Study Reveals AI in Mobility Requires Unprecedented Global Collaboration to Reach Its Potential
Artificial intelligence is quietly transforming transportation systems around the globe, promising safer streets, cleaner energy, and more efficient urban mobility. Yet according to a landmark study launched at CoMotion GLOBAL 2025 in Riyadh, most AI deployments remain isolated pilots that have yet to scale, and the gap between AI’s potential and its real-world execution continues to widen.
The report, Envisioning the Future of Mobility Powered by AI, jointly developed by the MIT Mobility Initiative and the Kearney Advanced Mobility Institute, offers the most comprehensive global assessment of AI applications in urban and intercity transportation. Drawing insights from 55 leading organizations including Google, Lyft, Uber Freight, Deutsche Bahn, and NEOM, the study maps real-world deployments of AI across Europe, the Americas, Asia-Pacific, and the Middle East, identifying opportunities, risks, and systemic challenges that must be addressed to unlock AI’s transformative potential.
AI is Not Just a Smarter Algorithm
“Cities are waking up to the reality that AI isn’t just a smarter algorithm – it fundamentally changes how humans and machines share control,” said Dr. Christian Gasparic, Partner at Kearney and Global Head of the Kearney Advanced Mobility Institute. “Getting that balance right is a strategic, safety-critical decision that will define which cities succeed in building the next generation of mobility systems.”
The study emphasizes that AI does not merely replicate human decision-making. Instead, it Research performs exceptionally well in certain functions, such as predictive traffic management or route optimization, while sometimes failing unpredictably in other areas. This “jagged frontier” of AI performance presents both immense opportunity and potential risk, particularly in safety-critical transportation systems like autonomous fleets, adaptive traffic control, and automated enforcement.
Key Findings from the Study
The report identifies several fundamental dynamics shaping the future of AI in mobility:
1. Fragmented Adoption
Most AI applications in mobility – spanning network planning, autonomous driving, demand simulation, and crowd monitoring – are still in pilot phases. Few cities or operators have scaled these technologies to system-wide impact, limiting the overall benefits of AI deployment.
2. System-Level Coordination Multiplies Impact
AI’s full value emerges when it is deployed across entire transportation systems, optimizing fleets, infrastructure, energy use, and passenger flows simultaneously. Achieving this level of coordination requires unprecedented collaboration between public agencies, private operators, and technology providers.
3. Human-AI Pairing is Safety-Critical
In some applications, combining human operators with AI increases safety and reliability. In others, human intervention can inadvertently reduce system performance. Understanding how to calibrate the human-AI partnership has become a strategic imperative for city planners and mobility operators.
4. The Execution Gap is Widening
Without interoperable standards, shared data infrastructure, and coherent governance frameworks, regions risk fragmenting into competing and incompatible AI ecosystems. This could slow innovation and limit the societal benefits of AI-powered mobility.
5. High-Impact Applications Sit on the Jagged Frontier
Some of the most transformative applications – autonomous fleets, adaptive traffic control, AI-enabled enforcement – operate at the edge of current technical capabilities. Realizing their potential requires careful management of safety, regulatory compliance, and public trust.
Collaboration as the Key to Scaling AI
“Enormous opportunities exist, but execution is fragmented,” said John Moavenzadeh, Executive Director of the MIT Mobility Initiative. “Our study highlights a paradox: the greater the potential for AI to deliver safe, clean, and inclusive mobility, the harder it is to implement at scale. Success will require governments, regulators, operators, and technology leaders to collaborate across borders and share a unified vision for safety, efficiency, and trust.”
The report underscores that the future of AI in transportation is less about individual technological breakthroughs and more about ecosystem execution. Coordinated efforts among cities, technology providers, and mobility operators are essential to unlock AI’s transformative potential, from reducing congestion and improving public transit reliability to enhancing energy efficiency and ensuring equitable access.
Global Perspectives on AI in Mobility
Several contributing organizations emphasized the need for a human-centered approach to AI deployment:
- Kristin White, Head of Transportation Strategy and Partnerships at Google Public Sector, stated: “Public mission and placing humans at the center of problem solving is critical for AI to scale successfully and deliver safer, more resilient transportation systems.”
- Dr. Axel Sondermann, Executive Director at Deutsche Bahn, highlighted: “AI is already supporting our agenda of safe, reliable, and clean railway and bus services. The study shows its greatest value comes when solutions are deployed system-wide. Achieving this requires shared standards and industry collaboration to create better, more resilient mobility for all.”
These insights reinforce the study’s core message: isolated pilots are insufficient. Cities and operators must share data, align standards, and coordinate policies to ensure Research AI delivers measurable societal benefits.
Implication for Cities and Operators
The study reveals several practical considerations for urban planners, mobility providers, and policymakers:
- Data Infrastructure is Foundational – AI systems require high-quality, interoperable data to function effectively. Cities must invest in platforms that allow different agencies and operators to share information securely and efficiently.
- Standards Enable Scaling – Without common technical and regulatory standards, AI applications risk remaining siloed, preventing full-system optimization.
- Governance and Trust Matter – Public confidence in Research AI-enabled mobility depends on transparent decision-making, clear accountability, and robust safety oversight.
- Cross-Border Collaboration – Many AI mobility challenges, from autonomous trucking to shared-mobility platforms, transcend national borders. International collaboration accelerates learning and reduces the risk of fragmented deployment.
The report concludes that AI’s most transformative impact will be realized not by individual technology companies or city departments, but by collective, coordinated action across the mobility ecosystem. By combining expertise from the public and private sectors, cities can implement AI at scale while maintaining safety, equity, and resilience.
“Launching this research at CoMotion GLOBAL in Riyadh is a milestone,” said John Rossant, Founder & CEO of CoMotion.
If the world wants clean, inclusive, and safe transportation systems, the next leap won’t come from individual breakthroughs; it will come from collaboration. Our role is to bring governments, operators, technologists, and cities together so this future can be built, not just imagined.
The study serves as both a Research roadmap and a call to action. For cities and mobility operators, the message is clear: the future of transportation will depend as much on partnerships and shared governance as on artificial intelligence itself. Only through unprecedented collaboration can the promise of AI-powered mobility – safer streets, lower emissions, and equitable access – be fully realized.
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