Organized by Ali Mortazavi, CEO, Davteq
Moderator: Randy Iwasaki, CEO, Iwasaki Consulting Services
Panelists:
- Ali Mortazavi, CEO, Davteq
- Tony Abuta, Director and Technologist – Global Smart Cities and Intelligent Transportation, Intel Corporation
- Dr Tamara Djukic, Head of Green & Urban Mobility, ERTICO, CEO & Co-Founder MLsquared
Artificial Intelligence has become the new frontier in transportation innovation — but also one of its biggest misconceptions. Agencies are collecting unprecedented volumes of data, yet decision-makers often face the same challenge: too much information, too little insight.
This session cuts through the noise to examine the myths and realities of applying AI in real transportation environments. It challenges assumptions like “more data equals better insight,” “AI will replace everything,” and “dashboards tell the full story.” Through real examples from field operations, data integration programs, and predictive mobility studies, the panel will reveal what it actually takes to make AI outputs meaningful, explainable, and trusted.
Structured as an interactive “Reality Lab”, the discussion blends rapid myth-busting, scenario challenges, and candid dialogue across public, private, and research perspectives. Participants will explore how to balance AI innovation with human expertise, bridge fragmented data silos, and build decision systems that are transparent, context-aware, and ethically grounded. The session goes beyond hype to envision a future where transportation AI systems don’t just automate — they reason, collaborate, and learn alongside the people who manage them.
By the end of this session, participants will:
- Identify the most common misconceptions about AI and data in transportation decision-making.
- Understand the technical and organizational realities of deploying AI for real-world mobility applications.
- Explore practical frameworks for building hybrid human-AI decision systems that are transparent and trustworthy.
- Recognize data quality, governance, and explainability as essential foundations for AI success.
- Envision how reasoning-based AI could shape the next decade of intelligent mobility.
