How do Rail leaders view Artificial Intelligence (AI), its benefits, challenges, and application areas? How have these views changed?
Thank you for participating. Princeton Consultants and Northwestern University Transportation Center have been joined this year by RailPulse to conduct this third annual survey. We are eager to see if and how responses differ from past years, and we have added several questions to obtain insights into usage of large volumes of Rail data and telematics. Your responses can be supplemented by a phone interview conducted by Princeton Consultants Rail Principal Keith Dierkx.
We will keep you and your organization anonymous in an executive summary that analyzes the responses and includes industry best practices and trends.
How do we define AI?
AI is the effort to automate intellectual tasks normally performed by humans. Examples of AI are Large Language Models (LLMs) that enable users to generate and refine content, code and conversations; self-driving vehicles; optimization solutions that recommend the best schedules and routes; and machine learning applications that ingest historical data and trends to predict demand.
