Read more about author Rod Garcia. From boosting efficiency to making data-driven decisions faster, the benefits of using AI and automation in the workplace are numerous. But understandably, there’s also plenty of apprehension among some team members. According to new research, around 80% of those who work in a digital setting and use AI say that it’s already improving their productivity. And yet, overall perceptions remain mixed, with 42% saying they’re…

Read more about author Katrina Ingram. At a recent presentation for a local post-secondary institution, I fielded a number of questions related to the use of language, primarily English language texts, as training data for generative AI. There were questions around cultural impacts and related ethical concerns. These queries were more nuanced than the usual ones I get around copyright or data reuse, which we tackled in last month’s column. So,…

Read more about author Herve Chapron. McKinsey analysts predict that enterprise employees will rely on data for almost every decision come 2025. If true, this development would mark a significant departure from the current business modus operandi. According to our research, only 25% of enterprise data professionals believe their organization’s decision-making process is data-backed or strategic.  How are these two concepts – the perception of data progress and the reality of disorganization – so distinct?…

Read more about author Hiral Rana. Large language models (LLMs) are a special type of AI model that uses natural language processing (NLP) to understand and generate text similar to human language. They are a form of generative AI trained on textual data to produce textual content. ChatGPT stands out as a well-known example of generative AI. Trained on massive datasets, LLMs can perform a broad spectrum of tasks with proficiency…