for the next milestones, such as AI innovation, machine learning, and predictive analytics. We know this would take years to make enterprise data ready for the next stage. Thus, data platform vendors, data solution vendors, and service vendors continue to work closely hand in hand to co-create and co-respond to the business demand for it.