In today's fast-paced innovation landscape, new technologies often promise to revolutionize our work, especially in data and analytics. Yet, these promises sometimes fall short in practical application. The concept of data democratisation, while theoretically sound, faces hurdles in implementation. It requires domain expertise and often encounters resistance due to the complexities of data handling.

The emergence of generative AI models like Large Language Models and Generative Adversarial Networks is shifting this paradigm. Tools such as Bard and Dall-E are leading the charge in AI democratisation, making data more accessible and actionable. The success of OpenAI's ChatGPT-3 highlights this trend, showcasing how non-technical users can harness AI for diverse applications, from creative endeavors to business planning.

This shift from data to AI democratisation is pivotal. It simplifies data analysis and application, leading to transformative business insights and value. It's a trend that business leaders must recognize and adapt to, as AI democratisation holds the key to unlocking new levels of efficiency and innovation in the business world.