For decades, revenue forecasting has relied on a combination of CRM data, manager inspections, pipeline reviews, and seller judgment. But as AI gains access to more signals - from buyer engagement and sales activity to product usage and conversation intelligence - a new question is emerging: can AI identify revenue outcomes more accurately than the people closest to the deal? This session explores how leading organizations are using AI to improve forecast accuracy, identify deal risk earlier, and uncover signals that traditional forecasting methods often miss. Join us for a practical discussion on where AI is delivering measurable value today, where human judgment still matters most, and what the future of revenue forecasting could look like. You'll walk away with: - How leading GTM teams are incorporating AI into forecasting and revenue planning - The signals and data sources improving forecast confidence and accuracy - Where AI outperforms traditional forecasting approaches - and where it falls short - Practical lessons from organizations using AI to identify risk and predict outcomes earlier