Everyone has heard it: Your organization needs to be more productive. But how? Businesses are constantly challenged with adopting AI technology, managing rising costs and closing talent gaps. While AI can boost performance, the need for faster, more performant models is often stymied by inefficient handoffs between key roles within
AI is no longer a futuristic concept – it’s a mainstay in our daily lives, both personally and professionally. In the business world, AI is revolutionizing workflows, driving efficiency and speeding up processes. However, as organizations rush to benefit from this modern technology, they must prioritize the ethical and transparent
Large language models (LLMs), like ChatGPT and Microsoft Copilot, have moved quickly out of the novelty phase into widespread use across industries. Among other examples, these new technologies are being used to generate customer emails, summarize meeting notes, supplement patient care and offer legal analysis. As LLMs proliferate across organizations,
I believe the most important part of the analytics lifecycle is defining the business question being asked.
