Idea generation (IG) is critical for innovation and maintaining a competitive edge in today's fast-paced global market, where generating novel and valuable ideas is fundamental to a firm’s innovative capabilities and its long-term success. Traditional metrics of quality and quantity of ideas alone do not fully capture the success of an idea generation session, especially in an era where digital technologies are reshaping workplace dynamics. The effects of these technologies on IG processes remain largely unexplored, making it difficult for organizations to fully leverage digital advancements in their innovation strategies. This research examines the impact of three different idea generation techniques—AI-Assisted, Traditional, and Virtual—on the outcomes of IG sessions. It extends the commonly used measures of quality and quantity of ideas by incorporating measures of Fluency, Flexibility, and Intrinsic Motivation, offering a more comprehensive view of what constitutes as successful idea generation. AI-assisted idea generation uses tools like ChatGPT to help participants generate ideas individually before group discussion. Traditional idea generation involves participants gathering in the same room to generate and discuss ideas. Virtual idea generation uses platforms like Microsoft Teams, where participants generate ideas online utilizing a virtual whiteboard. The study utilized three distinct workshops to evaluate AI-assisted, Traditional, and Virtual idea generation techniques. Each workshop involved five participants from an IT consulting firm, who were tasked with generating ideas individually and then discussing them collectively. Data were collected through surveys, direct observations, and expert assessments of idea quality.