Digital Transformation Journey

In the wake of advances in generative AI and large language models (LLMs), there is excitement about what the technology means for businesses. But we should not forget that this advancement is also posing a catch-22 situation to the traditional leadership. The transformative potential and rapid acceleration of generative AI are creating an imperative for them to act quickly. They should rethink their skillsets and develop new skillsets like – ability to make better sense of data insights, ability to ask better questions, ability to learn from smart mistakes etc. It is true that ChatGPT has taken the world by storm. In just 5 days since its launch in November last year, it gained one million users, a feat that no other popular online services have managed to achieve. But it is not the only generative AI tool, others include Midjourney and Dall-E for images generation, GitHub Copilot for coding, and even conditional generative adversarial networks (cGAN) such as Pix2Pix, developed by

We all know that the adoption of Generative AI platform / tool has grown at a breakneck pace. The focus is often on Open AI's large language model, Chat-GPT. But GenAI does not stop at text generation. It also promises greater efficiency, improved output, and better use of resources to produce other content. However, organizations that want to take advantage of this should also be aware of the potential threat this technology has posed to the business world. This requires them to set few rules of the game to protect the sensitive data and customer privacy - to avoid running afoul of regulators. Despite all the excitement about the potential of the now widespread and easily accessible technology, there is growing concern about its legal admissibility and possible liability risks for companies. Not least the temporary ban on Chat-GPT in Italy has shown that GenAI's features entail many legal uncertainties. Companies that want to use GenAI in their own business should therefore

In the wake of advances in generative AI and large language models (LLMs), there is excitement about what this technology means for businesses. Chief executives, data leaders and AI experts are being scrutinised for their strategic next steps. From boosting productivity and reducing operational costs to finding new routes to revenue generation, generative AI could transform traditional business models. Running alongside this excitement is deep concern, inside the tech industry and beyond, that generative AI models are being developed too quickly blossoming into a new hype machine for the industry to follow with curiosity. While other recent hype cycles have failed to deliver, is this the one that will deliver on its promises? The short answer is yes. It will not be immediately used in the ways that sci-fi thrillers would lead you to believe, but business leaders across every industry will deploy AI to augment today’s workforce by eliminating ordinary tasks. In fact, business leaders wh

The Generative AI marketplace is on fire. Beyond the big platform players, there are many hundreds of specialty providers funded by ample venture capital and a wave of new open-source models and capabilities. Enterprise application providers, such as Salesforce and SAP, are building LLM capabilities into their platforms. Organizations like Microsoft, Google, Amazon Web Services (AWS) and IBM have invested hundreds of millions of dollars and massive compute power to build the foundational models on which services like ChatGPT and others depend.  The rapidly changing technology landscape pressures management teams to transform organizations. Generative AI (GenAI), a cutting-edge technology, accelerates this need to change. According to Forbes in January 2023, venture capital investments increased by a massive 425% in generative AI startups. Democratization of AI at such a rapid scale makes one believe that this technology is here to stay and will be immensely disruptive.  While there a