Generative AI (GenAI), especially LLMs, has transitioned from a buzzword to an essential business asset. Leading organisations have moved beyond the proof-of-concept (POC) phase and are now actively deploying GenAI solutions. Many non-technology companies have realised that developing proprietary LLMs is unnecessary for solving internal challenges . Instead, they acquire LLMs from vendors or the open-source marketplace. Originally published at LinkedIn Pulse on 23 March 2025

In today’s data-driven landscape, CDO, CAO, and CDAO are critical in steering organisations towards success. The journey began with the CDO, who introduced a data-centric culture by developing robust data strategies, ensuring data governance, and effectively managing data assets. As the volume and complexity of data grew, the need for specialised analytics expertise became apparent, leading to the creation of the CAO role. The CAO focused on transforming raw data into actiona

Artificial Intelligence (AI) is advancing rapidly, and agentic AI is emerging as a transformative innovation. This approach enables systems to tackle complex, multi-step challenges autonomously. Generative AI (GenAI) has laid the groundwork by demonstrating the ability to understand and generate human-like text, code, images, audio, and video based on vast datasets. These foundational models are crucial for agentic AI, providing capabilities for understanding and generating n

In the wake of the advent of Large Language Models (LLMs), a multitude of initiatives have been undertaken to enhance user experiences via Natural Language Processing (NLP). A vast array of articles has been penned to encourage organisations to embrace generative artificial intelligence (AI). These pieces, however, have predominantly focused on the impressive ability of LLMs to understand user inquiries and generate responses, and often criticise the fact that they overlook f